awesome-scalability
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
https://github.com/eric-erki/awesome-scalability
Last synced: 19 days ago
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Scalability
- Alerting Framework at Airbnb
- Event Sourcing (2 parts) at eBay
- Event Sourcing at mytaxi
- Elasticsearch at Target
- DynamoDB at Nike
- DynamoDB at Segment
- DynamoDB at Mapbox
- Tracking Service Infrastructure at Scale at Shopify
- Distributed Tracing at HelloFresh
- Distributed Tracing at Uber
- JVM Profiler: Tracing Distributed JVM Applications at Uber
- Data Checking at Dropbox
- osquery Across the Enterprise at Palantir
- StatsD at DoorDash
- Chronos: A Replacement for Cron at Airbnb
- Scheduler at Nextdoor
- Peloton: Unified Resource Scheduler for Diverse Cluster Workloads at Uber
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow
- Airflow at Airbnb
- Airflow at Pandora
- Airflow at Robinhood
- Airflow at Lyft
- Airflow at Grab
- Airflow at Adobe
- MaaT: DAG-based Distributed Task Scheduler at Alibaba
- boundary-layer: Declarative Airflow Workflows at Etsy
- Monitoring System at Alibaba
- Real User Monitoring at Dailymotion
- Alerting Ecosystem at Uber
- Microservices and Orchestration
- Evolution of Container Usage at Netflix
- Dockerizing MySQL at Uber
- Docker in Production at Treehouse
- Operate Kubernetes Reliably at Stripe
- Kubernetes Traffic Routing (2 parts) at Rakuten
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- Docker Containers that Power Over 100.000 Online Shops at Shopify
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- From bare-metal to Kubernetes at Betabrand
- Kubernetes Platform at Pinterest
- Microservices at Nubank
- GRIT: Protocol for Distributed Transactions across Microservices at eBay
- Rubix: Kubernetes at Palantir
- Distributed Caching
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Memsniff: Robust Memcache Traffic Analyzer at Box
- Caching Internal Service Calls at Yelp
- Application Data Caching from RAM to SSD at NetFlix
- Tradeoffs of Replicated Cache at Skyscanner
- Avoiding Cache Stampede at DoorDash
- Location Caching with Quadtrees at Yext
- Scaling Redis at Twitter
- Moving persistent data out of Redis at Github
- Storing Hundreds of Millions of Simple Key-Value Pairs in Redis at Instagram
- Optimizing Redis Storage at Deliveroo
- Redis Fleet at Heroku
- HTTP Caching and CDN
- Zynga Geo Proxy: Reducing Mobile Game Latency at Zynga
- Google AMP at Condé Nast
- A/B Tests on Hosting Infrastructure (CDNs) at Deliveroo
- CDN in LIVE's Encoder Layer at LINE
- Chubby: Lock Service for Loosely Coupled Distributed Systems at Google
- Distributed Locking at Uber
- Eliminating Duplicate Queries using Distributed Locking at Chartio
- Real-time Distributed Tracing at LinkedIn
- Job-based Forecasting Workflow for Observability Anomaly Detection at Uber
- Monitoring and Alert System using Graphite and Cabot at HackerEarth
- Unicorn: Remediation System at eBay
- M3: Metrics and Monitoring Platform at Uber
- Nuage: Cloud Management Service at LinkedIn
- ThirdEye: Monitoring Platform at LinkedIn
- Data Pipeline Monitoring System at LinkedIn
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- LISA: Distributed Firewall at LinkedIn
- Secure Infrastructure To Store Bitcoin In The Cloud at Coinbase
- BinaryAlert: Real-time Serverless Malware Detection at Airbnb
- Scalable IAM Architecture to Secure Access to 100 AWS Accounts at Segment
- Active Directory Password Blacklisting at Yelp
- Athenz: Fine-Grained, Role-Based Access Control at Yahoo
- Unprivileged Container Builds at Kinvolk
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- AVA: Audit Web Applications at Indeed
- TTL as a Service: Automatic Revocation of Stale Privileges at Yelp
- Scalability and Authentication at Twitch
- Distributed Messaging, Queuing, and Event Streaming
- Brooklin: Distributed Service for Near Real-Time Data Streaming at LinkedIn
- Samza: Stream Processing System for Latency Insighs at LinkedIn
- Bullet: Forward-Looking Query Engine for Streaming Data at Yahoo
- Cherami: Message Queue System for Transporting Async Tasks at Uber
- Dynein: Distributed Delayed Job Queueing System at Airbnb
- Debugging Production with Event Logging at Zillow
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Benchmarking Streaming Computation Engines at Yahoo
- Improving Stream Data Quality With Protobuf Schema Validation at Deliveroo
- Event Stream Database at Nike
- Event-Driven Messaging
- Domain-Driven Design at Alibaba
- Scaling Event-Sourcing at Jet.com
- Elasticsearch at Kickstarter
- Pulsar: Pub-Sub Messaging at Scale at Yahoo
- Pub-Sub in Chatting Architecture at LINE
- Pub-Sub in Microservices at Netflix
- Kafka the Message Broker
- Kafka at LinkedIn
- Kafka at Pinterest
- Kafka at Rakuten
- Kafka at The New York Times
- Kafka at Yelp
- Kafka on Kubernetes at Shopify
- Migrating Kafka's Zookeeper with No Downtime at Yelp
- Reprocessing and Dead Letter Queues with Kafka at Uber
- Chaperone: Audit Kafka End-to-End at Uber
- InfluxDB and Kafka to Scale to Over 1 Million Metrics a Second at Hulu
- Stream Data Deduplication
- Exactly-once Semantics with Kafka
- Real-time Deduping at Tapjoy
- Deduplication at Segment
- Deduplication at Mail.Ru
- Petabyte Scale Data Deduplication at Mixpanel
- Distributed Logging
- Logging at LinkedIn
- Log Parsing with Static Code Analysis at Palantir
- Centralized Application Logging at eBay
- BookKeeper: Distributed Log Storage at Yahoo
- LogFeeder: Log Collection System at Yelp
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Distributed Searching
- Search Architecture at Instagram
- Search Architecture at eBay
- Search Architecture at Box
- Universal Search System at Pinterest
- Improving Search Engine Efficiency by over 25% at eBay
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Query Understanding at TripAdvisor
- Search Federation Architecture at LinkedIn (2018)
- Search and Recommendations at DoorDash
- Autocomplete Search (2 parts) at Traveloka
- Galene: Search Architecture of LinkedIn
- Sherlock: Near Real Time Search Indexing at Flipkart
- Nebula: Storage Platform to Build Search Backends at Airbnb
- ELK (Elasticsearch, Logstash, Kibana) Stack
- Predictions in Real Time with ELK at Uber
- ELK at Robinhood
- Elasticsearch Performance Tuning Practice at eBay
- Dotfiles Distribution at Booking.com
- Secret Detector: Preventing Secrets in Source Code at Yelp
- Managing Software Dependency at Scale at LinkedIn
- NoSQL Databases
- Fast Order Search using Data Pipeline and Elasticsearch at Yelp
- Moving Core Business Search to Elasticsearch at Yelp
- Upgrading Elasticsearch (3 parts) at Redmart
- Vulcanizer: a library for operating Elasticsearch at Github
- Distributed Storage
- In-memory Storage
- MemSQL Architecture - The Fast (MVCC, InMem, LockFree, CodeGen) And Familiar (SQL)
- Real-Time Data Warehouse with MemSQL on Cisco UCS
- Moving to MemSQL at Tapjoy
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- Scaling HDFS at Uber
- File System on Amazon S3 at Quantcast
- Cloud Object Store at Yahoo
- Ambry: Distributed Immutable Object Store at LinkedIn
