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add-docs
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20 changed files with 968 additions and 190 deletions
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[submodule "mkdocs-material-dib"] |
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path = mkdocs-material-dib |
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url = https://github.com/dib-lab/mkdocs-material-dib.git |
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.md-typeset h3 { font-weight: 600; } |
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.md-typeset h4 { font-weight: 600; } |
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body { |
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background-color: #FAFAFA; |
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} |
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div.body { |
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background-color: #FAFAFA; |
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} |
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# 2019-snakemake-byok8s |
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|
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[](https://travis-ci.org/charlesreid1/2019-snakemake-byok8s) |
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[](https://github.com/charlesreid1/2019-snakemake-byok8s/blob/master/LICENSE) |
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 |
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 |
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 |
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 |
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|
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# Overview |
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|
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This is an example of a Snakemake workflow that: |
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|
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- is a **command line utility** called `byok8s` |
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- is bundled as an installable **Python package** |
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- is designed to run on a **Kubernetes (k8s) cluster** |
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- can be **tested with Travis CI** (and/or locally) using [minikube](https://github.com/kubernetes/minikube) |
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|
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## What is byok8s? |
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|
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byok8s = Bring Your Own Kubernetes (cluster) |
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|
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k8s = kubernetes |
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|
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byok8s is a command line utility that launches |
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a Snakemake workflow on an existing Kubernetes |
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cluster. This allows you to do something |
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like this (also see the [Installation](installing.md) |
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and [Quickstart](quickstart.md) guides in the |
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documentation): |
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|
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``` |
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# Install byok8s |
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python setup.py build install |
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|
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# Create virtual k8s cluster |
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minikube start |
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|
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# Run the workflow on the k8s cluster |
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cd /path/to/workflow/ |
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byok8s my-workflowfile my-paramsfile --s3-bucket=my-bucket |
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|
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# Clean up the virtual k8s cluster |
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minikube stop |
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``` |
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|
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## Getting Up and Running |
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|
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See the [Quickstart Guide](quickstart.md) to get up and |
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running with byok8s. |
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|
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## How does byok8s work? |
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|
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The command line utility requires the user to provide |
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three input files: |
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|
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* A snakemake workflow, via a `Snakefile` |
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* A workflow configuration file (JSON) |
