argo
act
argo | act | |
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43 | 146 | |
14,314 | 50,324 | |
0.9% | 1.8% | |
9.8 | 9.2 | |
2 days ago | 2 days ago | |
Go | Go | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
argo
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StackStorm – IFTTT for Ops
Like Argo Workflows?
https://github.com/argoproj/argo-workflows
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Creators of Argo CD Release New OSS Project Kargo for Next Gen Gitops
Dagger looks more comparable to Argo Workflows: https://argoproj.github.io/argo-workflows/ That's the first of the Argo projects, which can run multi-step workflows within containers on Kubernetes.
For what it's worth, my colleagues and I have had great luck with Argo Workflows and wrote up a blog post about some of its advantages a few years ago: https://www.interline.io/blog/scaling-openstreetmap-data-wor...
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Practical Tips for Refactoring Release CI using GitHub Actions
Despite other alternatives like Circle CI, Travis CI, GitLab CI or even self-hosted options using open-source projects like Tekton or Argo Workflow, the reason for choosing GitHub Actions was straightforward: GitHub Actions, in conjunction with the GitHub ecosystem, offers a user-friendly experience and access to a rich software marketplace.
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(Not) to Write a Pipeline
author seems to be describing the kind of patterns you might make with https://argoproj.github.io/argo-workflows/ . or see for example https://github.com/couler-proj/couler , which is an sdk for describing tasks that may be submitted to different workflow engines on the backend.
it's a little confusing to me that the author seems to object to "pipelines" and then equate them with messaging-queues. for me at least, "pipeline" vs "workflow-engine" vs "scheduler" are all basically synonyms in this context. those things may or may not be implemented with a message-queue for persistence, but the persistence layer itself is usually below the level of abstraction that $current_problem is really concerned with. like the author says, eventually you have to track state/timestamps/logs, but you get that from the beginning if you start with a workflow engine.
i agree with author that message-queues should not be a knee-jerk response to most problems because the LoE for edge-cases/observability/monitoring is huge. (maybe reach for a queue only if you may actually overwhelm whatever the "scheduler" can handle.) but don't build the scheduler from scratch either.. use argowf, kubeflow, or a more opinionated framework like airflow, mlflow, databricks, aws lamda or step-functions. all/any of these should have config or api that's robust enough to express rate-limit/retry stuff. almost any of these choices has better observability out-of-the-box than you can easily get from a queue. but most importantly.. they provide idioms for handling failure that data-science folks and junior devs can work with. the right way to structure code is just much more clear and things like structuring messages/events, subclassing workers, repeating/retrying tasks, is just harder to mess up.
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what technologies are people using for job scheduling in/with k8s?
Argo Workflows + Argo Events
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What are some good self-hosted CI/CD tools where pipeline steps run in docker containers?
Drone, or Tekton, Argo Workflows if you’re on k8s
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job scheduling for scientific computing on k8s?
Check out Argo Workflows.
- Orchestration poll
- What's the best way to inject a yaml file into an Argo workflow step?
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Which build system do you use?
go-git has a lot of bugs and is not actively maintained. The bug even affects Argo Workflow, which caused our data pipeline to fail unexpectedly (reference: https://github.com/argoproj/argo-workflows/issues/10091)
act
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Create a Custom GitHub Action in Rust
To speed up your development cycle, install and use the act tool to test-run your action directly in your development environment. This tool lets you invoke a GitHub workflow right on your local machine and will save you the round-trips of pushing each change to GitHub to see if it works.
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How to debug GitHub actions. Real-world example
When it comes to the alternatives to tmate, there is another great debugging tool that you could check out. It is called act and it allows you to run GitHub Actions code on your local machine making debugging even easier. It has its own limitations and some learning curve but overall it is another tool you should use if you can’t fix the CI bugs by connecting directly into the running action with the tmate.
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Using my new Raspberry Pi to run an existing GitHub Action
Link: https://github.com/nektos/act
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Show HN: Open-source x64 and Arm GitHub runners. Reduces GitHub Actions bill 10x
Could you upload your build of GitHub's runner image to Docker Hub?
This would be quite useful for users of other GitHub Actions clones like act [0].
[0]: https://github.com/nektos/act
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Git commit messages are useless
> These kinds of commit messages are typically an indicator of a broken process where somebody needs to commit to see something happen, like a deployment or build process, and aren't able to assert that stuff works locally.