- Dynamometer: Scale Testing HDFS on Minimal Hardware with Maximum Fidelity at LinkedIn
- Hammerspace: Persistent, Concurrent, Off-heap Storage at Airbnb
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Relational Databases
- MySQL for Schema-less Data at FriendFeed
- PostgreSQL at Twitch
- Scaling MySQL-based Financial Reporting System at Airbnb
- Scaling MySQL at Wix
- MaxScale (MySQL) Database Proxy at Airbnb
- Switching from Postgres to MySQL at Uber
- Handling Growth with Postgres at Instagram
- Updating a 50 Terabyte PostgreSQL Database at Adyen
- MySQL Parallel Replication (4 parts) at Booking.com
- Mitigating MySQL Replication Lag and Reducing Read Load at Github
- Black-Box Auditing: Verifying End-to-End Replication Integrity between MySQL and Redshift at Yelp
- Monitoring MySQL Delayed Replication at IMVU
- Partitioning Main MySQL Database at Airbnb
- Herb: Multi-DC Replication Engine for Schemaless Datastore at Uber
- Sharding
- Sharding MySQL at Square
- Sharding Layer of Schemaless Datastore at Uber
- Sharding & IDs at Instagram
- Solr: Improving Performance for Batch Indexing at Box
- Presto Infrastructure at Lyft
- Presto at Grab
- Engineering Data Analytics with Presto and Apache Parquet at Uber
- Presto in Big Data Platform on AWS at Netflix
- Sherpa: Distributed NoSQL Key-Value Store at Yahoo
- HaloDB: Embedded Key-Value Storage Engine at Yahoo
- zBase: High Performance, Elastic, Distributed Key-Value Store at Zynga
- Venice: Distributed Key-Value Database at Linkedin
- Cassandra at Instagram
- Scaling Ad Analytics with Cassandra at Yelp
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Moving Food Feed from Redis to Cassandra at Zomato
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- HBase
- HBase at Xiaomi
- Redshift
- Redshift at GIPHY
- Redshift at Hudl
- eBay: Building Mission-Critical Multi-Data Center Applications with MongoDB
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- Couchbase Ecosystem at LinkedIn
- SimpleDB at Zendesk
- Espresso: Distributed Document Store at LinkedIn
- Time Series Databases
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Scaling Time Series Data Storage (2 parts) at Netflix
- Real-time Analytics Database (Druid)
- Druid at Airbnb
- Distributed Repositories, Dependencies, and Configurations Management
- DGit: Distributed Git at Github
- Stemma: Distributed Git Server at Palantir
- Configuration Management for Distributed Systems at Flickr
- Single Repository at Google
- Scaling Infrastructure and (Git) Workflow at Adyen
- Scaling Continuous Integration and Continuous Delivery
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Screwdriver: Continuous Delivery Build System for Dynamic Infrastructure at Yahoo
- Scaling Jira Server at Yelp
- Auto-scaling CI/CD cluster at Flexport
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- SimpleDB at Zendesk
- Stemma: Distributed Git Server at Palantir
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Scaling Time Series Data Storage (2 parts) at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Kafka at The New York Times
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- Kafka at The New York Times
- Petabyte Scale Data Deduplication at Mixpanel
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Log Parsing with Static Code Analysis at Palantir
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Kafka at The New York Times
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Auto-scaling CI/CD cluster at Flexport
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Evolution of Container Usage at Netflix
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- Evolution of Container Usage at Netflix
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Kafka at The New York Times
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Pub-Sub in Microservices at Netflix
- Kafka at The New York Times
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- Tracing Distributed Systems at Showmax
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Kafka at The New York Times
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Stemma: Distributed Git Server at Palantir
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Stemma: Distributed Git Server at Palantir
- Auto-scaling CI/CD cluster at Flexport
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Stemma: Distributed Git Server at Palantir
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Distributed Cache at Zalando
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- SimpleDB at Zendesk
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Stemma: Distributed Git Server at Palantir
- Auto-scaling CI/CD cluster at Flexport
- Conductor: Microservices Orchestrator at Netflix
- Rubix: Kubernetes at Palantir
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Distributed Tracing at HelloFresh
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Benchmarking Cassandra Scalability on AWS at Netflix
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- Auto-scaling CI/CD cluster at Flexport
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Kafka at The New York Times
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Stemma: Distributed Git Server at Palantir
- Auto-scaling CI/CD cluster at Flexport
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Kafka at The New York Times
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- Atlas: In-memory Dimensional Time Series Database at Netflix
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Stemma: Distributed Git Server at Palantir
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Conductor: Microservices Orchestrator at Netflix
- Rubix: Kubernetes at Palantir
- Distributed Scheduling
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Detecting Credential Compromise in AWS at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Distributed Tracing at HelloFresh
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Stemma: Distributed Git Server at Palantir
- Auto-scaling CI/CD cluster at Flexport
- Benchmarking Cassandra Scalability on AWS at Netflix
- Elasticsearch at Kickstarter
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Kafka at The New York Times
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- Pub-Sub in Microservices at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Stemma: Distributed Git Server at Palantir
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Stemma: Distributed Git Server at Palantir
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Distributed Tracing at HelloFresh
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Elasticsearch at Kickstarter
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Auto-scaling CI/CD cluster at Flexport
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Stemma: Distributed Git Server at Palantir
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Conductor: Microservices Orchestrator at Netflix
- Rubix: Kubernetes at Palantir
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Distributed Tracing at HelloFresh
- Pub-Sub in Microservices at Netflix