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* A workflow parameters file (JSON) |
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|
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Additionally, the user must create the following resources: |
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|
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* A kubernetes cluster up and running |
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* An S3 bucket (and AWS credentials to read/write) |
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|
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A sample Snakefile, workflow config file, and workflow |
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params file are provided in the `test/` directory. |
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|
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The workflow config file specifies which workflow targets |
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and input files to use. |
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|
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The workflow parameters file specifies which parameters to |
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use for the workflow steps. |
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|
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## Why S3 buckets? |
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|
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AWS credentials and an S3 bucket is required to run workflows because |
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of restrictions on file I/O on nodes in a kubernes cluster. The Snakemake |
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workflows use AWS S3 buckets as remote providers for the Kubernetes nodes, |
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but this can be modified to any others that Snakemake supports. |
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|
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AWS credentials are set with the two environment variables: |
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|
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``` |
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AWS_ACCESS_KEY_ID |
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AWS_SECRET_ACCESS_KEY |
||||
``` |
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|
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These are passed into the Kubernetes cluster by byok8s and Snakemake. |
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|
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## Kubernetes and Minikube |
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|
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[Kubernetes](https://kubernetes.io/) is a technology that utilizes Docker |
||||
container to orchestrate a cluster of compute nodes. These compute nodes are |
||||
usually real compute nodes requested and managed via a cloud provider, like AWS |
||||
or Google Cloud. |
||||
|
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But the compute nodes can also be virtual, which is where |
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[minikube](https://github.com/kubernetes/minikube) comes in. It creates a |
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kubernetes cluster that is entirely local and virtual, which makes testing |
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easy. See the [byok8s Minikube Guide](kubernetes_minikube.md) for details |
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about how to use minikube with byok8s. |
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|
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The Travis CI tests also utilize minikube to run test workflows. See [byok8s |
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Travis Tests](travis_tests.md) for more information. |
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|
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## Cloud Providers |
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|
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For real workflows, your options for |
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kubernetes clusters are cloud providers. |
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We have guides for the following: |
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|
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- AWS EKS (Elastic Container Service) |
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- GCP GKE (Google Kuberntes Engine) |
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- Digital Ocean Kubernetes service |
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|
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# Kubernetes + byok8s: In Practice |
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|
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| Cloud Provider | Kubernetes Service | Guide | State | |
||||
|-----------------------------|---------------------------------|-------------------------------------------------|------------| |
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| Minikube (on AWS EC2) | Minikube | [byok8s Minikube Guide](kubernetes_minikube.md) | Finished | |
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| Google Cloud Platform (GCP) | Google Container Engine (GKE) | [byok8s GCP GKE Guide](kubernetes_gcp.md) | Finished | |
