spring-boot-debug-app VS jmespath.py

This is a GitHub link to my demo app. It’s simple Spring Boot web app used to debugging various stuff. There are many ways to configure JSON logging in Spring Boot. I decided to use Logback because it is easy to configure and one of the most widely used logging library in the Java Community. To enable JSON logging we need to add below dependencies.

My demo app (GitHub Link) uses Spring Boot version 3, or more precisely the latest release from 2022, i.e. 3.0.1. The core monitoring component in Spring Boot is Actuator. If you remember the migration of Spring Boot from version 1 to 2, you’ll probably remember that update brought a lot of breaking changes in Actuator. Fortunately, in the case of version 3, no such changes have been made, so you can apply the following configurations to Spring Boot version 2.x.x

apiVersion: argoproj.io/v1alpha1 kind: Application metadata: name: demo spec: destination: namespace: sandbox server: https://kubernetes.default.svc project: default source: path: infra/helm repoURL: https://github.com/luafanti/spring-boot-debug-app targetRevision: main plugin: env: - name: HELM_VALUES value: | serviceAccount: create: true image: repository: luafanti/spring-boot-debug-app tag: main pullPolicy: IfNotPresent replicaCount: 1 resources: memoryRequest: 256Mi memoryLimit: 512Mi cpuRequest: 500m cpuLimit: 1 probes: liveness: initialDelaySeconds: 15 path: /actuator/health/liveness failureThreshold: 3 successThreshold: 1 timeoutSeconds: 3 periodSeconds: 5 readiness: initialDelaySeconds: 15 path: /actuator/health/readiness failureThreshold: 3 successThreshold: 1 timeoutSeconds: 3 periodSeconds: 5 ports: http: name: http value: 8080 management: name: management value: 8081 envs: - name: VAULT_SECRET_USER value: - name: VAULT_SECRET_PASSWORD value: log: level: spring: "info" service: "info" syncPolicy: {}

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.