zfs-localpv
Airflow
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zfs-localpv | Airflow | |
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12 | 169 | |
366 | 34,397 | |
5.2% | 2.1% | |
7.1 | 10.0 | |
5 days ago | 5 days ago | |
Go | Python | |
Apache License 2.0 | Apache License 2.0 |
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zfs-localpv
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ZFS 2.2.0 (RC): Block Cloning merged
I use it in Kubernetes via https://github.com/openebs/zfs-localpv
The PersistentVolume API is a nice way to divvy up a shared resource across different teams, and using ZFS for that gives us the snapshotting, deduplication, and compression for free. For our workloads, it benchmarked faster than XFS so it was a no-brainer.
- openebs/zfs-localpv: CSI Driver for dynamic provisioning of Persistent Local Volumes for Kubernetes using ZFS.
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OpenEBS on MicroK8S on Hetzner
Last few months I experimented more and more with all OpenEBS solutions that fit small Kubernetes cluster, using MicroK8S and Hetzner Cloud for a real experience.
- Openebs ?? Or equivalent
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Network Storage on On-Prem Barebones Machine
I would investigate https://openebs.io/ https://portworx.com/ https://longhorn.io/ if you are forced to you can mount ISCSI on the kublet and feed it to one of those solutions. Keep in mind most of the big guys buy some sort of managed solution that you can point a CSI like trident https://netapp-trident.readthedocs.io
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Ask HN: What are some fun projects to run on a home K8s cluster?
What are some cool projects to self hosted on a home Raspberry Pi (64 bit) Kubernetes cluster (Helm charts). arm64 support is a must. A lot of projects only build amd64 Docker containers which don't run on my cluster.
I currently run:
- obenebs (provides abstraction for using local k8s worker disks as PVC mounts when running on-prem) -- https://openebs.io/
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Finally got around to doing that Ceph on ZFS experiment
I didn't set anything actually -- I need to look into whether OpenEBS ZFS LocalPV can facilitate passing ZVOL options (I don't think it can just yet). The only tuning I did on the storage class was the usual ZFS-level options.
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My self-hosting infrastructure, fully automated
What do you use to provision Kubernetes persistent volumes on bare metal? I’m looking at open-ebs (https://openebs.io/).
Also, when you bump the image tag in a git commit for a given helm chart, how does that get deployed? Is it automatic, or do you manually run helm upgrade commands?
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Jinja2 not formatting my text correctly. Any advice?
ListItem( 'Kubernetes', 'https://kubernetes.io/', 'Container Engines and Orchestration', """Kubernetes is an open-source container-orchestration system for automating computer application deployment, scaling, and management.""" ), ListItem( 'Podman', 'https://podman.io/', 'Container Engines and Orchestration', """Podman is a daemonless, open source, Linux native tool designed to make it easy to find, run, build, share and deploy applications using Open Containers Initiative (OCI) Containers and Container Images.""" ), # Data Storage :: Block Storage ListItem( 'Amazon EBS', 'https://aws.amazon.com/ebs/', 'Data Storage :: Block Storage', """Amazon Elastic Block Store (Amazon EBS) is an easy-to-use, scalable, high-performance block-storage service designed for Amazon Elastic Compute Cloud (Amazon EC2).""" ), ListItem( 'OpenEBS', 'https://openebs.io/', 'Data Storage :: Block Storage', """OpenESB is a Java-based open-source enterprise service bus. It allows you to integrate legacy systems, external and internal partners and new development in your Business Process.""" ), # Data Storage :: Cluster Storage ListItem( 'Ceph', 'https://ceph.io/en/', 'Data Storage :: Cluster Storage', """Ceph is an open-source software storage platform, implements object storage on a single distributed computer cluster, and provides 3-in-1 interfaces for object-, block- and file-level storage.""" ), ListItem( 'Hadoop Distributed File System', 'https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html', 'Data Storage :: Cluster Storage', """The Hadoop Distributed File System ( HDFS ) is a distributed file system designed to run on commodity hardware.""" ), # Data Storage :: Object Storage ListItem( 'Amazon S3', 'https://aws.amazon.com/s3/', 'Data Storage :: Object Storage', """Amazon S3 or Amazon Simple Storage Service is a service offered by Amazon Web Services that provides scalable object storage through a web service interface.""" )
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Building a "complete" cluster locally
Ideas from my kubernetes experience: * Cert-Manager is very popular and almost a must-have if you terminate SSL inside the cluster * Backups using velero * A dashboard/UI is actually very helpful to quickly browse resources, client tools like k9s are fine too * Secret: Management: Bitnami Sealed Secrets is the second big project in that space * I would add Loki to aggregate Logs * Never heard of ory. Usually I see (dex)[https://dexidp.io/] or keycloak used for Authentication * I like to run OpenEBS as in-cluster storage. * Istio isn't compatible with the upcomming ServiceMeshInterface (i think), so the trend seem to go toward Linkerd * Some Operator to deploy your favorite Database, is also a nice learning exercise.
Airflow
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Building in Public: Leveraging Tublian's AI Copilot for My Open Source Contributions
Contributing to Apache Airflow's open-source project immersed me in collaborative coding. Experienced maintainers rigorously reviewed my contributions, providing constructive feedback. This ongoing dialogue refined the codebase and honed my understanding of best practices.
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Navigating Week Two: Insights and Experiences from My Tublian Internship Journey
In week Two, I contributed to the Apache Airflow repository.
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Airflow VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Best ETL Tools And Why To Choose
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.
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Simplifying Data Transformation in Redshift: An Approach with DBT and Airflow
Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring.
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Share Your favorite python related software!
AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic!
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Ask HN: What is the correct way to deal with pipelines?
I agree there are many options in this space. Two others to consider:
- https://airflow.apache.org/
- https://github.com/spotify/luigi
There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file showing up in a directory…
- "Você veio protestar para ter acesso ao código fonte da urnas. O que é o código fonte?" "Não sei" 🤡
- Cómo construir tu propia data platform. From zero to hero.
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Is it impossible to contribute to open source as a data engineer?
You can try and contribute some new connectors/operators for workflow managers like Airflow or Airbyte
What are some alternatives?
longhorn - Cloud-Native distributed storage built on and for Kubernetes
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
democratic-csi - csi storage for container orchestration systems
dagster - An orchestration platform for the development, production, and observation of data assets.
lvm-localpv - Dynamically provision Stateful Persistent Node-Local Volumes & Filesystems for Kubernetes that is integrated with a backend LVM2 data storage stack.
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
k3s - Lightweight Kubernetes
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
Mayastor - Dynamically provision Stateful Persistent Replicated Cluster-wide Fabric Volumes & Filesystems for Kubernetes that is provisioned from an optimized NVME SPDK backend data storage stack.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
rook - Storage Orchestration for Kubernetes
Dask - Parallel computing with task scheduling