||||
| Amazon Web Services (AWS) | Elastic Container Service (EKS) | [byok8s AWS EKS Guide](kubernetes_aws.md) | Unfinished | |
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| Digital Ocean (DO) | DO Kubernetes (DOK) | [byok8s DO DOK Guide](kubernetes_dok.md) | Unfinished | |
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|
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|
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# Installing byok8s |
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|
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byok8s requires two pieces of prerequisite software: |
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|
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- python (conda) |
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- virtualenv (optional) |
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|
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It also requires an AWS S3 bucket to be specified |
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(the bucket must exist and credentials to access it |
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must be provided via environment variables, see the |
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[Quickstart](quickstart.md)). |
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|
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Additionally, if you are planning to run byok8s on |
||||
a local virtual kubernetes cluster, you must install: |
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|
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- minikube |
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|
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Otherwise, if you are planning on running byok8s on |
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remote kubernetes clusters provided by cloud providers, |
||||
you must install: |
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|
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- kubernetes, ***OR*** |
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- a cloud provider command line tool (`gcloud`, `aws`) |
||||
|
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## Installing Python |
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|
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We recommend installing pyenv and using pyenv |
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to install miniconda: |
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|
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```plain |
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curl https://pyenv.run | bash |
||||
``` |
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|
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Restart your shell and install miniconda: |
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|
||||
```plain |
||||
pyenv update |
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pyenv install miniconda3-4.3.30 |
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pyenv global miniconda3-4.3.30 |
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``` |
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|
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## Installing virtualenv |
||||
|
||||
You will need the virtualenv package to |
||||
set up a virtual environment: |
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|
||||
```plain |
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pip install virtualenv |
||||
``` |
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|
||||
## Installing minikube |
||||
|
||||
This step is only required if you plan to run byok8s |
||||
kubernetes workflows locally on a virtual kubernetes |
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cluster (i.e., testing mode). |
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|
||||
Install the 64-bit Linux version of minikube, or visit the |
||||
[installing minikube](https://kubernetes.io/docs/tasks/tools/install-minikube/) |
||||
to find the right version: |
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|
||||
```plain |
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curl -LO https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64 \ |
||||
&& sudo install minikube-linux-amd64 /usr/local/bin/minikube |
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``` |
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|
||||
(On a Mac you can do `brew install minikube`.) |
||||
|
||||
If you are planning on running on a bare metal |
||||
machine, you will also need to install a hypervisor |
||||
like VirtualBox or KVM, see [installing minikube](https://kubernetes.io/docs/tasks/tools/install-minikube/). |
||||
|
||||
If you are planning on running minikube on a compute |
||||
node in the cloud, you cannot run a hypervisor, so you |
||||
will need to run using the native driver; see |
||||
[installing minikube](https://kubernetes.io/docs/tasks/tools/install-minikube/). |
||||
|
||||
Once you have installed minikube, you do not need to |
||||
install kubernetes. |
||||
|
||||
## Installing byok8s |
||||
|
||||
Start by cloning the repo and installing byok8s: |
||||
|
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```plain |
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cd |
||||
git clone https://github.com/charlesreid1/2019-snakemake-byok8s.git |
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cd ~/2019-snakemake-byok8s |