This is one of my biggest pet peeves with services like github actions. Something running locally like "act" [1] isn't sufficient because it doesn't have everything github has and is extra friction anyway to get everyone to use it for testing.
[1] https://github.com/nektos/act
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Essential Command Line Tools for Developers
View on GitHub
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What’s with DevOps engineers using `make` of all things?
If you use Github actions, act is incredibly useful. It can be used to test your GH actions, but also serves as an interface for running tasks locally.
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Streamlining CI/CD Pipelines with Code: A Developer's Guide
That's something that often is difficult or basically impossible. Except for maybe GitHub actions through Act (https://github.com/nektos/act). I'd still lean to something in the yaml sphere if it eventually would be used in deployment pipelines and such. For example a solution incorporating ansible.
It also seems to me that the argument you make is mostly focused on the building step? Earthly certainly seems focused on that aspect.
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GitHub Actions Are a Problem
I feel I'm being trolled, but I'll bite and accept the resulting downvotes
I don't think treating every mention of act as an opportunity for airing of personal grievances is helpful in a discussion when there's already ample reports of people's concrete issues with it, had one looked at the 800 issues in its repo https://github.com/nektos/act/issues?q=is%3Aissue or the 239 from gitea's for https://gitea.com/gitea/act_runner/issues or whatever is going on with Forgejo's fork https://code.forgejo.org/forgejo/act .
But, as for me specifically, there are two and a half answers: I wanted to run VSCodium's build locally, which act for sure puked about. Then, while trying to troubleshoot that, I thought I'd try something simpler and have it run the lint job from act's own repo <https://github.com/nektos/act/blob/1252e551b8672b1e16dc8835d...> to rule out "you're holding it wrong" type junk. It died with
[checks/lint] Failure - Main actions/setup-go@v3
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How Steve Jobs Saved Apple with the Online Apple Store
https://twitter.com/mitsuhiko/status/1720410479141487099 :
> GitHub Actions currently charges $0.16 per minute* for the macOS M1 Runners. That comes out to $84,096 for 1 machine year*
GitHub Runner is written in Go; it fetches tasks from GitHub Actions and posts the results back to the Pull Request that spawned the build.
nektos/act is how Gitea Actions builds GitHub Actions workflow YAML build definition documents. https://github.com/nektos/act
https://twitter.com/MatthewCroughan/status/17200423527675700... :
> This is the macOS Ventura installer running in 30 VMs, in 30 #nix derivations at once. It gets the installer from Apple, automates the installation using Tesseract OCR and TCL Expect scripts. This is to test the repeatability. A single function call `makeDarwinImage`.
With a Multi-Stage Dockerfile/Containerfild, you can have a dev environment like xcode or gcc+make in the first stage that builds the package, and then the second stage the package is installed and tested, and then the package is signed and published to a package repo / app store / OCI container image repository.
SLSA now specifies builders for signing things correctly in CI builds with keys in RAM on the build workers.
"Build your own SLSA 3+ provenance builder on GitHub Actions" https://slsa.dev/blog/2023/08/bring-your-own-builder-github
What are some alternatives?
temporal - Temporal service
reverse-rdp-windows-github-actions - Reverse Remote Desktop into Windows on GitHub Actions for Debugging and/or Job Introspection [GET https://api.github.com/repos/nelsonjchen/reverse-rdp-windows-github-actions: 403 - Repository access blocked]
keda - KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes
cache - Cache dependencies and build outputs in GitHub Actions
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
dagger - Application Delivery as Code that Runs Anywhere
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
earthly - Super simple build framework with fast, repeatable builds and an instantly familiar syntax – like Dockerfile and Makefile had a baby.
StackStorm - StackStorm (aka "IFTTT for Ops") is event-driven automation for auto-remediation, incident responses, troubleshooting, deployments, and more for DevOps and SREs. Includes rules engine, workflow, 160 integration packs with 6000+ actions (see https://exchange.stackstorm.org) and ChatOps. Installer at https://docs.stackstorm.com/install/index.html
action-tmate - Debug your GitHub Actions via SSH by using tmate to get access to the runner system itself.
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
LSPatch - LSPatch: A non-root Xposed framework extending from LSPosed