swagger-editor VS mimir

It has an online editor. You can easily play around with it and generate easy-to-use documentation.

After running the collection, I can see the API spec that was created and the mock server endpoint to test it. Looking at the rendered version on Swagger's OAS editor we can see pretty clearly this is a complete API that gets us exactly what we need.

While there’s not an officially supported Java SDK for Marqeta, building a Java client is quite straightforward, as the Core API is documented in both Swagger v2.0 and OpenAPI v3.0. The OpenAPI documentation is in beta, but it is generated directly from the API source code. To get a Java client, all we need to do is drop the OpenAPI yaml file into editor.swagger.io, modify the servers section to use the https://sandbox-api.marqeta.com/v3 as the URL, and tell it to generate a Java client.

Check out https://editor.swagger.io/ as a start point. In theory you should be able to generate a client for any swagger complient api and plug in your own auth and custom logic.

I would suggest using the swagger editor: https://editor.swagger.io/

Paste your json into https://editor.swagger.io and it will ask you if you want to convert it to yaml

Sure. You can use the editor from here for instance to define your endpoints and the data received and returned. By looking at the preloaded example you can figure out most of what you need to know about openapi. But if you need more info, the official documentation is pretty good.

Optional: If you make any changes to the plugin instructions or metadata models, you can also copy the contents of main.py into the main main.py file. This will allow you to access the openapi.json at http://0.0.0.0:8000/sub/openapi.json when you run the app locally. You can convert from JSON to YAML format with Swagger Editor. Alternatively, you can replace the openapi.yaml file with an openapi.json file.

I created another issue, this time quoting directly from swagger.io, showing screenshots from editor.swagger.io validation to prove that the library is creating invalid OpenAPI descriptions and that my suggestion creates valid ones, rephrasing the entire problem from a slightly different angle. I asked that if he decides to close the issue, to please not delete it so that it serves as documentation for others.

It consists of 6 separate components to run, plus 4 additional optional components [1]. And I don't even count 5 additional caches [2]. How is that "simple and easy"?

[1] https://grafana.com/docs/mimir/latest/references/architectur...

[2] https://github.com/grafana/mimir/blob/9a52522a05f25d6d6bc2e8...

Yes, but also no. The Prometheus ecosystem already has two FOSS time-series databases that are complementary to Prometheus itself. Thanos and Mimir. Not to mention M3db, developed at Uber, and Cortex, then ancestor of Mimir. There's a bunch of others I won't mention as it would take too long.

I used the one in their tutorial.

Grafana Agent can collect and stream data via Prometheus remote write protocol. Then you can either use Prometheus or Mimir. to receive the data at a central location. It depends on how many millions of series you need to collect.

Long term storage all depends on your needs and sophistication. I use Thanos for our system since it has an extremely flexible scaling system. But there is also Grafana Mimir. They're both similar in that they use Prometheus TSDB format as part of the underlying storage. One nice Thanos advantage is that it does do downsampling in addition to being able to store raw metric data for a long time. It will auto-select downsampled data to make requests faster.

Grafana Mimir - scalable storage for Prometheus

Depending on how you want to set things up, you can use Thanos or Mimir to create the single-pane-of-glass view of your data.