||||
``` |
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|
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Next, you'll create a virtual environment: |
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|
||||
```plain |
||||
virtualenv vp |
||||
source vp/bin/activate |
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|
||||
pip install -r requirements.txt |
||||
python setup.py build install |
||||
``` |
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|
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Now you should be ready to rock: |
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|
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``` |
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which byok8s |
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``` |
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|
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This will only be present when you have activated |
||||
your virtual environment. To activate/re-activate your |
||||
virtual environment: |
||||
|
||||
``` |
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cd ~/2019-snakemake-byok8s |
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source vp/bin/activate |
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``` |
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|
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|
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# Kubernetes on AWS |
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|
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Check back soon for an EKS guide! |
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|
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@@ -1,11 +1,9 @@
|
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# Kubernetes on Digital Ocean |
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|
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## Digital Ocean Kubernetes |
||||
Check back soon for a Digital Ocean kubernetes guide! |
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|
||||
(Use web interface to set up a Kubernetes cluster, |
||||
then use `kubectl` to connect with Digital Ocean |
||||
via Digital Ocean credentials.) |
||||
|
||||
## Quickstart |
||||
|
||||
[link](https://www.digitalocean.com/docs/kubernetes/how-to/connect-with-kubectl/) |
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|
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# Kubernetes on Google Cloud Platform |
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|
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This document will walk you through how to start a kubernetes cluster using the |
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Google Kubernetes Engine (GKE) on Google Cloud Platform (GCP), run the byok8s |
||||
Snakemake workflow on the GKE kubernetes cluster, and tear down the cluster |
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when the workflow is complete. |
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|
||||
## Setup |
||||
|
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Before you can create a kubernetes cluster on Google Cloud, |
||||
you need a Google Cloud account and a Google Cloud project. |
||||
You can sign up for a Google Cloud account [here](https://cloud.google.com/). |
||||
You can create a new project from the [Google Cloud Console](https://console.cloud.google.com/). |
||||
New accounts start with 300 free hours specifically to let you |
||||
test drive features like GKE! Cool! |
||||
|
||||
Once you have your account and your project, you can install |
||||
the `gcloud` Google Cloud SDK command line utility |
||||
(see [Google Cloud SDK Quickstart Guide](https://cloud.google.com/sdk/docs/quickstarts)). |
||||
|
||||
Once you have installed the `gcloud` utility, you will need |
||||
to log in with your Google acount using the `init` command: |
||||
|
||||
``` |
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gcloud init |
||||
``` |
||||
|
||||
This will give you a link to enter into your browser, where |
||||
you will log in with your Google account and recieve a code to |
||||
copy and paste into the terminal. |
||||
|
||||
The **Compute API** and **Kubernetes API** will both need to be |
||||
enabled as well. These can be enabled via the |
||||
[Google Cloud Console](https://console.cloud.google.com/) |
||||
(or read on). |
||||
|
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If you aren't sure how to use the console to enable these APIs, just start |
||||
running the commands below to create a kubernetes cluster, and the gcloud |
||||
utility will let you know if it needs APIs enabled for actions. If it can't |
||||
enable the API for you, it will give you a direct link to the relevant Google |
||||
Cloud Console page. |
||||
|
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## Google Kubernetes Engine |
||||
|
||||
GKE uses Google Cloud compute nodes to run a kubernetes cluster |
||||
on Google Cloud infrastructure. It automatically sets up the |
||||
cluster for you, and allows you to use `kubectl` and `gcloud` to |
||||
manage and interact with the remote cluster. |
||||
|
||||
Official Google link: <https://cloud.google.com/kubernetes-engine/> |
||||
|
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## Quickstart |
||||
|
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As mentioned, make sure your account credentials are initialized: |
||||
|
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``` |
