nextflow
argo
nextflow | argo | |
---|---|---|
9 | 43 | |
2,538 | 14,314 | |
0.9% | 0.7% | |
9.7 | 9.8 | |
7 days ago | about 9 hours ago | |
Groovy | 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.
nextflow
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Nextflow: Data-Driven Computational Pipelines
> It's been a while since you can rerun/resume Nextflow pipelines
Yes, you can resume, but you need your whole upstream DAG to be present. Snakemake can rerun a job when only the dependencies of that job are present, which allows to neatly manage the disk usage, or archive an intermediate state of a project and rerun things from there.
> and yes, you can have dry runs in Nextflow
You have stubs, which really isn't the same thing.
> I have no idea what you're referring to with the 'arbitrary limit of 1000 parallel jobs' though
I was referring to this issue: https://github.com/nextflow-io/nextflow/issues/1871. Except, the discussion doesn't give the issue a full justice. Nextflow spans each job in a separate thread, and when it tries to span 1000+ condor jobs it die with a cryptic error message. The option of -Dnxf.pool.type=sync and -Dnxf.pool.maxThreads=N prevents the ability to resume and attempts to rerun the pipeline.
> As for deleting temporary files, there are features that allow you to do a few things related to that, and other features being implemented.
There are some hacks for this - but nothing I would feel safe to integrate into a production tool. They are implementing something - you're right - and it's been the case for several years now, so we'll see.
Snakemake has all that out of the box.
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Alternatives to nextflow?
For now, I think that the best place to track this / get your voice heard is this GitHub Discussions post (which covers many things - error reporting is one of them). https://github.com/nextflow-io/nextflow/discussions/3107
- HyperQueue: ergonomic HPC task executor written in Rust
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Nextflow vs Snakemake
We could spend the day pointing to things we wish were different, but that doesn't change the fact that Nextflow is the leader when it comes to workflow orchestration. And feel free to create a new issue in the GitHub repository if you wish to request a feature :)
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Feel very hard writing nextflow pipeline.
The nextflow devs have been talking about this for a while on GitHub. Looks like they're implementing something along these lines using schema like they do for nf-core. GitHub discussion.
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Need a statically typed Python replacement
Groovy definitely scales up just fine I think but I never used it myself outside of little snippets embedded in my DSL, I know its considered by some to be "dead" so its interesting to see what other JVM-ecosystem users think of it.
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)
What are some alternatives?
galaxy - Data intensive science for everyone.
temporal - Temporal service
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
keda - KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes
singularity - Singularity has been renamed to Apptainer as part of us moving the project to the Linux Foundation. This repo has been persisted as a snapshot right before the changes.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
devops-resources - DevOps resources - Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP
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
Hubitat-iPhone-Presence-Sensor - A virtual presence sensor for Hubitat that checks if an iPhone/Android is on the WiFi network.
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.