The purpose of this guide is to install a minimal local Armada deployment for testing and evaluation purposes.
- Git
- Docker
- Helm v3
- Kind
- Kubectl
Ensure the current user has permission to run the docker
command without sudo
.
You can install the pre-requisites with Homebrew:
brew cask install docker
brew install helm kind kubernetes-cli
Ensure at least 5GB of RAM are allocated to the Docker VM (see Preferences -> Resources -> Advanced).
You can install the pre-requisites with Chocolatey:
choco install git docker-desktop kubernetes-helm kind kubernetes-cli
Ensure at least 5GB of RAM are allocated to the Docker VM (see Settings -> Resources -> Advanced).
All the commands below should be executed in Git Bash.
Make sure helm is configured to use the official Helm stable charts:
helm repo add stable https://kubernetes-charts.storage.googleapis.com/
And add the G-Research helm charts repository, too:
helm repo add gresearch https://g-research.github.io/charts/
This guide will install Armada on 3 local Kubernetes clusters; one server and two executor clusters.
You should then clone this repository and step into it:
git clone https://github.com/G-Research/armada.git
cd armada
All commands are intended to be run from the root of the repository.
kind create cluster --name quickstart-armada-server --config ./docs/quickstart/kind-config-server.yaml
# Install Redis
helm install redis stable/redis-ha -f docs/quickstart/redis-values.yaml
# Install Prometheus
helm install prometheus-operator stable/prometheus-operator -f docs/quickstart/server-prometheus-values.yaml
# Install Armada server
helm install armada-server gresearch/armada -f ./docs/quickstart/server-values.yaml
# Get server IP for executors
SERVER_IP=$(kubectl get nodes quickstart-armada-server-worker -o jsonpath='{.status.addresses[?(@.type=="InternalIP")].address}')
First executor:
kind create cluster --name quickstart-armada-executor-0 --config ./docs/quickstart/kind-config-executor.yaml
# Install Prometheus
helm install prometheus-operator stable/prometheus-operator -f docs/quickstart/executor-prometheus-values.yaml
# Install executor
helm install armada-executor gresearch/armada-executor --set applicationConfig.apiConnection.armadaUrl="$SERVER_IP:30000" -f docs/quickstart/executor-values.yaml
helm install armada-executor-cluster-monitoring gresearch/executor-cluster-monitoring -f docs/quickstart/executor-cluster-monitoring-values.yaml
# Get executor IP for Grafana
EXECUTOR_0_IP=$(kubectl get nodes quickstart-armada-executor-0-worker -o jsonpath='{.status.addresses[?(@.type=="InternalIP")].address}')
Second executor:
kind create cluster --name quickstart-armada-executor-1 --config ./docs/quickstart/kind-config-executor.yaml
# Install Prometheus
helm install prometheus-operator stable/prometheus-operator -f docs/quickstart/executor-prometheus-values.yaml
# Install executor
helm install armada-executor gresearch/armada-executor --set applicationConfig.apiConnection.armadaUrl="$SERVER_IP:30000" -f docs/quickstart/executor-values.yaml
helm install armada-executor-cluster-monitoring gresearch/executor-cluster-monitoring -f docs/quickstart/executor-cluster-monitoring-values.yaml
# Get executor IP for Grafana
EXECUTOR_1_IP=$(kubectl get nodes quickstart-armada-executor-1-worker -o jsonpath='{.status.addresses[?(@.type=="InternalIP")].address}')
curl -X POST -i http://admin:prom-operator@localhost:30001/api/datasources -H "Content-Type: application/json" -d '{"name":"cluster-0","type":"prometheus","url":"http://'$EXECUTOR_0_IP':30001","access":"proxy","basicAuth":false}'
curl -X POST -i http://admin:prom-operator@localhost:30001/api/datasources -H "Content-Type: application/json" -d '{"name":"cluster-1","type":"prometheus","url":"http://'$EXECUTOR_1_IP':30001","access":"proxy","basicAuth":false}'
curl -X POST -i http://admin:prom-operator@localhost:30001/api/dashboards/import --data-binary @./docs/quickstart/grafana-armada-dashboard.json -H "Content-Type: application/json"
The following steps download the armadactl
CLI to the current directory:
#!/bin/bash
echo "Downloading armadactl for your platform"
# Determine Platform
SYSTEM=$(uname | sed 's/MINGW.*/windows/' | tr A-Z a-z)
if [ $SYSTEM == "windows" ]; then
ARCHIVE_TYPE=zip
UNARCHIVE="zcat > armadactl.exe"
else
ARCHIVE_TYPE=tar.gz
UNARCHIVE="tar xzf -"
fi
# Find the latest Armada version
LATEST_GH_URL=$(curl -fsSLI -o /dev/null -w %{url_effective} https://github.com/G-Research/armada/releases/latest)
ARMADA_VERSION=${LATEST_GH_URL##*/}
ARMADACTL_URL="https://github.com/G-Research/armada/releases/download/$ARMADA_VERSION/armadactl-$ARMADA_VERSION-$SYSTEM-amd64.$ARCHIVE_TYPE"
# Download and untar/unzip armadactl
if curl -sL $ARMADACTL_URL | sh -c "$UNARCHIVE" ; then
echo "armadactl downloaded successfully"
else
echo "Something is amiss!"
echo "Please visit:"
echo " - https://github.com/G-Research/armada/releases/latest"
echo "to find the latest armadactl binary for your platform"
fi
Alternatively, you can find the latst armadactl binaries at:
Simply download the latest release for your platform and unzip or untar.
