lakeFS
helm-operator
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| lakeFS | helm-operator | |
|---|---|---|
| 48 | 5 | |
| 4,053 | 657 | |
| 2.2% | - | |
| 9.8 | 6.4 | |
| 7 days ago | over 1 year 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.
lakeFS
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A Step-by-Step Guide to Implementing Data Version Control
# Download the LakeFS binary wget https://github.com/treeverse/lakeFS/releases/latest/download/lakefs # Make the binary executable chmod +x lakefs # Initialize LakeFS with S3 as the storage backend ./lakefs init --backend s3 --s3-gateway-endpoint --s3-region --s3-force-path-style --s3-access-key --s3-secret-key
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Jujutsu: A Git-compatible DVCS that is both simple and powerful
Might want to look at purpose built tools for that such as lakeFS (https://github.com/treeverse/lakeFS/)
* Disclaimer: I'm one of the creators/maintainers of the project.
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Data diffs: Algorithms for explaining what changed in a dataset (2022)
Might want to checkout lakeFS: https://github.com/treeverse/lakeFS
(full disclosure: I'm one of the creators)
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Transactions in Spark / Delta lake?
Take a look at https://github.com/treeverse/lakeFS -
- LakeFS – Version Control for Big Data
- DuckDB <3 LakeFS
- We built an open-source project (3.1K stars on GitHub) for data version control
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How are you incrementally testing your data pipelines as you develop them?
I mean if you're ready to adopt a new framework into your ecosystem this is one of the major usecases for LakeFS.
- Git-for-Data
- LakeFS: Git-like versioning for object stores
helm-operator
- Question for declarative GitOps managed shops
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Auto helm (software) installations in ci/cd pipeline
You can store the values file of the helm in your repository and deploy with CI, but I personally prefer going to GitOps and Helm Operator (https://github.com/fluxcd/helm-operator) Or you can have a mixed approach where you define your HelmRelease to be deployed for HelmOperator and deploy it with CI (instead of having an operator in the cluster to apply every change in the repo)
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Kubernetes State Checker
Nothing prevents you from making an operator that creates Deployment/Services/Ingress for you.
This is even simplified with Helm (to template your resources) and the HelmOperator[1].
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How do you automate Helm charts installation?
I think you should check out flux and flux helm operator. https://github.com/fluxcd/helm-operator/stargazers
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Gopher Gold #14 - Wed Oct 07 2020
fluxcd/helm-operator (Go): The Flux Helm Operator, for declarative Helming
What are some alternatives?
dvc - 🦉 ML Experiments and Data Management with Git
kubebuilder - Kubebuilder - SDK for building Kubernetes APIs using CRDs
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
helmfile - Deploy Kubernetes Helm Charts
git-lfs - Git extension for versioning large files
Flux - Successor: https://github.com/fluxcd/flux2
Ory Kratos - Next-gen identity server replacing your Auth0, Okta, Firebase with hardened security and PassKeys, SMS, OIDC, Social Sign In, MFA, FIDO, TOTP and OTP, WebAuthn, passwordless and much more. Golang, headless, API-first. Available as a worry-free SaaS with the fairest pricing on the market!
spark-operator - Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.
MLflow - Open source platform for the machine learning lifecycle
duf - Disk Usage/Free Utility - a better 'df' alternative
tofu-controller - A GitOps OpenTofu and Terraform controller for Flux