https://github.com/marco-lancini/cartography-queries

Utilities for programmatic analysis of Cartography data.
https://github.com/marco-lancini/cartography-queries

aws cartography docker elasticsearch gcp jupyter kubernetes

Last synced: 4 months ago
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Utilities for programmatic analysis of Cartography data.

• Host: GitHub
• URL: https://github.com/marco-lancini/cartography-queries
• Owner: marco-lancini
• License: apache-2.0
• Created: 2020-01-15T08:28:36.000Z (about 5 years ago)
• Default Branch: main
• Last Pushed: 2023-05-01T18:57:12.000Z (almost 2 years ago)
• Last Synced: 2024-10-14T07:42:37.689Z (4 months ago)
• Topics: aws, cartography, docker, elasticsearch, gcp, jupyter, kubernetes
• Language: Jupyter Notebook
• Homepage: https://blog.marcolancini.it/continuous-cloud-visibility/
• Size: 512 KB
• Stars: 32
• Watchers: 5
• Forks: 8
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE
  • Codeowners: CODEOWNERS

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README

        
# Cartography Queries

This is the companion repo for the "[Continuous Visibility into Ephemeral Cloud Environments](https://www.marcolancini.it/continuous-cloud-visibility/)" series.

## Custom Queries

The file `queries/queries.json` contains a set of custom queries specifically created for analysing data collected by Cartography, and is structured as a list of dictionaries, where each dictionary represents an annotated query (enriched with metadata).

## Consumers

### Elasticsearch

The [consumers/elasticsearch](consumers/elasticsearch/) folder contains all the code needed to get you started with integrating Elasticsearch with Cartography data.

For more information, please refer to the [README.md](consumers/elasticsearch/README.md) file in that folder, and the "[Tracking Moving Clouds: How to continuously track cloud assets with Cartography](https://www.marcolancini.it/2020/blog-tracking-moving-clouds-with-cartography)" blog post.

### Jupyter Notebooks

The [consumers/jupyter_notebooks](consumers/jupyter_notebooks/) folder contains all the code needed to get you started with your own Jupyter reports for analysing Cartography data.

For more information, please refer to the [README.md](consumers/jupyter_notebooks/README.md) file in that folder, and the "[Repeatability: Jupyter Notebooks](https://www.marcolancini.it/2020/blog-mapping-moving-clouds-with-cartography/#repeatability-jupyter-notebooks)" section of the "[Mapping Moving Clouds: how to stay on top of your ephemeral environments with Cartography](https://www.marcolancini.it/2020/blog-mapping-moving-clouds-with-cartography)" blog post.

## Deployment on Kubernetes

I've now described an automated process to get Neo4J and Cartography up and running in a Kubernetes cluster at: [Automating Cartography Deployments on Kubernetes](https://www.marcolancini.it/2021/blog-cartography-on-kubernetes/).

## References

* **[CODE]** [Cartography's source code](https://github.com/lyft/cartography)

* **[CODE]** [Cartography Deployment on Kubernetes](https://github.com/marco-lancini/k8s-lab-plz/tree/master/components/cartography)

* **[CODE]** [Terraform AWS Security Reviewer](https://github.com/marco-lancini/utils/tree/main/terraform/aws-security-reviewer)

* **[BLOG]** [Mapping Moving Clouds: How to stay on top of your ephemeral environments with Cartography](https://www.marcolancini.it/2020/blog-mapping-moving-clouds-with-cartography/)

* **[BLOG]** [Tracking Moving Clouds: How to continuously track cloud assets with Cartography](https://www.marcolancini.it/2020/blog-tracking-moving-clouds-with-cartography/)

* **[BLOG]** [Automating Cartography Deployments on Kubernetes](https://www.marcolancini.it/2021/blog-cartography-on-kubernetes/)

* **[BLOG]** [Cross Account Auditing in AWS and GCP](https://www.marcolancini.it/2019/blog-cross-account-auditing/)

* **[BLOG]** [Kubernetes Lab on Baremetal](https://www.marcolancini.it/2021/blog-kubernetes-lab-baremetal/)

* **[TALK]** [Cartography: using graphs to improve and scale security decision-making](https://speakerdeck.com/marcolancini/cartography-using-graphs-to-improve-and-scale-security-decision-making)