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Elasticsearch at Kickstarter
- Atlas: In-memory Dimensional Time Series Database at Netflix
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- Stemma: Distributed Git Server at Palantir
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Auto-scaling CI/CD cluster at Flexport
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Pub-Sub in Microservices at Netflix
- Kafka at The New York Times
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- Auto-scaling CI/CD cluster at Flexport
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- Pub-Sub in Microservices at Netflix
- Kafka at The New York Times
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Elasticsearch at Kickstarter
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- DynamoDB at Mapbox
- Benchmarking Cassandra Scalability on AWS at Netflix
- Sharding & IDs at Instagram
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Scaling Time Series Data Storage (2 parts) at Netflix
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Stemma: Distributed Git Server at Palantir
- Auto-scaling CI/CD cluster at Flexport
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Evolution of Container Usage at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- Scaling Time Series Data Storage (2 parts) at Netflix
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Stemma: Distributed Git Server at Palantir
- Auto-scaling CI/CD cluster at Flexport
- Video Gatekeeper at Netflix
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Stemma: Distributed Git Server at Palantir
- Auto-scaling CI/CD cluster at Flexport
- Conductor: Microservices Orchestrator at Netflix
- Agrarian-Scale Kubernetes (3 parts) at New York Times
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Elasticsearch at Kickstarter
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Sharding & IDs at Instagram
- Benchmarking Cassandra Scalability on AWS at Netflix
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- SimpleDB at Zendesk
- Stemma: Distributed Git Server at Palantir
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Airflow at Lyft
- Airflow at Adobe
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Presto Infrastructure at Lyft
- Elasticsearch at Kickstarter
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- SimpleDB at Zendesk
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- Atlas: In-memory Dimensional Time Series Database at Netflix
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- Auto-scaling CI/CD cluster at Flexport
- Stemma: Distributed Git Server at Palantir
- Rubix: Kubernetes at Palantir
- Distributed Tracing at HelloFresh
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Conductor: Microservices Orchestrator at Netflix
- Rubix: Kubernetes at Palantir
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Kafka at The New York Times
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Scaling Time Series Data Storage (2 parts) at Netflix
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Stemma: Distributed Git Server at Palantir
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Auto-scaling CI/CD cluster at Flexport
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Detecting Credential Compromise in AWS at Netflix
- Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Auto-scaling CI/CD cluster at Flexport
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Stemma: Distributed Git Server at Palantir
- PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache: Distributed In-memory Caching at Netflix
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- Atlas: In-memory Dimensional Time Series Database at Netflix
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Elasticsearch at Kickstarter
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- SimpleDB at Zendesk
- Auto-scaling CI/CD cluster at Flexport
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Search Architecture at Instagram
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- Auto-scaling CI/CD cluster at Flexport
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Kafka at The New York Times
- Petabyte Scale Data Deduplication at Mixpanel
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- Elasticsearch at Kickstarter
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- SimpleDB at Zendesk
- Auto-scaling CI/CD cluster at Flexport
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Conductor: Microservices Orchestrator at Netflix
- Rubix: Kubernetes at Palantir
- Distributed Tracing at HelloFresh
- Evolution of Container Usage at Netflix
- Conductor: Microservices Orchestrator at Netflix
- Rubix: Kubernetes at Palantir
- Distributed Tracing at HelloFresh
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Detecting Credential Compromise in AWS at Netflix
- Kafka at The New York Times
- SimpleDB at Zendesk
- Log Parsing with Static Code Analysis at Palantir
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Elasticsearch at Kickstarter
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Scaling Time Series Data Storage (2 parts) at Netflix
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- Stemma: Distributed Git Server at Palantir
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Conductor: Microservices Orchestrator at Netflix
- Microservice Architecture at Medium
- Rubix: Kubernetes at Palantir
- EVCache Cache Warmer Infrastructure at Netflix
- Application Data Caching from RAM to SSD at NetFlix
- ZooKeeper at Twitter
- Zipkin: Distributed Systems Tracing at Twitter
- Distributed Tracing at HelloFresh
- osquery Across the Enterprise at Palantir
- Observability (2 parts) at Twitter
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Airflow at Adobe
- Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- Pub-Sub in Microservices at Netflix
- Petabyte Scale Data Deduplication at Mixpanel
- High-performance Replicated Log Service at Twitter
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Indexing and Querying Telemetry Logs with Lucene at Palantir
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Stemma: Distributed Git Server at Palantir
- Sharding & IDs at Instagram
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Manhattan: Distributed Key-Value Database at Twitter
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Service Decomposition at Scale with Cassandra at Intuit QuickBooks
- Scaling iOS CI with Anka at Shopify
- Migrating Mountains of Mongo Data at Addepar
- SimpleDB at Zendesk
- FlockDB: Distributed Graph Database at Twitter
- MetricsDB: TimeSeries Database for storing metrics at Twitter
- Atlas: In-memory Dimensional Time Series Database at Netflix
- Auto-scaling CI/CD cluster at Flexport
- Scaling Time Series Data Storage (2 parts) at Netflix
- Dynamic Configuration at Twitter
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- Auto-scaling CI/CD cluster at Flexport
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Video Gatekeeper at Netflix
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Evolution of Container Usage at Netflix
- Conductor: Microservices Orchestrator at Netflix
- Rubix: Kubernetes at Palantir
