Argo: Open source Kubernetes native workflows, events, CI and CD | Hacker News Reader

Argo: Open source Kubernetes native workflows, events, CI and CD

argoproj.github.io

133 pointsjcamou19 comments

We're using Argo as a replacement for our GoCD based continuous delivery system and it's been fantastic. We were about to move onto Concourse and realized we would need to set up the and manage the equivalent of a Kubernetes cluster just to support it. We took a few extra weeks to prototype Argo first and were glad we did.

In our use case, the primary deployment model is blue/green deploys of VM based microservices on AWS with a bunch of Terraform managed infrastructure gluing them together. The newer class of service we're developing right now is container based and has even more infrastructure complexity. Teams manage their own service releases and each group has slight variations in their deploy steps. We need a deploy system that can support the old and new style and remain flexible while providing a migration path.

Teams love the flexibility and expressiveness of the workflow definitions. They've begun to move cron jobs onto it as well. Argo is much more lightweight and easy to operate than any other system we had worked with because it leans so heavily on Kubernetes primitives that we already needed to understand. The codebase is also relatively easy to understand, so we've been able to contribute things back to the project while working through the migration.

We've taken a cue from the project and begun to consolidate our control plane on CRDs so they can seamlessly integrate with Argo. CRD Operators + Argo are allowing us to consolidate all of the custom deploy/config tooling we built over the years onto a common system that is testable and well integrated.

It's a little early in the project to measure the full effect, but the internal project has a lot of momentum.

The idea is nice, but if security is one of your concerns, you'll probably not want to run this if the docs are even close to representative of the actual application:

> 3. Configure the service account to run workflows

> For clusters with RBAC enabled, the 'default' service account is too limited to support features like artifacts, outputs, access to secrets, etc... Run the following command to grant admin privileges to the 'default' service account in the namespace 'default'

This raises so many red flags. Never give admin rights 'as a default'.

While I agree with your position that admin rights should not be the default, that doesn't seem to be what Argo is actually doing.

The text snippet you've included is from the quick start/demo page, which seems to be targeted at getting the examples running quickly so that a potential user can see what it is capable of. Other issues for this in a production setup would be the use of the 'default' role/namespace at all. In this use case (running the examples in a new cluster), giving the default user full access is the quickest way to this result.

Clearly it would be better if Argo included a more precise (permission wise) role by default, but from my understanding Argo does not require cluster admin permissions in order to function.

The parent post did quality it appropriately with "if the docs are even close to representative of the actual application".

I hope the docs are not representative, but the parent post is right that it's a bad sign. At least put up a warning sign that it's insecure and only suitable for demo purposes to do that.

Thanks. We've updated the docs to outline the bare minimum set of privileges.

And right below that it says:

>NOTE: You can also submit workflows which run with a different service account using:

>argo submit --serviceaccount <name>

To which there is further documentation as to the exact permissions you need. While I only spent about 30 seconds searching, this gets you 90% of the way there from what I can tell on my phone.

https://github.com/argoproj/argo/issues/725

I work on Argo. Those instructions are mainly for demo purposes because many of the examples need admin privileges. The amount of access which is needed, is really dependent on what your workflow is doing (e.g. if your workflow needs to deploy a resource, then you need to give the service account 'create' privileges on that resource). Currently, the bare minimum for a workflow to function is outlined here:

https://github.com/argoproj/argo/issues/983#issuecomment-435...

I will make sure that the docs are updated, so that this information is well understood.

Docs have been updated and linked to in the getting started guide: https://github.com/argoproj/argo/blob/master/docs/workflow-r...

We've had much success with Argo workflows over the past months. Among other projects, we use it to generate city-sized extracts of mapping data from the OpenStreetMap planet. Blog post at https://www.interline.io/blog/scaling-openstreetmap-data-wor...

Using Argo on Google Kubernetes Engine makes it easy to auto-scale for our workflow steps that parallelize. We're also able to reuse Dockerfiles and resources between both our batch workflows and our running services (also on Kubernetes).

What does this project simplify?

It seems to be equivalently complex to the process it would have you replace.

I always explain that Workflows should be thought of as a fancier version of Kubernetes Jobs. Some of the killer features, IMO, are with artifact management and control flow (e.g. loops, conditionals, parallelism).

So far, our most common use case has been in the machine learning space. One of the biggest problems it can solve is the ability to leverage a Kubernetes cluster as an auto-scaling compute grid for all forms batch processing. We've been working closely with ML teams at various companies, both large and small, and many of our features were implemented to address the ML use cases (e.g. DAG support, loops/step expansion, step aggregation).

With that said, Argo got its start trying to address the CI use case, so we also feel like we handle that one pretty well.

The workflow controller has always been intended to be a lego block to enable higher level applications to be built on top of it.

FYI, Google's new Kubeflow Pipelines service uses Argo.

https://cloud.google.com/blog/products/ai-machine-learning/i...

https://github.com/kubeflow/pipelines#acknowledgments

Is there easy way to build containers ?

I see many resources for running stuff with already built container but could not any simple how to do it. Currently just mounting docker host and building on it.

Dockerfiles?

Edit: I misunderstood the parents question.

Instead of using docker host you might run docker daemon in sidecar container.

Here is a sample argo workflow which uses this technique:

https://github.com/argoproj/argo/blob/master/examples/sideca...

Very very small suggestion: its not very expensive to register a domain and have it redirect to the github pages; might make it appear somewhat more polished.

Thank you. We didn't submit the post, but we actually have https://argoproj.io which redirects to the argoproj.github.io page. Actually we've been meaning to take advantage of GitHub's custom domain so we can drop the github.io entirely.

"that's like yout opinion, man"

registering vanity domains is a shure way to make this information harder to find in a few years

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