openebs
bodywork
Our great sponsors
openebs | bodywork | |
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7 | 8 | |
8,632 | 430 | |
1.2% | - | |
6.9 | 0.0 | |
8 days ago | 8 months ago | |
Python | ||
Apache License 2.0 | GNU Affero General Public License v3.0 |
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.
openebs
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What's the coolest thing you have (or do) in your homelab?
I run local-path-provisioner, openEBS (jiva) and minio on top of local-path storage.
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Kubernetes size definitions: What's the difference of "Gi" and "G"?
volumeClaimTemplates: - metadata: name: mongo-persistent-storage spec: resources: requests: storage: 5G here in detail: https://github.com/openebs/openebs/blob/master/k8s/demo/mongodb/mongo-statefulset.yml
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Why OpenEBS 3.0 for Kubernetes and Storage?
We are grateful for the support and contributions of the vibrant open-source community that OpenEBS has received. We are also thankful to the Cloud Native Computing Foundation (CNCF) for including OpenEBS as one of its storage projects. And a special thanks to the CNCF for being a reference user of OpenEBS as well - you can read about their experience and that of others including TikTok / ByteDance and Verizon / Yahoo on Adopters.md. Collectively, these aspects have helped my team to notice challenges and opportunities and of course to resolve bugs and improve the polish of OpenEBS with each release.
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Provisioning High-Performance Storage for NoSQL databases with OpenEBS
Many organizations and users have adopted OpenEBS to deploy and provision storage for their stateful workloads, including those who use NoSQL. Some of the following are reasons to adopt OpenEBS for NoSQL databases include:
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Container Attached Storage (CAS) vs. Software-Defined Storage - Which One to Choose?
OpenEBS, a popular CAS based storage solution, has helped several enterprises run stateful workloads. Originally developed by MayaData, OpenEBS is now a CNCF project with a vibrant community of organizations and individuals alike. This was also evident from CNCF’s 2020 Survey Report that highlighted MayaData (OpenEBS) in the top-5 list of most popular storage solutions. To know more on how OpenEBS can help your organization run stateful workloads, contact us here.
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Deploying Percona Kubernetes Operators using OpenEBS Local Storage
OpenEBS has become a popular choice for provisioning local persistent volumes (local PVs) for resilient applications. Users of OpenEBS for Local PV include reference users such as ByteDance (maker of TikTok), Flipkart (one of the world’s largest eCommerce providers), and thousands of others including many that have shared their experiences in the Adopters.md at the OpenEBS community.
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Deploy Elasticsearch on Kubernetes Using OpenEBS LocalPV
Many users have shared their experience of using OpenEBS for local storage management in Kubernetes for Elasticsearch, including the Cloud Native Computing Foundation, ByteDance (TikTok), and Zeta Associates (Lockheed Martin) on the Adopters list in the OpenEBS community available here.
bodywork
- Deployment automation for ML projects of all shapes and sizes
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A tutorial on how to handle prediction uncertainty in production systems, by using Bayesian inference and probabilistic programs
how to deploy it to Kuberentes using Bodywork.
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[P] [D] How are you approaching prediction uncertainty in ML systems?
I usually turn to generative models - e.g. probabilistic programs and Bayesian inference. I’ve written-up my thoughts on how to engineer these into a ‘production system’ deployed to Kubernetes, using PyMC and Bodywork (an open-source ML deployment tool that I contribute to).
- Bodywork: MLOps tool for deploying ML projects to Kubernetes
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Tool for mapping executable Python modules to Kubernetes deployments
I’m one of the core contributors to Bodywork, an open-source tool for deploying machine learning projects developed in Python, to Kubernetes.
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[P] [D] The benefits of training the simplest model you can think of and deploying it to production, as soon as you can.
I’ve had many successes with this approach. With this in mind, I’ve put together an example of how to make this Agile approach to developing machine learning systems a reality, by demonstrating that it takes under 15 minutes to deploy a Scikit-Learn model, using FastAPI with Bodywork (an open-source MLOps tool that I have built).
- bodywork - MLOps for Python and K8S
- bodywork-ml/bodywork-core - MLOps automation for Python and Kubernetes
What are some alternatives?
dynamic-nfs-provisioner - Operator for dynamically provisioning an NFS server on any Kubernetes Persistent Volume. Also creates an NFS volume on the dynamically provisioned server for enabling Kubernetes RWX volumes.
NuPIC - Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.
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.
gensim - Topic Modelling for Humans
devspace - DevSpace - The Fastest Developer Tool for Kubernetes ⚡ Automate your deployment workflow with DevSpace and develop software directly inside Kubernetes.
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
cstor-operators - Collection of OpenEBS cStor Data Engine Operators
Crab - Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (numpy, scipy, matplotlib).
ThreatMapper - Open source cloud native security observability platform. Linux, K8s, AWS Fargate and more.
TFLearn - Deep learning library featuring a higher-level API for TensorFlow.
faas-netes - Serverless Functions For Kubernetes
PyBrain