- Auto-scaling CI/CD cluster at Flexport
- Kafka at The New York Times
- Distributed Tracing at HelloFresh
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Detecting Credential Compromise in AWS at Netflix
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Sharding & IDs at Instagram
- Elasticsearch at Kickstarter
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- Presto Infrastructure at Lyft
- Presto in Big Data Platform on AWS at Netflix
- DynamoDB at Mapbox
- The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
- SimpleDB at Zendesk
- Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
- Benchmarking Cassandra Scalability on AWS at Netflix
- Scaling Time Series Data Storage (2 parts) at Netflix
- Stemma: Distributed Git Server at Palantir
- Continuous Integration with Distributed Repositories and Dependencies at Netflix
- Video Gatekeeper at Netflix
- Kafka at The New York Times
- Conductor: Microservices Orchestrator at Netflix
- Rubix: Kubernetes at Palantir
- MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
- MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
- Distributed Tracing at HelloFresh
- Scheduler at Nextdoor
- Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
- Airflow at Pandora
- Airflow at Lyft
- Detecting Credential Compromise in AWS at Netflix
- Cross-platform In-app Messaging Orchestration Service at Netflix
- Log Parsing with Static Code Analysis at Palantir
- DBLog: Generic Change-Data-Capture Framework at Netflix
- Elasticsearch at Kickstarter
- Sharding & IDs at Instagram
-
Intelligence
- Computer Vision at Airbnb
- 3D Home Backend Algorithms at Zillow
- Long-term Forecasts at Lyft
- Log Analysis Platform at LINE
- Data Visualisation Platform at Myntra
- Building and Scaling Data Lineage at Netflix
- Data Platform at Uber
- Data Platform at Netflix
- Data Platform at Flipkart
- Data Infrastructure at Airbnb
- Data Infrastructure at GO-JEK
- Big Data Processing at Uber
- Analytics Pipeline at Lyft
- Analytics Pipeline at Teads
- Big Data Analytics and ML Techniques at LinkedIn
- Self-Serve Reporting Platform on Hadoop at LinkedIn
- Privacy-Preserving Analytics and Reporting at LinkedIn
- RBEA: Real-time Analytics Platform at King
- AresDB: GPU-Powered Real-time Analytics Engine at Uber
- AthenaX: Streaming Analytics Platform at Uber
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Databook: Turning Big Data into Knowledge with Metadata at Uber
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Maze: Funnel Visualization Platform at Uber
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- SpinalTap: Change Data Capture System at Airbnb
- Accelerator: Fast Data Processing Framework at eBay
- Omid: Transaction Processing Platform at Yahoo
- TensorFlowOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo
- CaffeOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo
- Spark on Scala: Analytics Reference Architecture at Adobe
- Experimentation Platform at Airbnb
- Scaling a Mature Data Pipeline - Managing Overhead at Airbnb
- Distributed Machine Learning
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Michelangelo: Machine Learning Platform at Uber
- Scaling Michelangelo
- Horovod: Open Source Distributed Deep Learning Framework for TensorFlow at Uber
- COTA: Improving Customer Care with NLP & Machine Learning at Uber
- Manifold: Model-Agnostic Visual Debugging Tool for Machine Learning at Uber
- Repo-Topix: Topic Extraction Framework at Github
- Concourse: Generating Personalized Content Notifications in Near-Real-Time at LinkedIn
- Altus Care: Applying a Chatbot to Platform Engineering at eBay
- Box Graph: Spontaneous Social Network at Box
- PricingNet: Pricing Modelling with Neural Networks at Skyscanner
- PinText: Multitask Text Embedding System at Pinterest
- Scaling Gradient Boosted Trees for Click-Through-Rate Prediction at Yelp
- Deep Learning for Image Classification Experiment at Mercari
- Improving Photo Selection With Deep Learning at TripAdvisor
- Personalized Recommendations for Experiences Using Deep Learning at TripAdvisor
- Machine Learning (2 parts) at Condé Nast
- Natural Language Processing and Content Analysis (2 parts) at Condé Nast
- Machine Learning Applications In The E-commerce Domain (4 parts) at Rakuten
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Machine Learning to Match Drivers & Riders at GO-JEK
- Improving Video Thumbnails with Deep Neural Nets at YouTube
- Quantile Regression for Delivering On Time at Instacart
- Machine Learning at Jane Street
- Similarity Search at Flickr
- Atom Smashing using Machine Learning at CERN
- Mapping Tags at Medium
- Clustering with the Dirichlet Process Mixture Model in Scala at Monsanto
- Map Pins with DBSCAN & Random Forests at Foursquare
- Detecting and Preventing Fraud at Uber
- Forecasting at Uber
- Financial Forecasting at Uber
- GUI Testing Powered by Deep Learning at eBay
- Automated Fake Account Detection at LinkedIn
- Building Knowledge Graph at Airbnb
- Core Modeling at Instagram
- Neural Architecture Search (NAS) for Prohibited Item Detection at Mercari
- Discovering Popular Dishes with Deep Learning at Yelp
- Jobs Filter at Indeed
- Architecting Restaurant Wait Time Predictions at Yelp
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Keystone: Real-time Stream Processing Platform at Netflix
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Spark on Scala: Analytics Reference Architecture at Adobe
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Spark on Scala: Analytics Reference Architecture at Adobe
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Spark on Scala: Analytics Reference Architecture at Adobe
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Machine Learning (2 parts) at Condé Nast
- Natural Language Processing and Content Analysis (2 parts) at Condé Nast
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Spark on Scala: Analytics Reference Architecture at Adobe
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Long-term Forecasts at Lyft
- Core Modeling at Instagram
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Spark on Scala: Analytics Reference Architecture at Adobe
- Building and Scaling Data Lineage at Netflix
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Spark on Scala: Analytics Reference Architecture at Adobe
- Smart Product Platform at Zalando
- Building and Scaling Data Lineage at Netflix
- Long-term Forecasts at Lyft
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Cross-Lingual End-to-End Product Search with Deep Learning at Zalando
- Mapping Tags at Medium
- Core Modeling at Instagram
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Spark on Scala: Analytics Reference Architecture at Adobe
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Mapping Tags at Medium
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Scaling Machine Learning to Recommend Driving Routes at Pivotal
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Spark on Scala: Analytics Reference Architecture at Adobe
- Building and Scaling Data Lineage at Netflix
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Long-term Forecasts at Lyft