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gcloud init |
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``` |
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|
||||
Create a new GKE cluster: |
||||
|
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``` |
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gcloud container clusters create $CLUSTER_NAME --num-nodes=$NODES --region=us-west1 |
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``` |
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|
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The `--scopes storage-rw` flag is required if you plan to use Google |
||||
Cloud buckets instead of S3 buckets (not currently enabled in byok8s). |
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|
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Next get configuration details about the cluster so your local |
||||
kubernetes controller can control the cluster: |
||||
|
||||
``` |
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gcloud container clusters get-credentials $CLUSTER_NAME |
||||
``` |
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|
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**This will take several minutes.** |
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|
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The cluster should now be up and running and ready to rock: |
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|
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``` |
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$ kubectl get pods --namespace=kube-system |
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NAME READY STATUS RESTARTS AGE |
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event-exporter-v0.2.3-54f94754f4-5jczv 2/2 Running 0 4m |
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fluentd-gcp-scaler-6d7bbc67c5-hkllz 1/1 Running 0 4m |
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fluentd-gcp-v3.1.0-48pb2 2/2 Running 0 2m |
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fluentd-gcp-v3.1.0-58dpx 2/2 Running 0 2m |
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fluentd-gcp-v3.1.0-c4b49 2/2 Running 0 2m |
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fluentd-gcp-v3.1.0-h24m5 2/2 Running 0 2m |
||||
fluentd-gcp-v3.1.0-hbdj4 2/2 Running 0 2m |
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fluentd-gcp-v3.1.0-rfnmt 2/2 Running 0 2m |
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fluentd-gcp-v3.1.0-vwd8w 2/2 Running 0 2m |
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fluentd-gcp-v3.1.0-wxt79 2/2 Running 0 2m |
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fluentd-gcp-v3.1.0-xkt42 2/2 Running 0 2m |
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heapster-v1.5.3-bc9f6bfd5-7jhqs 3/3 Running 0 3m |
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kube-dns-788979dc8f-l7hch 4/4 Running 0 4m |
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kube-dns-788979dc8f-pts99 4/4 Running 0 3m |
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kube-dns-autoscaler-79b4b844b9-j48js 1/1 Running 0 4m |
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kube-proxy-gke-mycluster-default-pool-9ad2912e-130p 1/1 Running 0 4m |
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kube-proxy-gke-mycluster-default-pool-9ad2912e-lfpw 1/1 Running 0 4m |
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kube-proxy-gke-mycluster-default-pool-9ad2912e-rt9m 1/1 Running 0 4m |
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kube-proxy-gke-mycluster-default-pool-b44fa389-2ds8 1/1 Running 0 4m |
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kube-proxy-gke-mycluster-default-pool-b44fa389-hc66 1/1 Running 0 4m |
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kube-proxy-gke-mycluster-default-pool-b44fa389-vh3x 1/1 Running 0 4m |
||||
kube-proxy-gke-mycluster-default-pool-d58ee1e7-2kkw 1/1 Running 0 4m |
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kube-proxy-gke-mycluster-default-pool-d58ee1e7-3l6r 1/1 Running 0 4m |
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kube-proxy-gke-mycluster-default-pool-d58ee1e7-4w18 1/1 Running 0 4m |
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l7-default-backend-5d5b9874d5-ms75l 1/1 Running 0 4m |
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metrics-server-v0.2.1-7486f5bd67-2n6cn 2/2 Running 0 3m |
||||
``` |
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|
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Now assuming you have installed `byok8s` and it is located |
||||
at `~/2019-snakemake-byok8s/`, you can run the test workflow |
||||
on the kubernetes cluster: |
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|
||||
``` |
||||
# Return to our virtual environment |
||||
cd ~/2019-snakemake-byok8s/test/ |
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source vp/bin/activate |
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|
||||
# Export AWS keys for Snakemake |
||||
export AWS_ACCESS_KEY_ID="XXXXX" |
||||
export AWS_SECRET_ACCESS_KEY="XXXXX" |
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|
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# Run byok8s |
||||
byok8s workflow-alpha params-blue --s3-bucket=mah-bukkit |
||||
``` |
||||
|
||||
Once the workflow has run successfully, the results will be written |
||||
to S3 buckets and all the kubernetes containers created by snakemake |
||||
will be gone. |
||||
|
||||
