helm
volcano
Our great sponsors
helm | volcano | |
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5 | 2 | |
19,316 | 3,744 | |
- | 3.3% | |
9.2 | 9.1 | |
about 3 years ago | 4 days 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.
helm
- kubernetes helm: "lost connection to pod" and "transport is closing" errors
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How to reference a value defined in a template in a sub-chart in helm for kubernetes?
Update after some digging:According to Subcharts and Globals the templates are shared between charts.
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Eli5 What is Kubernetes, containers, etc.?
But that’s not all! As we’ve decomposed, ported, and reborn our PaaS as a Kubernetes citizen; we found a need for tools to help manage all of the ephemera that comes along with building and running Kubernetes-native applications. The result has been open sourced as Helm and we’re excited to see increasing adoption and growing excitement around the project.
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go startpack
Helm (label: good first issue) The Kubernetes Package Manager
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My Journey With Spark On Kubernetes... In Python (1/3)
In this section, you use Helm to deploy the Kubernetes Operator for Apache Spark from the incubator Chart repository. Helm is a package manager you can use to configure and deploy Kubernetes apps.
volcano
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Can we specify nodeSelector inline for a kubectl command
Also, if you are creating bare pods, this sounds like batch scheduling and you should consider using Jobs instead, to have a pod controller. And then you could also consider the https://volcano.sh/ scheduler if it has a fitting scheduling plugin for your use case.
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My Journey With Spark On Kubernetes... In Python (1/3)
For our experiments, we will use Volcano which is a batch scheduler for Kubernetes, well-suited for scheduling Spark applications pods with a better efficiency than the default kube-scheduler. The main reason is that Volcano allows "group scheduling" or "gang scheduling": while the default scheduler of Kubernetes schedules containers one by one, Volcano ensures that a gang of related containers (here, the Spark driver and its executors) can be scheduled at the same time. If for any reason it is not possible to deploy all the containers in a gang, Volcano will not schedule that gang. This article explains in more detail the reasons for using Volcano.
What are some alternatives?
snowflake - Snowflake is a network service for generating unique ID numbers at high scale with some simple guarantees.
kube-batch - A batch scheduler of kubernetes for high performance workload, e.g. AI/ML, BigData, HPC
spark-operator - Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.
chart-releaser - Hosting Helm Charts via GitHub Pages and Releases
argo - Workflow Engine for Kubernetes
k8s-platform-lcm - A faster and easier way to manage the lifecycle of applications and tools, running and living around your Kubernetes platform
singularity-cri - The Singularity implementation of the Kubernetes Container Runtime Interface
cockroach - CockroachDB - the open source, cloud-native distributed SQL database.
warewulf - Warewulf is a stateless and diskless container operating system provisioning system for large clusters of bare metal and/or virtual systems.
go-formatter - A curated list of awesome Go frameworks, libraries and software
charts - ⚠️(OBSOLETE) Curated applications for Kubernetes