Create queues, submit some jobs and monitor progress:
./armadactl create-queue queue-a --priorityFactor 1
./armadactl create-queue queue-b --priorityFactor 2
./armadactl submit ./docs/quickstart/job-queue-a.yaml
./armadactl submit ./docs/quickstart/job-queue-b.yaml
Watch individual queues:
./armadactl watch queue-a job-set-1
./armadactl watch queue-b job-set-1
Log in to the Grafana dashboard at http://localhost:30001 using the default credentials of admin
/ prom-operator
.
Navigate to the Armada Overview dashboard to get a view of jobs progressing through the system.
Try submitting lots of jobs and see queues build and get processed:
for i in {1..50}
do
./armadactl submit ./docs/quickstart/job-queue-a.yaml
./armadactl submit ./docs/quickstart/job-queue-b.yaml
done
CLI:
$ ./armadactl watch queue-a job-set-1
Watching job set job-set-1
Nov 4 11:43:36 | Queued: 0, Leased: 0, Pending: 0, Running: 0, Succeeded: 0, Failed: 0, Cancelled: 0 | event: *api.JobSubmittedEvent, job id: 01drv3mey2mzmayf50631tzp9m
Nov 4 11:43:36 | Queued: 1, Leased: 0, Pending: 0, Running: 0, Succeeded: 0, Failed: 0, Cancelled: 0 | event: *api.JobQueuedEvent, job id: 01drv3mey2mzmayf50631tzp9m
Nov 4 11:43:36 | Queued: 1, Leased: 0, Pending: 0, Running: 0, Succeeded: 0, Failed: 0, Cancelled: 0 | event: *api.JobSubmittedEvent, job id: 01drv3mf7b6fd1rraeq1f554fn
Nov 4 11:43:36 | Queued: 2, Leased: 0, Pending: 0, Running: 0, Succeeded: 0, Failed: 0, Cancelled: 0 | event: *api.JobQueuedEvent, job id: 01drv3mf7b6fd1rraeq1f554fn
Nov 4 11:43:38 | Queued: 1, Leased: 1, Pending: 0, Running: 0, Succeeded: 0, Failed: 0, Cancelled: 0 | event: *api.JobLeasedEvent, job id: 01drv3mey2mzmayf50631tzp9m
Nov 4 11:43:38 | Queued: 0, Leased: 2, Pending: 0, Running: 0, Succeeded: 0, Failed: 0, Cancelled: 0 | event: *api.JobLeasedEvent, job id: 01drv3mf7b6fd1rraeq1f554fn
Nov 4 11:43:38 | Queued: 0, Leased: 1, Pending: 1, Running: 0, Succeeded: 0, Failed: 0, Cancelled: 0 | event: *api.JobPendingEvent, job id: 01drv3mey2mzmayf50631tzp9m
Nov 4 11:43:38 | Queued: 0, Leased: 0, Pending: 2, Running: 0, Succeeded: 0, Failed: 0, Cancelled: 0 | event: *api.JobPendingEvent, job id: 01drv3mf7b6fd1rraeq1f554fn
Nov 4 11:43:41 | Queued: 0, Leased: 0, Pending: 1, Running: 1, Succeeded: 0, Failed: 0, Cancelled: 0 | event: *api.JobRunningEvent, job id: 01drv3mf7b6fd1rraeq1f554fn
Nov 4 11:43:41 | Queued: 0, Leased: 0, Pending: 0, Running: 2, Succeeded: 0, Failed: 0, Cancelled: 0 | event: *api.JobRunningEvent, job id: 01drv3mey2mzmayf50631tzp9m
Nov 4 11:44:17 | Queued: 0, Leased: 0, Pending: 0, Running: 1, Succeeded: 1, Failed: 0, Cancelled: 0 | event: *api.JobSucceededEvent, job id: 01drv3mf7b6fd1rraeq1f554fn
Nov 4 11:44:26 | Queued: 0, Leased: 0, Pending: 0, Running: 0, Succeeded: 2, Failed: 0, Cancelled: 0 | event: *api.JobSucceededEvent, job id: 01drv3mey2mzmayf50631tzp9m
Grafana:
Note that the jobs in this demo simply run the sleep
command so do not consume much resource.