kube-batch
Docker Compose
kube-batch | Docker Compose | |
---|---|---|
3 | 388 | |
1,057 | 32,367 | |
- | 0.7% | |
4.0 | 9.6 | |
12 months ago | 8 days ago | |
Go | Go | |
Apache License 2.0 | Apache License 2.0 |
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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.
kube-batch
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Volcano vs Yunikorn vs Knative
tldr; Knative Batch Job provider should support the respective coscheduling and kube-batch support. We had developed an in-house one for KubeFlow, from scratch. We had added Apache Arrow support into knative-serving with the respective CloudEvents interop layer, natively (i.e. secure shmem via IPC namespace, instead of message passing on the same host). We use it as a direct replacement for Apache Arrow Ballista, and had planned researching further DataFusion compat layer. Almost any modern ETL is pretty dubious without Apache Arrow.
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Kubernetes Was Never Designed for Batch Jobs
Another aspect of batch jobs is that we’ll often want to run distributed computations where we split our data into chunks and run a function on each chunk. One popular option is to run Spark, which is built for exactly this use case, on top of Kubernetes. And there are other options for additional software to make running distributed computations on Kubernetes easier.
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Scaling Kubernetes to 7,500 Nodes
> That said, strain on the kube-scheduler is spiky. A new job may consist of many hundreds of pods all being created at once, then return to a relatively low rate of churn.
Last I checked, the default scheduler places Pods one at a time. It might be advantageous to use a gang/batch scheduler like kube-batch[0], Poseidon[1] or DCM[2].
[0] https://github.com/kubernetes-sigs/kube-batch
[1] https://github.com/kubernetes-sigs/poseidon
[2] https://github.com/vmware/declarative-cluster-management
Docker Compose
- Docker Compose: `version` is obsolete
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12 Factor: 13 years later
Solutions are many, and could include Docker Compose, VS Code dev containers, Telepresence, Localstack or setting up temporary AWS accounts as a development environment for serverless applications.
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Let's write a simple microservice in Clojure
Using Docker Compose to run Postgres and any third-party services locally provides a streamlined and consistent development environment. Developers can define services in a docker-compose.yml file, which enables them to configure and launch an entire stack with a single command. In this case, Postgres is encapsulated within a container with predefined configurations. Docker Compose also facilitates easy scaling, updates, and isolation of services, enhancing development efficiency and reducing the setup time for new team members or transitioning between projects. It encapsulates complex configurations, such as Postgres' performance monitoring and logging settings, in a manageable, version-controlled file, simplifying and replicating the service setup across different environments.
- Live reload em Go com docker e compile daemon
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Docker compose, orchestrating and automating services
“Compose simplifies the control of your entire application stack, making it easy to manage services, networks, and volumes in a single, comprehensible YAML configuration file. Then, with a single command, you create and start all the services from your configuration file.” - Docker documentation
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Hosting a simple docker-compose app with Nginx and generate a SSL with certbot on digitalocean droplet
curl -fsSL https://get.docker.com -o get-docker.sh sudo sh get-docker.sh # Install docker compose sudo curl -L "https://github.com/docker/compose/releases/download/1.29.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose # Apply executable permissions to the binary sudo chmod +x /usr/local/bin/docker-compose # Run Project docker-compose up -d
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One Minute: Compose
Docker,
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How to Set Up a Docker Container
This foundation now opens the door to even more powerful concepts. You can explore more advanced concepts such as container networking, streamlining the management of complex applications with Docker Compose, and how to make your application data persistent using volumes.
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Use same Dockerfile for Dev & Production
In many projects that are containerized, especially in cases where development is also done locally with docker-compose, teams often have two Dockerfiles, 1 for Development, the other for Production. If you happen to have multiple environments like pre-prod, staging and so on, some teams could have different Dockerfiles for these environments.
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How to Dockerise a NodeJS - TypeScript API || A Comprehensive Guide from Environment Setup to Deployment with a CI/CD Pipeline
sudo curl -L "https://github.com/docker/compose/releases/latest/download/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
What are some alternatives?
volcano - A Cloud Native Batch System (Project under CNCF)
supervisor - Supervisor process control system for Unix (supervisord)
argo - Workflow Engine for Kubernetes
LibreNMS-docker - LibreNMS Docker image
mpi-operator - Kubernetes Operator for MPI-based applications (distributed training, HPC, etc.)
terraform - Terraform enables you to safely and predictably create, change, and improve infrastructure. It is a source-available tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned.
kube-scheduler-simulator - The simulator for the Kubernetes scheduler
Portainer - Making Docker and Kubernetes management easy.
sidekick - High Performance HTTP Sidecar Load Balancer
Cloud-Init - unofficial mirror of Ubuntu's cloud-init
sarus - OCI-compatible engine to deploy Linux containers on HPC environments.
k3s - Lightweight Kubernetes