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https://github.com/replicatedhq/troubleshoot.git
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77 lines
2.8 KiB
Markdown
77 lines
2.8 KiB
Markdown
# Contributing to Troubleshoot
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Thank you for your interest in Troubleshoot, we welcome your participation. There are a number of ways to participate in Troubleshoot as outlined below:
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# Community
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For discussions about developing Troubleshoot, there's an [#app-troubleshoot channel in Kubernetes Slack](https://kubernetes.slack.com/channels/app-troubleshoot).
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## Issues
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- [Request a New Feature](https://github.com/replicatedhq/troubleshoot/issues/new?assignees=&labels=feature&template=feature_enhancement.md) Create an issue to add functionality that addresses a problem or adds an enhancement.
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- [Report a Bug](https://github.com/replicatedhq/troubleshoot/issues/new?assignees=&labels=bug&template=bug_report.md) Report a problem or unexpected behaviour with Troubleshoot.
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## Design Principles
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When implementing a new feature please review the [design principles](./docs/design/design-principles.md) to help guide the approach.
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## Development Environment
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To get started we recommend:
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1. Go (v1.24 or later)
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2. For cluster-based collectors, you will need access to a Kubernetes cluster
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3. Fork and clone repo
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4. Run `make clean build` to generate binaries
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5. You can now run `./bin/preflight` and/or `./bin/support-bundle` to use the code you've been writing
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> Note: to cross-compile a Linux binary from MacOS:
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> `GOOS=linux GOARCH=amd64 make clean build`
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### Testing
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To run the tests locally run the following:
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```bash
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make test
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make test RUN=TestClusterResources_Merge
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```
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Additionally, e2e tests can be run with:
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```bash
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make support-bundle preflight e2e-test
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```
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A running Kubernetes cluster as well as `jq` are required to run e2e tests.
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### Profiling
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You are able to collect CPU & memory runtime properties and store the data for analysis in a file. To do so, pass in the file paths using `--cpuprofile` and `--memprofile` flags in the CLI. Once you have your data collected, you can analyse it using [pprof visualization tool](https://github.com/google/pprof/blob/main/doc/README.md). Here is how
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Run support bundle and with CPU & memory profile flags
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```sh
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./bin/support-bundle examples/support-bundle/sample-supportbundle.yaml --cpuprofile=cpu.prof --memprofile=mem.prof
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```
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Visualize using [pprof](https://github.com/google/pprof/blob/main/doc/README.md)
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```sh
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go tool pprof -http=":8000" cpu.prof
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go tool pprof -http=":8001" mem.prof
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```
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**Additional flags for memory profiling**
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- `inuse_space`: Amount of memory allocated and not released yet (default).
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- `inuse_objects`: Amount of objects allocated and not released yet.
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- `alloc_space`: Total amount of memory allocated (regardless of released).
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- `alloc_objects`: Total amount of objects allocated (regardless of released).
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More on profiling please visit https://go.dev/doc/diagnostics#profiling
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## Contribution workflow
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We'd love to talk before you dig into a a large feature.
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