argo
pipeline
argo | pipeline | |
---|---|---|
43 | 51 | |
14,314 | 8,285 | |
0.7% | 0.3% | |
9.8 | 9.7 | |
1 day ago | 7 days ago | |
Go | Go | |
Apache License 2.0 | Apache License 2.0 |
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)
pipeline
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14 DevOps and SRE Tools for 2024: Your Ultimate Guide to Stay Ahead
Tekton
- GitHub Actions could be so much better
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Distributed Traces for Testing with Tekton Pipelines and Tracetest
Tekton is an open-source framework for creating efficient CI/CD systems. This empowers developers to seamlessly construct, test, and deploy applications across various cloud environments and on-premise setups.
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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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Wolfi: A community Linux OS designed for the container and cloud-native era
[2]: https://github.com/tektoncd/pipeline/issues/5507#issuecommen...
- Nu stiu ce sa fac, orice sfat e bine venit
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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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Is Jenkins still the king?
If you want a step up, I would recommend trying out Tekton Pipelines. It’s a very popular ci tool, and it runs on Kubernetes. Yes, this would involve setting up a Kubernetes cluster but please don’t run for the hills! You can setup a Kubernetes cluster and install Tekton on top of it with minimal setup using minikube (see here. This would be a great joint exercise as it will give you a bit of Kubernetes understanding alongside it, and the mechanisms of Tekton are a little trickier than GitHub actions imo. It’s all much the same though.
- Is there a way to run a one-off pod that would work as a command line tool?
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K8s powered Git push deployments
I've recently found this quote by Kelsey Hightower:
"I'm convinced the majority of people managing infrastructure just want a PaaS. The only requirement: it has to be built by them."
Source: https://twitter.com/kelseyhightower/status/85193508753294540...
In the last few weeks, I've experimented a bit with Flux (https://fluxcd.io/), Tekton (https://tekton.dev/) and Cloud Native Buildpacks (https://buildpacks.io/) on how to provide K8s powered git push deployments without using a dedicated CI/CD server.
My project is still in early alpha stage and just a proof of concept :-) My vision is to expand it into an Open Source PaaS in the future.
Do you think the above quote is true? What does an open source PaaS need to be like in order to be accepted by software developers?
Some other projects have been discontinued in the past (like Flynn or Deis) or were created before the Kubernetes era.
Is it the right direction to provide a Heroku like solution based on K8s or is it better to provide an Open Source Infrastructure as Code library with building blocks to avoid everything from scratch?
What are some alternatives?
temporal - Temporal service
dagger - Application Delivery as Code that Runs Anywhere
keda - KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes
argo-cd - Declarative Continuous Deployment for Kubernetes
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
kubevela - The Modern Application Platform.
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
tekton-argocd-poc - This a PoC using Tekton (for CI) and ArgoCD (CD). It uses a local k8s cluster (K3D)
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
NUKE - 🏗 The AKEless Build System for C#/.NET
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
skaffold - Easy and Repeatable Kubernetes Development