JaCoCo VS zipkin

I will use here JaCoCo, where also the JaCoCo-Maven-lugin exists for the usage in your Maven builds. This article will show how to configure the code coverage to finally get the results for unit- and integration-tests.

In protection rules, I added build workflow in Require status checks to pass before merging. This is to ensure that before merging code in master branch, build should run successfully. I also added Jacoco Code Coverage to make sure that enough unit tests are available in project and Detekt to make sure that code in project is readable. I added them in build configuration. Even if one of them gives error, build will fail. Whenever, someone push code in pull request, build action will run and check if build is running successfully or not.

Code coverage analysis tools quantify the amount of tested code, serving as a valuable tool to inform on code structure and testing related decisions. We will make use of JaCoCo, JaCoCo produces reports on multiple kinds of code coverage metrics including instructions, line and branch coverage.

One specific example where I regularly use a profile in this way is for configuring code coverage. In all of my Java projects, I use JaCoCo for generating code coverage reports. I use JaCoCo during the Maven test phase. However, while developing I find it useful at times to exclude coverage reporting to reduce the build time. But in my CI/CD workflows in GitHub Actions, I activate the code coverage profile during pull-requests and pushes to the default branch. For pull-requests, my GitHub Actions workflow comments the code coverage on the PR and uploads the coverage report as a workflow artifact, where I can inspect it as necessary. And during a push to the default branch, my workflow updates coverage badges to keep them up to date with the current state of the default branch. I can also activate the code coverage profile locally while developing, such as prior to submitting a pull-request, to ensure that I didn't miss testing something.

In Unit tests, individual software code components are checked if it is working as expected or not. Unit tests isolate a function or module of code and verify its correctness. We can use tools like JaCoCo for Java and Mocha, and Jasmine for NodeJS to generate unit test reports. We can also send these reports to SonarQube which shows us code coverage and the percentage of your code covered by your test cases.

And there is the original jacoco/jacoco: (0.8.7: released this on May 5, 2021), but it's for Java. I'm not sure if we can use it with multiple flavors on Android.

Make sure to also update to Jacoco 0.8.7 to avoid test issues: https://github.com/jacoco/jacoco/releases/tag/v0.8.7

When choosing distributed tracing tools, considerations include your technology stack, business requirements, and monitoring complexity. Zipkin, SkyWalking, and OpenTelemetry are popular distributed tracing solutions, each with its unique features.

From the perspective of the realization of GraphQL infrastructure, the interesting direction is "Finding". How to find the problem? How to find the bottleneck of the system? Distributed Tracing System (DTS) will help answer this question. Distributed tracing is a method of observing requests as they propagate through distributed environments. In our scenario, we have dozens of subgraphs, gateway, and transport layer through which the request goes. We have several tools that can be used to detect the whole lifecycle of the request through the system, e.g. Jaeger, Zipkin or solutions that provided DTS as a part of the solution NewRelic.

Zipkin is a distributed tracing system used for tracking and analyzing how requests move through complex systems, especially in setups with many interconnected services, known as microservices.

Distributed Tracing: Middleware for distributed tracing like Jaeger and Zipkin helps monitor and trace requests as they flow through multiple microservices, aiding in debugging, performance optimization, and understanding the system's behavior.

For microservice tracing, you might want to look at Zipkin [0], or OpenTelemetry [1]

[0] https://zipkin.io/

I’ve not used a self-hosted solution before, but here’s one I found. https://zipkin.io/

> IMO the reason these vendors can and do charge so much is not because telemetry software is hard.

I always saw it as "they are charging for their polished UI/experience"

The UI of https://zipkin.io/ versus DataDog is kind of... not really in the same ballpark?

There are the zipkin https://zipkin.io/ and jaeger https://www.jaegertracing.io/ packages/components you can use both have quickstarts if you consider that to be a beginner's guide.

Zipkin, which was developed by Twitter, is an open source tool for distributed tracing that can also be used to troubleshoot latency issues in your application. While Zipkin is Java-based, py_zipkin is an implementation for Python.