kapp
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kapp | grenade | |
---|---|---|
7 | 5 | |
859 | 1,440 | |
1.5% | - | |
8.1 | 5.6 | |
8 days ago | 5 months ago | |
Go | Haskell | |
Apache License 2.0 | BSD 2-clause "Simplified" License |
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kapp
- HELM vs KUSTOMIZE
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How to handle the lifecycle of multiple COTS
If you want to take it one step further: you might be applying several resources at a time that are logically one "application". kapp (https://carvel.dev/kapp/) lets you group those together and give them a name, and provides a "terraform-like" experience where it shows you its execution plan before applying updates. So then you might do `ytt -f | kapp deploy -a name-of-thing` Or you could use helm's templating engine but then still pass the resulting yaml to kapp for its unification of the deployment step.
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Dhall: A Gateway Drug to Haskell
since you mentioned Kubernetes...
> It would be nice if there was a separate state reconciliation system that one could adapt to use with Cue or Dhall or any other frontend
this exactly was thinking behind https://carvel.dev/kapp for Kubernetes (i'm one of the maintainers). it makes a point to not know how you decided to generate your Kubernetes config -- just takes it as input.
> In particular the ability to import other files as semantic hashes seems like a great feature.
it's an interesting feature but seems like it should be unnecessary given that config can be easily checked into git (your own and its dependencies).
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Terraform should have remained stateless
i think kubernetes is not a great example in favor of more client state (like tf) since k8s has uniform resource structure (metadata.*) and first class labeling support. but as you point out kubectl doesnt use labels well (at least imho).
when building https://carvel.dev/kapp (which i think of as "optimized terraform" for k8s) the goal was absolutely to take advantage of those k8s features. we ended up providing two capabilities: direct label (more advanced) and "app name" (more user friendly). from impl standpoint, difference is how much state is maintained.
"kapp deploy -a label:x=y -f ..." allows user to specify label that is applied to all deployed resources and is also used for querying k8s to determine whats out there under given label. invocation is completely stateless since burden of keeping/providing state (in this case the label x=y) is shifted to the user. downside of course is that all apis within k8s need to be iterated over. (side note, fun features like "kapp delete -a label:!x" are free thanks to k8s querying).
"kapp deploy -a my-app -f ..." gives user ability to associate name with uniquely auto-generated label. this case is more stateful than previous but again only label needs to be saved (we use ConfigMap to store that label). if this state is lost, one has to only recover generated label.
imho k8s api structure enables focused tools like kapp to be much much simpler than more generic tool like terraform. as much as i'd like for terraform to keep less state, i totally appreciate its needs to support lowest common denominator feature set.
common discussion topics:
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Is there any CLI tool to sync between local yamls and current cluster namespace state?
Take a look at kapp (https://github.com/vmware-tanzu/carvel-kapp).
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Deploy Neo4J's APOC plugin with code thanks to CARVEL vendir
kapp - Install, upgrade, and delete multiple Kubernetes resources as one "application"
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Open Application Model – An open standard for defining cloud native apps
I really like this approach for simplifying Kubernetes. A few projects similar to OAM in that it provides a higher level "Application" CRD:
https://github.com/vmware-tanzu/carvel-kapp
grenade
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Haskell deep learning tutorials [Blog]
Grenade is fun, but it does not support CUDA, so it will limit you. I would say that this was a great experiment that has influenced the Hasktorch library in different ways (let me know if I am wrong).
- Dhall: A Gateway Drug to Haskell
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Haskell for Artificial Intelligence?
FWIW there's an interesting library called grenade which offers nice types for constructing neural nets. I haven't used it, and this is not my areas of expertise, but it looks cool!
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Rank 3 Stencils for "Efficient Parallel Stencil Convolution in Haskell" (Repa)
When I wrote grenade I used the im2col trick to turn convolutions into a single matrix multiplication, which could then be done in hmatrix.
- What are some ways I could tickle my (beginner) haskell-brain with something *useful*?
What are some alternatives?
kubevela - The Modern Application Platform.
hasktorch - Tensors and neural networks in Haskell
argo-cd - Declarative Continuous Deployment for Kubernetes
liblinear-enumerator - Haskell bindings to liblinear
Flux - Successor: https://github.com/fluxcd/flux2
simple-neural-networks - Simple parallel neural networks implementation in pure Haskell
kapp-controller - Continuous delivery and package management for Kubernetes.
CV - Haskell wrappers and utilities for OpenCV machine vision library
ytt - YAML templating tool that works on YAML structure instead of text
nn - A tiny neural network 🧠
carvel - Carvel provides a set of reliable, single-purpose, composable tools that aid in your application building, configuration, and deployment to Kubernetes. This repo contains information regarding the Carvel open-source community.
hnn - haskell neural network library