- Mapping Tags at Medium
- Core Modeling at Instagram
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Spark on Scala: Analytics Reference Architecture at Adobe
- Building and Scaling Data Lineage at Netflix
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Mapping Tags at Medium
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Mapping Tags at Medium
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Data Analytics Architecture at Pinterest
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Long-term Forecasts at Lyft
- Building and Scaling Data Lineage at Netflix
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Spark on Scala: Analytics Reference Architecture at Adobe
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Quantile Regression for Delivering On Time at Instacart
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Quantile Regression for Delivering On Time at Instacart
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Keystone: Real-time Stream Processing Platform at Netflix
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Mapping Tags at Medium
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Spark on Scala: Analytics Reference Architecture at Adobe
- Quantile Regression for Delivering On Time at Instacart
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Long-term Forecasts at Lyft
- Long-term Forecasts at Lyft
- Mapping Tags at Medium
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Core Modeling at Instagram
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Mapping Tags at Medium
- Core Modeling at Instagram
- Long-term Forecasts at Lyft
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Core Modeling at Instagram
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Long-term Forecasts at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Mapping Tags at Medium
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Keystone: Real-time Stream Processing Platform at Netflix
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Long-term Forecasts at Lyft
- Building and Scaling Data Lineage at Netflix
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Keystone: Real-time Stream Processing Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Core Modeling at Instagram
- Mapping Tags at Medium
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Productionizing ML with Workflows at Twitter
- Long-term Forecasts at Lyft
- SplitNet Architecture for Ad Candidate Ranking at Twitter
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Long-term Forecasts at Lyft
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Spark on Scala: Analytics Reference Architecture at Adobe
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
- Delta: Data Synchronization and Enrichment Platform at Netflix
- Amundsen: Data Discovery & Metadata Engine at Lyft
- Metacat: Making Big Data Discoverable and Meaningful at Netflix
- Long-term Forecasts at Lyft
- Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
- Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
- Machine Learning to Improve Streaming Quality at Netflix
- Quantile Regression for Delivering On Time at Instacart
-
Interview
- Netflix: What Happens When You Press Play?
- Monzo: How Peer-To-Peer Payments Work
- Transit and Peering: How Your Requests Reach GitHub
- Designing Large-Scale Systems
- My Scaling Hero - Jeff Atwood (a dose of Endorphins before your interview, JK)
- Software Engineering Advice from Building Large-Scale Distributed Systems - Jeff Dean
- Introduction to Architecting Systems for Scale
- Anatomy of a System Design Interview
- 8 Things You Need to Know Before a System Design Interview
- Top 10 System Design Interview Questions
- Cloud Big Data Design Patterns - Lynn Langit
- How NOT to design Netflix in your 45-minute System Design Interview?
- API Best Practices: Webhooks, Deprecation, and Design
- OSI and TCP/IP Cheat Sheet
- Paxos Made Live – An Engineering Perspective
- SQL Transaction Isolation Levels Explained
- "What Happens When... and How" Questions
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- How to do Distributed Locking
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- OSI and TCP/IP Cheat Sheet
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- OSI and TCP/IP Cheat Sheet
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- OSI and TCP/IP Cheat Sheet
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- OSI and TCP/IP Cheat Sheet
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
- Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
-
Organization
- Engineering Roles at Palantir
- Scaling Engineering Teams at Twitter
- Scaling Decision-Making Across Teams at LinkedIn
- Scaling Data Science Team at GOJEK
- Scaling Agile at bol.com
- Hiring, Managing, and Scaling Engineering Teams at Typeform
- Scaling the Datagram Team at Instagram
- Team Model for Scaling a Design System at Salesforce
- Building Analytics Team (4 parts) at Wish
- From 2 Founders to 1000 Employees at Transferwise
- Lessons Learned Growing a UX Team from 10 to 170 at Adobe
- Using Metrics to Improve the Development Process (and Coach People) at Indeed
- Mistakes to Avoid while Creating an Internal Product at Skyscanner
- Distributed Responsibility at Asana
- Code Review at Palantir
- Code Review at LINE
- Code Reviews at Medium
- Code Review at LinkedIn
- Code Review at Disney
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Engineering Roles at Palantir
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Engineering Roles at Palantir
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Engineering Roles at Palantir
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Engineering Roles at Palantir
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Scaling the Datagram Team at Instagram
- Engineering Roles at Palantir
- Code Review at Palantir
- Code Reviews at Medium
- Code Review at Palantir
- Scaling the Datagram Team at Instagram
- Code Reviews at Medium
- Engineering Roles at Palantir
- Scaling Agile at Zalando
- Scaling the Datagram Team at Instagram
- Four Pillars of Leading People (Empathy, Inspiration, Trust, Honesty) at Zalando
- Rotating Engineers at Zalando
- Code Review at Palantir
- Code Reviews at Medium
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Engineering Roles at Palantir
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Engineering Roles at Palantir
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Code Reviews at Medium
- Scaling the Datagram Team at Instagram
- Engineering Roles at Palantir
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Engineering Roles at Palantir
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Code Review at Palantir
- Code Reviews at Medium
- Scaling the Datagram Team at Instagram
- Engineering Roles at Palantir
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Code Review at Palantir
- Scaling the Datagram Team at Instagram
- Code Reviews at Medium
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Engineering Roles at Palantir
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Scaling the Datagram Team at Instagram
