https://github.com/sergeyt/pandora

Small box of pandora to prototype your app with ready for use backend. This is just my compilation of different solutions occasionally applied in hackathons and challenges
https://github.com/sergeyt/pandora

baas caddy celery dgraph docker-compose elasticsearch golang kibana minio nats python quick-start rabbitmq redis template-project tika

Last synced: about 1 month ago
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Small box of pandora to prototype your app with ready for use backend. This is just my compilation of different solutions occasionally applied in hackathons and challenges

• Host: GitHub
• URL: https://github.com/sergeyt/pandora
• Owner: sergeyt
• License: apache-2.0
• Created: 2018-09-24T15:44:49.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2024-08-06T10:18:44.000Z (3 months ago)
• Last Synced: 2024-09-22T14:02:16.669Z (about 2 months ago)
• Topics: baas, caddy, celery, dgraph, docker-compose, elasticsearch, golang, kibana, minio, nats, python, quick-start, rabbitmq, redis, template-project, tika
• Language: Go
• Homepage: https://tsvbits.com/pandora/
• Size: 1.82 MB
• Stars: 26
• Watchers: 3
• Forks: 8
• Open Issues: 48
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# PANDORA

This small box of pandora (aka small app basis) composed from the following technologies:

* [Dgraph](https://dgraph.io/) as data store with GraphQL support, write operations using REST

* [Minio](https://www.minio.io/) as Amazon S3 compatible storage

* [Stow](https://github.com/graymeta/stow) allows using cloud storage provides like Amazon, Google, Azure

* [ElasticSearch](https://www.elastic.co/products/elasticsearch) as search engine. Dgraph data can be automatically replicated in ElasticSeach index

* [Kibana](https://www.elastic.co/products/kibana) to explore ElasticSearch data

* [NATS](https://nats.io/) as messaging system with streaming of push notifications (events) via [SSE](https://en.wikipedia.org/wiki/Server-sent_events) channel

* [Celery](http://www.celeryproject.org/) - distributed task queue

* [RabbitMQ](https://www.rabbitmq.com/) - fast message broker for celery tasks

* [Redis](https://redis.io/) - result backend for celery tasks and cache service

* [Apache Tika](https://tika.apache.org/) - powerful content analysis toolkit

* try [FluentD](https://www.fluentd.org/) - for centralized logging, not implemented yet :)

Programming languages currently used in the project:

* [Go](https://golang.org/)

* [Python](https://www.python.org/)

* [Kotlin](https://kotlinlang.org/)

## Basic Idea

I'd like to have simple, flexible, dynamic, declarative, reactive, realtime information system :)

## How to run

`docker-compose up` runs the following services:

1. `zero` - Dgraph cluster manager

1. `dgraph` - Dgraph data manager hosts predicates & indexes

1. `ratel` - serves the UI to run queries, mutations & altering schema

1. `nats` - plays as message bus

1. `pubsub` - event streaming service based on [SSE](https://en.wikipedia.org/wiki/Server-sent_events) protocol

1. `minio` - Amazon S3 compatible file store

1. `imageproxy` - [service](https://willnorris.com/go/imageproxy) with image manipulation ops like resizing

1. `elasticsearch` - search and analitycs engine

1. `kibana` - Elasticsearch dashboard

1. `app` - application API service

1. `caddy` - web server as service gateway