aws-shell VS jmespath.py

While at it - I heartily recommend you to install aws-shell which boosts your aws cli productivity by providing graphical autocompletion, hints and shortcuts as shown in the image below. I only discovered it recently myself and it's definitely a game changer!

AWS-shell is super handy for learning the CLI.

aws-shell will improve your life :) https://github.com/awslabs/aws-shell

With aws-shell you're able to quickly run commands against any AWS API from your local terminal with great auto-completion. I use it very regularly and it reduces the need to jump to the documentation. You can find it on Github but can also install it easily via your favorite package manager like homebrew.

If so the region config is explained here: https://github.com/awslabs/aws-shell#configuration

The Azure CLI lets us write queries to filter the results of the az storage blob list command. The queries are written in JMESPath, which is a query language for JSON. In this case, we are filtering the results to only include blobs that end with the .bacpac extension and then selecting the first one as ordered by the lastModified property. If there are no blobs found, the script exits with a failure code. If we find a blob, we download it to the local path specified by the localPath variable.

For JSON there is the `jmespath` library which might help.

https://github.com/jmespath/jmespath.py

I love jq, but I also use JMESPath (especially with AWS CLI), yq (bundled with tomlq and xq as well), and dasel [2]. I also wish hclq [3] wasn't so dead!

[0]: https://jmespath.org/

Probably writing the query side of things is a lot of the fun here, but there is actually a spec (and a complying Rust impl) you can hook into for this JQ-like querying: https://jmespath.org/ ( https://github.com/jmespath/jmespath.rs ).

Thanks to custom variables that use labels, we can create various filters for the dashboard. You can look up my configuration of variables and extend it with an analogy way for your own needs. At the top, I marked the filter with detected pods in selected namespace. In the lower part, you can see a preview of all labels that are associated with a single log line. Most labels are meta information that Promtail adds during scraping targets. This part of the Promtail configuration provides it. In this section, I also marked a few labels that not comes out-of-the box e.g. leavel , class , thread . We added these labels using the Promtail json stage. You need to know that Promtail processes scraped logs in a pipeline. A pipeline is comprised of a set of stages. json stage is a parsing stage that reads the log line as JSON and accepts JMESPath expressions to extract data.

The tester on the official website for JMESPath (what json_query is doing) has been useful to me: https://jmespath.org/

Interesting. How does this compared to Jmespath? Not saying Jmespath is superior, just wondering whether you were aware of it.