If all goes well, you should see output like this: |
||||
|
||||
``` |
||||
$ byok8s --s3-bucket=mah-bukkit -f workflow-alpha params-blue |
||||
-------- |
||||
details! |
||||
snakefile: /home/ubuntu/2019-snakemake-byok8s/test/Snakefile |
||||
config: /home/ubuntu/2019-snakemake-byok8s/test/workflow-alpha.json |
||||
params: /home/ubuntu/2019-snakemake-byok8s/test/params-blue.json |
||||
target: target1 |
||||
k8s namespace: default |
||||
-------- |
||||
Building DAG of jobs... |
||||
Using shell: /bin/bash |
||||
Provided cores: 1 |
||||
Rules claiming more threads will be scaled down. |
||||
Job counts: |
||||
count jobs |
||||
1 target1 |
||||
1 |
||||
Resources before job selection: {'_cores': 1, '_nodes': 9223372036854775807} |
||||
Ready jobs (1): |
||||
target1 |
||||
Selected jobs (1): |
||||
target1 |
||||
Resources after job selection: {'_cores': 0, '_nodes': 9223372036854775806} |
||||
|
||||
[Mon Jan 28 23:49:51 2019] |
||||
rule target1: |
||||
output: cmr-0123/alpha.txt |
||||
jobid: 0 |
||||
|
||||
echo alpha blue > cmr-0123/alpha.txt |
||||
Get status with: |
||||
kubectl describe pod snakejob-1ab52bdb-903b-5506-b712-ccc86772dc8d |
||||
kubectl logs snakejob-1ab52bdb-903b-5506-b712-ccc86772dc8d |
||||
Checking status for pod snakejob-1ab52bdb-903b-5506-b712-ccc86772dc8d |
||||
Checking status for pod snakejob-1ab52bdb-903b-5506-b712-ccc86772dc8d |
||||
Checking status for pod snakejob-1ab52bdb-903b-5506-b712-ccc86772dc8d |
||||
Checking status for pod snakejob-1ab52bdb-903b-5506-b712-ccc86772dc8d |
||||
Checking status for pod snakejob-1ab52bdb-903b-5506-b712-ccc86772dc8d |
||||
[Mon Jan 28 23:50:41 2019] |
||||
Finished job 0. |
||||
1 of 1 steps (100%) done |
||||
Complete log: /home/ubuntu/2019-snakemake-byok8s/test/.snakemake/log/2019-01-28T234950.253823.snakemake.log |
||||
unlocking |
||||
removing lock |
||||
removing lock |
||||
removed all locks |
||||
``` |
||||
|
||||
Congratulations! You'e just run an executable Snakemake workflow |
||||
on a Google Cloud kubernetes cluster! |
||||
|
||||
You can get more information about the containers running each step of |
||||
the workflow using the `kubectl describe` commands printed in the output. |
||||
Here is an example: |
||||
|
||||
``` |
||||
$ kubectl describe pod snakejob-c91f804c-805a-56a2-b0ea-b3b74bc38001 |
||||
Name: snakejob-c91f804c-805a-56a2-b0ea-b3b74bc38001 |
||||
Namespace: default |
||||
Node: gke-mycluster-default-pool-b44fa389-vh3x/10.138.0.7 |
||||
Start Time: Mon, 28 Jan 2019 23:55:18 -0800 |
||||
Labels: app=snakemake |
||||
Annotations: <none> |
||||
Status: Running |
||||
IP: 10.0.6.4 |
||||
Containers: |
||||
snakejob-c91f804c-805a-56a2-b0ea-b3b74bc38001: |
||||
Container ID: docker://2aaa04c34770c6088334b29c0332dc426aff2fbbd3a8af07b65bbbc2c5fe437d |
||||
Image: quay.io/snakemake/snakemake:v5.4.0 |
||||
Image ID: docker-pullable://quay.io/snakemake/snakemake@sha256:f5bb7bef99c4e45cb7dfd5b55535b8dc185b43ca610341476378a9566a8b52c5 |
||||
Port: <none> |
||||
Host Port: <none> |
||||
Command: |
||||
/bin/sh |
||||
Args: |
||||
-c |
||||
cp -rf /source/. . && snakemake cmr-0123/.zetaB1 --snakefile Snakefile --force -j --keep-target-files --keep-remote --latency-wait 0 --attempt 1 --force-use-threads --wrapper-prefix None --config 'name='"'"'blue'"'"'' -p --nocolor --notemp --no-hooks --nolock --default-remote-provider S3 --default-remote-prefix cmr-0123 --allowed-rules target3sleepyB1 |
||||
State: Running |
||||
Started: Mon, 28 Jan 2019 23:56:15 -0800 |
||||
Ready: True |
||||
Restart Count: 0 |
||||
Requests: |
||||
cpu: 0 |
||||
Environment: |
||||
AWS_ACCESS_KEY_ID: <set to the key 'aws_access_key_id' in secret 'e077a45f-1274-4a98-a76c-d1a9718707db'> Optional: false |
||||
AWS_SECRET_ACCESS_KEY: <set to the key 'aws_secret_access_key' in secret 'e077a45f-1274-4a98-a76c-d1a9718707db'> Optional: false |
||||
Mounts: |
||||
/source from source (rw) |
||||
/var/run/secrets/kubernetes.io/serviceaccount from default-token-jmnv4 (ro) |
||||
Conditions: |
||||
Type Status |
||||
Initialized True |
||||
Ready True |
||||
PodScheduled True |
||||
Volumes: |
||||
source: |
||||
Type: Secret (a volume populated by a Secret) |
||||
SecretName: e077a45f-1274-4a98-a76c-d1a9718707db |
||||
Optional: false |
||||
workdir: |
||||
Type: EmptyDir (a temporary directory that shares a pod's lifetime) |
||||
Medium: |
||||
default-token-jmnv4: |
||||
Type: Secret (a volume populated by a Secret) |
||||
SecretName: default-token-jmnv4 |
||||
Optional: false |
||||
QoS Class: BestEffort |
||||
Node-Selectors: <none> |
||||
Tolerations: node.kubernetes.io/not-ready:NoExecute for 300s |
||||
node.kubernetes.io/unreachable:NoExecute for 300s |
||||
Events: |
||||
Type Reason Age From Message |
||||
---- ------ ---- ---- ------- |
||||
Normal Scheduled 63s default-scheduler Successfully assigned snakejob-c91f804c-805a-56a2-b0ea-b3b74bc38001 to gke-mycluster-default-pool-b44fa389-vh3x |
||||
Normal SuccessfulMountVolume 63s kubelet, gke-mycluster-default-pool-b44fa389-vh3x MountVolume.SetUp succeeded for volume "workdir" |
||||
Normal SuccessfulMountVolume 63s kubelet, gke-mycluster-default-pool-b44fa389-vh3x MountVolume.SetUp succeeded for volume "default-token-jmnv4" |
||||
Normal SuccessfulMountVolume 63s kubelet, gke-mycluster-default-pool-b44fa389-vh3x MountVolume.SetUp succeeded for volume "source" |
||||
Normal Pulling 61s kubelet, gke-mycluster-default-pool-b44fa389-vh3x pulling image "quay.io/snakemake/snakemake:v5.4.0" |
||||
Normal Pulled 10s kubelet, gke-mycluster-default-pool-b44fa389-vh3x Successfully pulled image "quay.io/snakemake/snakemake:v5.4.0" |
