Often we require a multi cluster deployment where we need to replicate a stack across multiple locations.
These multiple clusters should be able to connect and communicate among themselves.
We tried deploying such a stack through EMCO platform.
While most of the deployment is automated, there are few steps which were done manually and each of them have been mentioned here.
So, these steps shall also be automated and the entire stack shall be a 1 click deployment through EMCO.
The components of the stack are below :
Step-by-step guide
For smooth deployment we have created 3 scripts. One must edit the script to give the correct cluster details to each script. For eg, kubeconfig file, cluster ips
and also the corrects URLs where EMCO binaries like orchestrator, clm etc are running.
- m3operatorScript -
- This script has to run first as it deploys the m3operator.
- M3operator is a pre-requisite for the m3 cluster deployment.
- Make necessary changes in the script as per the cluster details at your end.
- Helm charts and profile can be found at : operatorHelmChartsAndProfile
After you are done with the m3Operator installation, the following pods shall be running
vagrant@emco:~/multicloud-k8s/kud/tests$ kcc2 get pods NAME READY STATUS RESTARTS AGE etcd-0 1/1 Running 0 30s etcd-1 1/1 Running 0 18s etcd-2 1/1 Running 0 10s m3db-operator-0 1/1 Running 0 30s
- m3dbInstallerScript -
- This script shall install m3db nodes.
- Helm charts and profile : m3dbHelmCharts
- This script shall also bring m3coordinator-m3db-cluster service.
- A sidecar process, M3Coordinator, allows M3DB to act as the long-term storage for Prometheus. Its responsible for integration with prometheus
After the m3installer script is run , the pods and services visible shall be :
vagrant@emco:~/multicloud-k8s/kud/tests$ kcc2 get pods NAME READY STATUS RESTARTS AGE etcd-0 1/1 Running 0 5m11s etcd-1 1/1 Running 0 4m59s etcd-2 1/1 Running 0 4m51s gr-grafana-5c57fbd899-llmmm 1/1 Running 0 2d5h m3db-cluster-rep0-0 1/1 Running 0 105s m3db-cluster-rep1-0 1/1 Running 0 84s m3db-cluster-rep2-0 1/1 Running 0 60s m3db-operator-0 1/1 Running 0 5m11s vagrant@emco:~/multicloud-k8s/kud/tests$ kcc2 get svc NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE etcd ClusterIP None <none> 2379/TCP,2380/TCP 5m22s etcd-cluster ClusterIP 10.244.13.90 <none> 2379/TCP 5m22s gr-grafana NodePort 10.244.12.2 <none> 80:30007/TCP 2d5h kubernetes ClusterIP 10.244.0.1 <none> 443/TCP 2d18h m3coordinator-m3db-cluster ClusterIP 10.244.36.133 <none> 7201/TCP,7203/TCP 116s m3dbnode-m3db-cluster ClusterIP None <none> 9000/TCP,9001/TCP,9002/TCP,9003/TCP,9004/TCP,7201/TCP,7203/TCP 116s
- CollectD-PrometheusScript - This script shall install collectd and prometheus. Helm charts for collectd and prometheus : collectd and prometheus
- Once all pods are deployed correctly, the topology should be like below:
Manual steps for getting the m3db up and running:
As pointed out earlier, we are working on some steps which are not automated for the deployment of the stack.
In due course of time, these might as well be automated. But these are steps till then :
1. Three node cluster on which m3db needs to be deployed have to be labelled, before the m3db script is run. The commands :
NODES=($(kubectl get nodes --output=jsonpath={.items..metadata.name}))
kubectl label node/${NODES[0]} failure-domain.beta.kubernetes.io/region=us-west1-a
kubectl label node/${NODES[1]} failure-domain.beta.kubernetes.io/region=us-west1-b
kubectl label node/${NODES[2]} failure-domain.beta.kubernetes.io/region=us-west1-c
kubectl label node/${NODES[0]} failure-domain.beta.kubernetes.io/zone=us-west1-a --overwrite=true
kubectl label node/${NODES[1]} failure-domain.beta.kubernetes.io/zone=us-west1-b --overwrite=true
kubectl label node/${NODES[2]} failure-domain.beta.kubernetes.io/zone=us-west1-c --overwrite=true
2. Create db namespace and bootstrap m3 db
kubectl -n training port-forward svc/m3coordinator-m3db-cluster 7201
curl -vvv -X POST http://localhost:7201/api/v1/database/create -d '{
"type": "cluster",
"namespaceName": "collectd",
"retentionTime": "168h",
"numShards": "64",
"replicationFactor": "3",
"hosts": [
{
"id": "m3db-cluster-rep0-0",
"isolationGroup": "us-west1-a",
"zone": "embedded",
"weight": 100,
"address": "m3db-cluster-rep0-0.m3dbnode-m3db-cluster:9000",
"port": 9000
},
{
"id": "m3db-cluster-rep1-0",
"isolationGroup": "us-west1-b",
"zone": "embedded",
"weight": 100,
"address": "m3db-cluster-rep1-0.m3dbnode-m3db-cluster:9000",
"port": 9000
},
{
"id": "m3db-cluster-rep2-0",
"isolationGroup": "us-west1-c",
"zone": "embedded",
"weight": 100,
"address": "m3db-cluster-rep2-0.m3dbnode-m3db-cluster:9000",
"port": 9000
}
]
}'
3. Connecting the prometheus and m3coordinator service.
After the pods for m3db and prometheus, we need to make m3coordinator service a NodePort in case, we are not using the loadbalance.
This can be done by kubectl edit command :
kubectl edit svc/m3coordinator-m3-cluster Edit type to be NodePort instead of the "ClusterIP" that is present there.