- Code Review at Palantir
- Code Reviews at Medium
- Engineering Roles at Palantir
- Scaling the Datagram Team at Instagram
- Pair Programming at Shopify
- Code Review at Palantir
- Code Reviews at Medium
- Engineering Roles at Palantir
- Engineering Roles at Palantir
-
Principle
- Performance is a Feature
- Automate and Abstract: Lessons at Facebook
- (UI) Design Doesn’t Scale - Stanley Wood, Design Director at Spotify
- Building Fast and Resilient Web Applications - Ilya Grigorik
- Accept Partial Failures, Minimize Service Loss
- Design for Resiliency
- Learn from Mistakes
- Lessons from Giant-Scale Services - Eric Brewer, UC Berkeley & Google
- Designs, Lessons and Advice from Building Large Distributed Systems - Jeff Dean, Google
- Things to Keep in Mind When Building a Platform for the Enterprise - Heidi Williams, VP Platform at Box
- Principles of Chaos Engineering
- Finding the Order in Chaos
- The Twelve-Factor App
- Monoliths and Microservices
- Stateless vs Stateful Scalability
- Scale Up vs Scale Out
- Scale Up vs Scale Out: Hidden Costs
- Best Practices for Scaling Out
- Best Practices for Continuous Delivery
- ACID and BASE
- Performance and Scalability of Databases
- Database Isolation Levels and Effects on Performance and Scalability
- The Probability of Data Loss in Large Clusters
- Data Access for Highly-Scalable Solutions: Using SQL, NoSQL, and Polyglot Persistence
- SQL vs NoSQL
- NoSQL Databases: Survey and Decision Guidance
- How Sharding Works
- Don’t be tricked by the Hashing Trick
- Uniform Consistent Hashing at Netflix
- Eventually Consistent - Werner Vogels, CTO at Amazon
- Cache is King
- Anti-Caching
- Understand Latency
- Latency Numbers Every Programmer Should Know
- Architecture Issues When Scaling Web Applications: Bottlenecks, Database, CPU, IO
- Common Bottlenecks
- Life Beyond Distributed Transactions
- Relying on Software to Redirect Traffic Reliably at Various Layers
- Breaking Things on Purpose
- Avoid Over Engineering
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- Uniform Consistent Hashing at Netflix
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- Uniform Consistent Hashing at Netflix
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- Uniform Consistent Hashing at Netflix
- NoSQL Databases: Survey and Decision Guidance
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- Don’t be tricked by the Hashing Trick
- Uniform Consistent Hashing at Netflix
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- Uniform Consistent Hashing at Netflix
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- Uniform Consistent Hashing at Netflix
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- Simplicity by Distributing Complexity
- NoSQL Databases: Survey and Decision Guidance
- Uniform Consistent Hashing at Netflix
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- Uniform Consistent Hashing at Netflix
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- Uniform Consistent Hashing at Netflix
- NoSQL Databases: Survey and Decision Guidance
- Uniform Consistent Hashing at Netflix
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- NoSQL Databases: Survey and Decision Guidance
- NoSQL Databases: Survey and Decision Guidance
- NoSQL Databases: Survey and Decision Guidance
- Don’t be tricked by the Hashing Trick
- Uniform Consistent Hashing at Netflix
- NoSQL Databases: Survey and Decision Guidance
- NoSQL Databases: Survey and Decision Guidance
-
Availability
- Resilience Engineering: Learning to Embrace Failure
- Resilience Engineering with Project Waterbear at LinkedIn
- Resiliency against Traffic Oversaturation at iHeartRadio
- Resiliency in Distributed Systems at GO-JEK
- Resilience at Shopify
- The Evolution of Global Traffic Routing and Failover
- Testing for Disaster Recovery Failover Testing
- MySQL High Availability at GitHub
- Introduction to Modern Network Load Balancing and Proxying
- Top Five (Load Balancing) Scalability Patterns
- Load Balancing infrastructure to support more than 1.3 billion users at Facebook
- Load Balancing with Eureka at Netflix
- Edge Load Balancing at Netflix
- Zuul 2: Cloud Gateway at Netflix
- Load Balancing at Yelp
- Load Balancing at Github
- Consistent Hashing to Improve Load Balancing at Vimeo
- UDP Load Balancing at 500 pixel
- QALM: QoS Load Management Framework at Uber
- Traffic Steering using Rum DNS at LinkedIn
- Cloud Bouncer: Distributed Rate Limiting at Yahoo
- Scaling API with Rate Limiters at Stripe
- Rate Limiting at Etsy
- Quotas Service at Grab
- Autoscaling Based on Request Queuing at Square
- Autoscaling AWS Step Functions Activities at Yelp
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Clusterman: Autoscaling Mesos Clusters at Yelp
- Availability in Globally Distributed Storage Systems at Google
- NodeJS High Availability at Yahoo
- Operations (11 parts) at LinkedIn
- Monitoring Powers High Availability for LinkedIn Feed
- Globalizing Player Accounts at Riot Games
- Edge Load Balancing at Netflix
- Eliminate the Database for Higher Availability at American Express
- Introduction to Modern Network Load Balancing and Proxying
- Scryer: Predictive Auto Scaling Engine at Netflix
- Resiliency against Traffic Oversaturation at iHeartRadio
- Introduction to Modern Network Load Balancing and Proxying
- Load Balancing with Eureka at Netflix
- Edge Load Balancing at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Resiliency against Traffic Oversaturation at iHeartRadio
- Introduction to Modern Network Load Balancing and Proxying
- Load Balancing with Eureka at Netflix
- Edge Load Balancing at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Resiliency against Traffic Oversaturation at iHeartRadio
- Introduction to Modern Network Load Balancing and Proxying
- Load Balancing with Eureka at Netflix
- Edge Load Balancing at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Resiliency against Traffic Oversaturation at iHeartRadio
- Introduction to Modern Network Load Balancing and Proxying
- Load Balancing with Eureka at Netflix
- Edge Load Balancing at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Resiliency against Traffic Oversaturation at iHeartRadio
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Introduction to Modern Network Load Balancing and Proxying
- Load Balancing with Eureka at Netflix
- Edge Load Balancing at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Designing a Microservices Architecture for Failure
- Introduction to Modern Network Load Balancing and Proxying
- Edge Load Balancing at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Load Balancing with Eureka at Netflix
- Edge Load Balancing at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Introduction to Modern Network Load Balancing and Proxying
- Edge Load Balancing at Netflix
- Scryer: Predictive Auto Scaling Engine at Netflix
- Resiliency against Traffic Oversaturation at iHeartRadio
- Introduction to Modern Network Load Balancing and Proxying
- Edge Load Balancing at Netflix
- Scryer: Predictive Auto Scaling Engine at Netflix
- Resiliency against Traffic Oversaturation at iHeartRadio