||||
Normal Created 6s kubelet, gke-mycluster-default-pool-b44fa389-vh3x Created container |
||||
Normal Started 6s kubelet, gke-mycluster-default-pool-b44fa389-vh3x Started container |
||||
``` |
||||
|
||||
Delete the GKE cluster when you are done: |
||||
|
||||
``` |
||||
gcloud container clusters delete $CLUSTER_NAME |
||||
``` |
||||
|
||||
@ -0,0 +1,115 @@
@@ -0,0 +1,115 @@
|
||||
# Running byok8s with minikube |
||||
|
||||
## Installing |
||||
|
||||
See the [Installing](installing.md) page for details |
||||
about installing byok8s and its prerequisites |
||||
(including minikube). |
||||
|
||||
We cover two scenarios: |
||||
|
||||
- bare metal machine, i.e., a laptop or desktop machine |
||||
that can run a hypervisor like VirtualBox |
||||
|
||||
- cloud machine, i.e., AWS EC2 node, which is itself a |
||||
virtual machine and cannot run a hypervisor |
||||
|
||||
These quickstarts assume you have Python and minikube |
||||
installed, and that you have cloned and installed byok8s |
||||
at `~/2019-snakemake-byok8s/`. |
||||
|
||||
## Quickstart on Bare Metal Machine |
||||
|
||||
On a bare metal machine, the procedure is |
||||
relatively uncomplicated: we create a cluster, |
||||
we export some variables, we run the workflow, |
||||
we tear down the cluster: |
||||
|
||||
```plain |
||||
# Start a minikube cluster |
||||
minikube start |
||||
|
||||
# Verify k8s is running |
||||
minikube status |
||||
|
||||
# Export AWS credentials |
||||
export AWS_ACCESS_KEY_ID="XXXXX" |
||||
export AWS_SECRET_ACCESS_KEY="XXXXX" |
||||
|
||||
# Run the workflow |
||||
byok8s workflow-alpha params-blue --s3-bucket=mah-bukkit |
||||
|
||||
# Stop the minikube cluster |
||||
minikube stop |
||||
``` |
||||
|
||||
## Quickstart on Cloud Machine |
||||
|
||||
As mentioned above, cloud compute nodes are virtual machines |
||||
themselves and cannot run a hypervisor, so things are a bit |
||||
more complicated. |
||||
|
||||
To tell minikube not to use a virtual machine driver, |
||||
run the following command in a terminal to create |
||||
a minikube config file: |
||||
|
||||
``` |
||||
cat <<'EOF' > ~/.minikube/config/config.json |
||||
{ |
||||
"vm-driver": "none" |
||||
} |
||||
EOF |
||||
``` |
||||
|
||||
Now you can start up a minikube cluster. |
||||
|
||||
There is an additional DNS problem that needs to be fixed |
||||
in the containers before you proceed. You will know there |
||||
is a problem if you run the `get pods` command with |
||||
`kubectl` and see your CoreDNS containers in a |
||||
`CrashLoopBackOff` state: |
||||
|
||||
```text |
||||
$ kubectl get pods --namespace=kube-system |
||||
NAME READY STATUS RESTARTS AGE |
||||
coredns-86c58d9df4-lvq8b 0/1 CrashLoopBackOff 5 5m17s |
||||
coredns-86c58d9df4-pr52t 0/1 CrashLoopBackOff 5 5m17s |
||||
... ... ... ... ... |
||||
``` |
||||
|
||||
To fix the problem with the DNS settings, we have to patch |
||||
the CoreDNS image being used by `kube-system`. |
||||
To do that, use the file |
||||
[`test/fixcoredns.yml`](https://github.com/charlesreid1/2019-snakemake-byok8s/blob/master/test/fixcoredns.yml) |
||||
in this repository with `kubectl apply`: |
||||
|
||||
```plain |
||||
# Fix the DNS container |
||||
kubectl apply -f fixcoredns.yml |
||||
|
||||
# Delete all kube-system containers |
||||
kubectl delete --all pods --namespace kube-system |
||||
``` |
||||
|
||||
The kube-system containers will be re-spawned by the cluster control system. |
||||
It should happen in a few seconds, and then you'll be ready to run byok8s: |
||||
|
||||
``` |
||||
# Return to our virtual environment |
||||
cd ~/2019-snakemake-byok8s/test/ |
||||
source vp/bin/activate |
||||
|
||||
# Verify k8s is running |
||||
minikube status |
||||
|
||||
# Export AWS keys for Snakemake |
||||
export AWS_ACCESS_KEY_ID="XXXXX" |
||||
export AWS_SECRET_ACCESS_KEY="XXXXX" |
||||
|
||||
# Run byok8s |
||||
byok8s workflow-alpha params-blue --s3-bucket=mah-bukkit |
||||
``` |
||||
|
||||
Congratulations! You've just run an executable Snakemake workflow |
||||
on a minikube kubernetes cluster. |
||||
|
||||
@ -0,0 +1,155 @@
@@ -0,0 +1,155 @@
|
||||
# Quickstart |
||||
|
||||
This runs through the installation and usage |
||||
of `2019-snakemake-byok8s`. |
||||
|
||||
Step 1: Set up Kubernetes cluster with `minikube`. |
||||
|
||||
Step 2: Install `byok8s`. |
||||
|
||||
Step 3: Run the `byok8s` workflow using the Kubernetes cluster. |
||||
|
||||
Step 4: Tear down Kubernetes cluster with `minikube`. |
||||
|
||||
|
||||
## Step 1: Set Up Virtual Kubernetes Cluster |
||||
|
||||
For the purposes of the quickstart, we will walk |
||||
through how to set up a local, virtual Kubernetes |
||||
cluster using `minikube`. |
||||
|
||||
Start by installing minikube: |
||||
|
||||
``` |
||||
scripts/install_minikube.sh |
||||
``` |
||||
|
||||
Once it is installed, you can start up a kubernetes cluster |
||||
with minikube using the following commands: |
||||
|
||||
``` |
||||
cd test |
||||
minikube start |
||||
``` |
||||
|
||||
NOTE: If you are running on AWS, run this command first |
||||
|
||||
``` |
||||
minikube config set vm-driver none |
||||
``` |
||||
|
||||
to set the the vm driver to none and use native Docker to run stuff. |
||||
|
||||
If you are running on AWS, the DNS in the minikube |
||||
kubernetes cluster will not work, so run this command |
||||
to fix the DNS settings (should be run from the |
||||
`test/` directory): |
||||
|
||||
``` |
||||
kubectl apply -f fixcoredns.yml |
