presto-gateway VS cartography

https://www.youtube.com/watch?v=-5mlZGjt6H4

All use the Lyft "Presto but really Trino"-Gateway project to run different clusters to handle various workloads. They go into various details for how this is achieved.

https://github.com/lyft/presto-gateway

Regarding the Trino/Presto split. I recommend looking at this blog to better understand why these two communities aren't mergeing. TL;DR Presto is a Facebook-driven project that mainly considers running on the Facebook infrastructure. Trino is community-driven which is why you see a higher velocity there.

https://trino.io/blog/2022/08/02/leaving-facebook-meta-best-...

Cartography (Python application) will get you part of the way there, in that it will discover the state of the environment, record node information and relationships in a graph database, and can be easily extended. You can also then easily write queries about the relationships of various resources to answer questions like “what can I reach from VPC X”. Drawing diagrams though is very hard to do well without extra input.

Build an asset inventory of the cloud environment. (using an OSS project called cartography)

The project is still early, so we’d love your feedback! We’ve based our cloud asset inventory on another great OSS project called cartography. So far, we’ve added misconfiguration checks and common identity-based attack paths. Up next on our roadmap are network/access graph visualizations, vulnerability scanning, and secret scanning!

The first step involved in threat modelling is to build an architecture diagram of the system you are protecting. This also involves building a list of assets in the system. You cannot protect something which you don’t have visibility over. We can use tools such as CloudMapper from the previous step for building an architecture diagram of an AWS cloud environment. There are similar tools for threat modeling for other cloud service providers like Cartography.

Lyft made a tool called Cartography, which scrapes your AWS Account(s) and inserts representations of many of your cloud resources into a Neo4j (graph) database. This makes it easy to query and discover how things are connected in your account.

Recently, we at Cloudanix made open source contributions to the Cartography project by Lyft. We contributed to the pre-existing AWS module by adding support for KMS and API gateway. Since the Cartography project did not have support for Microsoft Azure, we started from scratch to add that capability to Cartography. We added support for Azure services like CosmosDB, SQL, Storage, and Virtual Machines.

[2] https://github.com/lyft/cartography