- Introduction to Modern Network Load Balancing and Proxying
- Load Balancing with Eureka at Netflix
- Edge Load Balancing at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Introduction to Modern Network Load Balancing and Proxying
- Load Balancing with Eureka at Netflix
- Edge Load Balancing at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Edge Load Balancing at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Scryer: Predictive Auto Scaling Engine at Netflix
- Resiliency against Traffic Oversaturation at iHeartRadio
- Introduction to Modern Network Load Balancing and Proxying
- Edge Load Balancing at Netflix
- Scryer: Predictive Auto Scaling Engine at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Load Balancing with Eureka at Netflix
- Edge Load Balancing at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Introduction to Modern Network Load Balancing and Proxying
- Edge Load Balancing at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Load Balancing with Eureka at Netflix
- Edge Load Balancing at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Introduction to Modern Network Load Balancing and Proxying
- Scryer: Predictive Auto Scaling Engine at Netflix
- Edge Load Balancing at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Scryer: Predictive Auto Scaling Engine at Netflix
- Scryer: Predictive Auto Scaling Engine at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Edge Load Balancing at Netflix
- Scryer: Predictive Auto Scaling Engine at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Edge Load Balancing at Netflix
- Scryer: Predictive Auto Scaling Engine at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Scryer: Predictive Auto Scaling Engine at Netflix
- Edge Load Balancing at Netflix
- Edge Load Balancing at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Scryer: Predictive Auto Scaling Engine at Netflix
- Load Balancing with Eureka at Netflix
- Zuul 2: Cloud Gateway at Netflix
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Scryer: Predictive Auto Scaling Engine at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Edge Load Balancing at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Edge Load Balancing at Netflix
- Scryer: Predictive Auto Scaling Engine at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Edge Load Balancing at Netflix
- Scryer: Predictive Auto Scaling Engine at Netflix
- Introduction to Modern Network Load Balancing and Proxying
- Scryer: Predictive Auto Scaling Engine at Netflix
- Load Balancing with Eureka at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Resiliency against Traffic Oversaturation at iHeartRadio
- High-availability SaaS Infrastructure at FreeAgent
- Introduction to Modern Network Load Balancing and Proxying
- Edge Load Balancing at Netflix
- Rate Limiting for Scaling to Millions of Domains at Cloudfare
- Scryer: Predictive Auto Scaling Engine at Netflix
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
- Load Balancing with Eureka at Netflix
- Zuul 2: Cloud Gateway at Netflix
- Load Balancing with Eureka at Netflix
- Zuul 2: Cloud Gateway at Netflix
- UDP Load Balancing at 500 pixel
- Scryer: Predictive Auto Scaling Engine at Netflix
- Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
-
Stability
- Circuit Breaker
- Circuit Breakers for Distributed Services at LINE
- Applying Circuit Breaker to Channel Gateway at LINE
- Improved Production Stability with Circuit Breakers at Heroku
- Circuit Breakers at Zendesk
- Circuit Breakers at Traveloka
- Timeouts
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Enforce Timeout: A Reliability Methodology at DoorDash
- Troubleshooting a Connection Timeout Issue with tcp_tw_recycle Enabled at eBay
- Crash-safe Replication for MySQL at Booking.com
- Bulkheads: Partition and Tolerate Failure in One Part
- Throttling: Maintain a Steady Pace
- Multi-Clustering: Improving Resiliency and Stability of a Large-scale Monolithic API Service at LinkedIn
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Circuit Breakers at Zendesk
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
- Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
-
Performance
- Performance Optimization on OS, Storage, Database, Network
- Improving Performance with Background Data Prefetching at Instagram
- Compression Techniques to Solve Network I/O Bottlenecks at eBay
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Live Downsizing Google Cloud Persistent Disks (PD-SSD) at Mixpanel
- Decreasing RAM Usage by 40% Using jemalloc with Python & Celery at Zapier
- Server Side Rendering at Wix
- 30x Performance Improvements on MySQLStreamer at Yelp
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Performance Tracking Dashboard for Live Games at Zynga
- Optimizing CAL Report Hadoop MapReduce Jobs at eBay
- Performance Tuning on Quartz Scheduler at eBay
- Diagnosing Networking Issues in the Linux Kernel at Mixpanel
- Pagelets Parallelize Server-side Processing at Yelp
- Ad Delivery Network Performance Optimization with Flame Graphs at MindGeek
- Predictive CPU isolation of containers at Netflix
- Performance Optimization by Tuning Garbage Collection
- Garbage Collection in Java Applications at LinkedIn
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Garbage Collection in Go Application at Twitch
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Performance Impact of Removing Out of Band Garbage Collector (OOBGC) at Github
- Optimizing JVM at Alibaba
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Adaptive Video Streaming at YouTube
- Reducing Video Loading Time at Dailymotion
- Boosting Site Speed Using Brotli Compression at LinkedIn
- Improving Homepage Performance at Zillow
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Predictive CPU isolation of containers at Netflix
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Predictive CPU isolation of containers at Netflix
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Improving GIF Performance at Pinterest
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- The Process of Optimizing for Client Performance at Expedia
- Predictive CPU isolation of containers at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Predictive CPU isolation of containers at Netflix
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Predictive CPU isolation of containers at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Improving key expiration in Redis at Twitter
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Predictive CPU isolation of containers at Netflix
- Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
- Linux Performance Analysis in 60.000 Milliseconds at Netflix
- Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix
- Predictive CPU isolation of containers at Netflix
-
Architecture
- Systems We Make
- Tech Stack (2 parts) at Uber
- Tech Stack at Medium
- Services (2 parts) at Airbnb
- Architecture of Evernote
- Architecture of League of Legends Client Update
- Back-end at LinkedIn
- Back-end at Flickr
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Real-time Presence Platform at LinkedIn
- Settings Platform at LinkedIn