||||
kubectl delete --all pods --namespace kube-system |
||||
``` |
||||
|
||||
|
||||
## Step 2: Install byok8s |
||||
|
||||
Start by setting up a python virtual environment, |
||||
and install the required packages into the |
||||
virtual environment: |
||||
|
||||
``` |
||||
pip install -r requirements.txt |
||||
``` |
||||
|
||||
This installs snakemake and kubernetes Python |
||||
modules. Now install the `byok8s` command line |
||||
tool: |
||||
|
||||
``` |
||||
python setup.py build install |
||||
``` |
||||
|
||||
Now you can run: |
||||
|
||||
``` |
||||
which byok8s |
||||
``` |
||||
|
||||
and you should see `byok8s` in your virtual |
||||
environment's `bin/` directory. |
||||
|
||||
This command line utility will expect a kubernetes |
||||
cluster to be set up before it is run. |
||||
|
||||
Setting up a kubernetes cluster will create... |
||||
(fill in more info here)... |
||||
|
||||
Snakemake will automatically create the pods |
||||
in the cluster, so you just need to allocate |
||||
a kubernetes cluster. |
||||
|
||||
|
||||
## Step 3: Run byok8s |
||||
|
||||
Now you can run the workflow with the `byok8s` command. |
||||
This submits the Snakemake workflow jobs to the Kubernetes |
||||
cluster that minikube created. |
||||
|
||||
You should have your workflow in a `Snakefile` in the |
||||
current directory. Use the `--snakefile` flag if it is |
||||
named something other than `Snakefile`. |
||||
|
||||
You will also need to specify your AWS credentials |
||||
via the `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` |
||||
environment variables. These are used to to access |
||||
S3 buckets for file I/O. |
||||
|
||||
Finally, you will need to create an S3 bucket for |
||||
Snakemake to use for file I/O. Pass the name of the |
||||
bucket using the `--s3-bucket` flag. |
||||
|
||||
Start by exporting these two vars (careful to |
||||
scrub them from bash history): |
||||
|
||||
``` |
||||
export AWS_ACCESS_KEY_ID=XXXXX |
||||
export AWS_SECRET_ACCESS_KEY=XXXXX |
||||
``` |
||||
|
||||
Run the alpha workflow with blue params: |
||||
|
||||
``` |
||||
byok8s --s3-bucket=mah-bukkit workflow-alpha params-blue |
||||
``` |
||||
|
||||
Run the alpha workflow with red params: |
||||
|
||||
``` |
||||
byok8s --s3-bucket=mah-bukkit workflow-alpha params-red |
||||
``` |
||||
|
||||
Run the gamma workflow with red params, &c: |
||||
|
||||
``` |
||||
byok8s --s3-bucket=mah-bukkit workflow-gamma params-red |
||||
``` |
||||
|
||||
(NOTE: May want to let the user specify |
||||
input and output directories with flags.) |
||||
|
||||
All input files are searched for relative to the working |
||||
directory. |
||||
|
||||
|
||||
## Step 4: Tear Down Kubernetes Cluster |
||||
|
||||
The last step once the workflow has been finished, |
||||
is to tear down the kubernetes cluster. The virtual |
||||
kubernetes cluster created by minikube can be torn |
||||
down with the following command: |
||||
|
||||
``` |
||||
minikube stop |
||||
``` |
||||
|
||||
|
||||
@ -0,0 +1,5 @@
@@ -0,0 +1,5 @@
|
||||
# Travis Tests with Minikube |
||||
|
||||
This page is in progress; see this post |
||||
on the <https://charlesreid1.github.io> blog for info: |
||||
[Building Snakemake Command Line Wrappers for Kubernetes Workflows](https://charlesreid1.github.io/building-snakemake-command-line-wrappers-for-kubernetes-workflows.html). |
||||
@ -1,6 +0,0 @@
@@ -1,6 +0,0 @@
|
||||
# Kubernetes on AWS |
||||
|
||||
## Elastic Container Service |
||||
|
||||
## Quickstart |
||||
|
||||
@ -1,7 +0,0 @@
@@ -1,7 +0,0 @@
|
||||
# Kubernetes on Google Cloud Platform |
||||
|
||||
## Google Container Engine |
||||
|
||||
## Quickstart |
||||
|
||||
|
||||
@ -1,6 +0,0 @@
@@ -1,6 +0,0 @@
|
||||
# Minikube on AWS EC2 Nodes |
||||
|
||||
## Quickstart |
||||
|
||||
|
||||
|
||||
@ -0,0 +1 @@
@@ -0,0 +1 @@
|
||||
Subproject commit 745d13f187711bc43865dcb44f21a010689d27ac |
||||
@ -0,0 +1,42 @@
@@ -0,0 +1,42 @@
|
||||
site_name: 2019-snakemake-byok8s |
||||
site_url: https://charlesreid1.github.io/2019-snakemake-byok8s |
||||
repo_name: 2019-snakemake-byok8s |
||||
repo_url: https://github.com/charlesreid1/2019-snakemake-byok8s |
||||
edit_uri: "" |
||||
|
||||
copyright: 'Copyright © 2018 <a href="https://charlesreid1.com">Charles Reid</a>, released under the <a href="https://opensource.org/licenses/MIT">MIT license</a> <br /><br /> |
||||
<div>Icon made by Freepik, obtained from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a>, used under a <a href="http://creativecommons.org/licenses/by/3.0/" title="Creative Commons BY 3.0" target="_blank">CC 3.0 BY</a></div> license.' |
||||
|
||||
docs_dir: docs |
||||
site_dir: site |
||||
extra_css: |
||||
- css/custom.css |
||||
theme: |
||||
name: null |
||||
custom_dir: 'mkdocs-material-dib/material' |
||||
palette: |
||||
primary: 'blue' |
||||
accent: 'blue' |
||||
logo: 'images/ship.svg' |
||||
font: |
||||
text: 'Roboto' |
||||
code: 'Roboto Mono' |
||||
nav: |
||||
- 'Index': 'index.md' |
||||
- 'Installing': 'installing.md' |
||||
- 'Quickstart': 'quickstart.md' |
||||
- 'K8s with Minikube' : 'kubernetes_minikube.md' |
||||
- 'K8s with GCP' : 'kubernetes_gcp.md' |
||||
- 'K8s with AWS' : 'kubernetes_aws.md' |
||||
- 'K8s with DigitalOcean' : 'kubernetes_dok.md' |
||||
- 'Travis Tests': 'travis_tests.md' |
||||
|
||||
# Extensions |
||||
markdown_extensions: |
||||
- admonition |
||||
- codehilite: |
||||
guess_lang: false |
||||
- toc: |
||||
permalink: true |
||||
|
||||
strict: true |
||||
Loading…
Reference in new issue