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Seagull: Distributed System that Helps Running > 20 Million Tests Per Day at Yelp
- Architecture of Play API Service at Netflix
- Architecture of Sticker Services at LINE
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Architectures of Finance and Banking Systems
- Bank Backend at Monzo
- Trading Platform for Scale at Wealthsimple
- Tech Stack at Addepar
- Avoiding Double Payments in a Distributed Payments System at Airbnb
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Media Database at Netflix
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Cloud Infrastructure at Grubhub
- Infrastructure (3 parts) at Zendesk
- Kabootar: Communication Platform at Swiggy
- Games Platform at The New York Times
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Cloud Infrastructure at Grubhub
- Infrastructure (3 parts) at Zendesk
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Cloud Infrastructure at Grubhub
- Infrastructure (3 parts) at Zendesk
- Stack Overflow Enterprise at Palantir
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- API Specification Workflow at WeWork
- Media Database at Netflix
- Games Platform at The New York Times
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Simone: Distributed Simulation Service at Netflix
- Kabootar: Communication Platform at Swiggy
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Stack Overflow Enterprise at Palantir
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- API Specification Workflow at WeWork
- Media Database at Netflix
- Infrastructure (3 parts) at Zendesk
- Tech Stack at Medium
- Cloud Infrastructure at Grubhub
- Simone: Distributed Simulation Service at Netflix
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Simone: Distributed Simulation Service at Netflix
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Stack Overflow Enterprise at Palantir
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- API Specification Workflow at WeWork
- Media Database at Netflix
- Media Database at Netflix
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Games Platform at The New York Times
- Cloud Infrastructure at Grubhub
- Media Database at Netflix
- Games Platform at The New York Times
- Cloud Infrastructure at Grubhub
- Media Database at Netflix
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Tech Stack at Medium
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Games Platform at The New York Times
- Cloud Infrastructure at Grubhub
- Media Database at Netflix
- API Specification Workflow at WeWork
- Games Platform at The New York Times
- Tech Stack at Medium
- Kabootar: Communication Platform at Swiggy
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- Media Database at Netflix
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- Tech Stack at Medium
- API Specification Workflow at WeWork
- Media Database at Netflix
- Tech Stack at Medium
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Kabootar: Communication Platform at Swiggy
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Media Database at Netflix
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Media Database at Netflix
- Tech Stack at Shopify
- Infrastructure (3 parts) at Zendesk
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Simone: Distributed Simulation Service at Netflix
- Stack Overflow Enterprise at Palantir
- API Specification Workflow at WeWork
- Media Database at Netflix
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Media Database at Netflix
- Cloud Infrastructure at Grubhub
- Games Platform at The New York Times
- Media Database at Netflix
-
Talk
- Distributed Systems in One Lesson - Tim Berglund, Senior Director of Developer Experience at Confluent
- Building Real Time Infrastructure at Facebook - Jeff Barber and Shie Erlich, Software Engineer at Facebook
- Building Reliable Social Infrastructure for Google - Marc Alvidrez, Senior Manager at Google
- Building a Distributed Build System at Google Scale - Aysylu Greenberg, SDE at Google
- Site Reliability Engineering at Dropbox - Tammy Butow, Site Reliability Engineering Manager at Dropbox
- How Google Does Planet-Scale for Planet-Scale Infra - Melissa Binde, SRE Director for Google Cloud Platform
- Netflix Guide to Microservices - Josh Evans, Director of Operations Engineering at Netflix
- Achieving Rapid Response Times in Large Online Services - Jeff Dean, Google Senior Fellow
- Architecture to Handle 80K RPS Celebrity Sales at Shopify - Simon Eskildsen, Engineering Lead at Shopify
- Lessons of Scale at Facebook - Bobby Johnson, Director of Engineering at Facebook
- How GIPHY Delivers a GIF to 300 Millions Users - Alex Hoang and Nima Khoshini, Services Engineers at GIPHY
- High Performance Packet Processing Platform at Alibaba - Haiyong Wang, Senior Director at Alibaba
- Solving Large-scale Data Center and Cloud Interconnection Problems - Ihab Tarazi, CTO at Equinix
- Scaling Dropbox - Kevin Modzelewski, Back-end Engineer at Dropbox
- Scaling Reliability at Dropbox - Sat Kriya Khalsa, SRE at Dropbox
- Scaling with Performance at Facebook - Bill Jia, VP of Infrastructure at Facebook
- Scaling Live Videos to a Billion Users at Facebook - Sachin Kulkarni, Director of Engineering at Facebook
- Scaling Infrastructure at Instagram - Lisa Guo, Instagram Engineering
- Scaling Infrastructure at Twitter - Yao Yue, Staff Software Engineer at Twitter
- Scaling Infrastructure at Etsy - Bethany Macri, Engineering Manager at Etsy
- Scaling Real-time Infrastructure at Alibaba for Global Shopping Holiday - Xiaowei Jiang, Senior Director at Alibaba
- Scaling Data Infrastructure at Spotify - Matti (Lepistö) Pehrs, Spotify
- Scaling Pinterest - Marty Weiner, Pinterest’s founding engineer
- Scaling Backend at Youtube - Sugu Sougoumarane, SDE at Youtube
- Scaling Backend at Uber - Matt Ranney, Chief Systems Architect at Uber
- Scaling Global CDN at Netflix - Dave Temkin, Director of Global Networks at Netflix
- Scaling Load Balancing Infra to Support 1.3 Billion Users at Facebook - Patrick Shuff, Production Engineer at Facebook
- Scaling (a NSFW site) to 200 Million Views A Day And Beyond - Eric Pickup, Lead Platform Developer at MindGeek
- Scaling Git at Microsoft - Saeed Noursalehi, Principal Program Manager at Microsoft
- Scaling Multitenant Architecture Across Multiple Data Centres at Shopify - Weingarten, Engineering Lead at Shopify
- Netflix Guide to Microservices - Josh Evans, Director of Operations Engineering at Netflix
- High Performance Packet Processing Platform at Alibaba - Haiyong Wang, Senior Director at Alibaba
- Scaling Pinterest - Marty Weiner, Pinterest’s founding engineer
- Scaling Backend at Youtube - Sugu Sougoumarane, SDE at Youtube
-
Book
- Distributed Systems for Fun and Profit (Online - Free)
- What Every Developer Should Know About SQL Performance (Online - Free)
- Beyond the Twelve-Factor App - Exploring the DNA of Highly Scalable, Resilient Cloud Applications (Free)
- Chaos Engineering - Building Confidence in System Behavior through Experiments (Free)
- Designing Data-Intensive Applications
- Web Scalability for Startup Engineers
-
Donation