K8s Helm Chart for running StackStorm cluster in HA mode.
It will install 2 replicas for each component of StackStorm microservices for redundancy, as well as backends like RabbitMQ HA, MongoDB HA Replicaset and etcd cluster that st2 replies on for MQ, DB and distributed coordination respectively.
It's more than welcome to fine-tune each component settings to fit specific availability/scalability demands.
- Kubernetes cluster
- Helm and Tiller
v2.x
- Edit
values.yamlwith configuration for the StackStorm HA K8s cluster.
NB! It's highly recommended to set your own secrets as file contains unsafe defaults like self-signed SSL certificates, SSH keys, StackStorm access and DB/MQ passwords!
- Pull 3rd party Helm dependencies:
helm dependency update
- Install the chart
helm install .
- Upgrade Once you make any changes to values, upgrade the cluster:
helm upgrade <release-name> .
By default, StackStorm Community FOSS version is configured via Helm chart. If you want to install StackStorm Enterprise (EWC), run:
helm install --set enterprise.enabled=true --set enterprise.license=<ST2_LICENSE_KEY> .
It will pull enterprise images from private Docker registry as well as allows configuring features like RBAC and LDAP.
See Helm values.yaml, enterprise section for configuration examples.
Don't have StackStorm Enterprise License?
90-day free trial can be requested at https://stackstorm.com/#product
The default configuration values for this chart are described in values.yaml.
Ingress is worth considering if you want to expose multiple services under the same IP address, and
these services all use the same L7 protocol (typically HTTP). You only pay for one load balancer if
you are using native cloud integration, and because Ingress is "smart", you can get a lot of
features out of the box (like SSL, Auth, Routing, etc.). See the ingress section in values.yaml
for configuration details.
You will first need to deploy an ingress controller of your preference. See https://kubernetes.io/docs/concepts/services-networking/ingress-controllers/#additional-controllers for more information.
The Community FOSS Dockerfiles used to generate the docker images for each st2 component are available at st2-dockerfiles.
A helper container to switch into and run st2 CLI commands against the deployed StackStorm cluster. All resources like credentials, configs, RBAC, packs, keys and secrets are shared with this container.
# obtain st2client pod name
ST2CLIENT=$(kubectl get pod -l app=st2client -o jsonpath="{.items[0].metadata.name}")
# run a single st2 client command
kubectl exec -it ${ST2CLIENT} -- st2 --version
# switch into a container shell and use st2 CLI
kubectl exec -it ${ST2CLIENT} /bin/bash
st2web is a StackStorm Web UI admin dashboard. By default, st2web K8s config includes a Pod Deployment and a Service.
2 replicas (configurable) of st2web serve the web app and proxy requests to st2auth, st2api, st2stream.
By default, st2web uses HTTP instead of HTTPS. We recommend you rely on LoadBalancer or Ingress to add HTTPS layer on top of it.
Note! By default, st2web is a NodePort Service and is not exposed to the public net. If your Kubernetes cluster setup supports the LoadBalancer service type, you can edit the corresponding helm values to configure st2web as a LoadBalancer service in order to expose it and the services it proxies to the public net.
All authentication is managed by st2auth service.
K8s configuration includes a Pod Deployment backed by 2 replicas by default and Service of type ClusterIP listening on port 9100.
Multiple st2auth processes can be behind a load balancer in an active-active configuration and you can increase number of replicas per your discretion.
Service hosts the REST API endpoints that serve requests from WebUI, CLI, ChatOps and other st2 components.
K8s configuration consists of Pod Deployment with 2 default replicas for HA and ClusterIP Service accepting HTTP requests on port 9101.
Being one of the most important StackStorm services with a lot of logic involved,
we recommend you increase the number of replicas if you expect increased load.
StackStorm st2stream - exposes a server-sent event stream, used by the clients like WebUI and ChatOps to receive updates from the st2stream server.
Similar to st2auth and st2api, st2stream K8s configuration includes Pod Deployment with 2 replicas for HA (can be increased in values.yaml)
and ClusterIP Service listening on port 9102.
st2rulesengine evaluates rules when it sees new triggers and decides if new action execution should be requested.
K8s config includes Pod Deployment with 2 (configurable) replicas by default for HA.
st2timersengine is responsible for scheduling all user specified timers aka st2 cron. Only a single replica is created via K8s Deployment as timersengine can't work in active-active mode at the moment (multiple timers will produce duplicated events) and it relies on K8s failover/reschedule capabilities to address cases of process failure.
st2workflowengine drives the execution of orquesta workflows and actually schedules actions to run by another component st2actionrunner.
Multiple st2workflowengine processes can run in active-active mode and so minimum 2 K8s Deployment replicas are created by default.
All the workflow engine processes will share the load and pick up more work if one or more of the processes become available.
Note! As Mistral is going to be deprecated and removed from StackStorm platform soon, Helm chart relies only on Orquesta st2workflowengine as a new native workflow engine.
st2scheduler is responsible for handling ingress action execution requests.
2 replicas for K8s Deployment are configured by default to increase StackStorm scheduling throughput.
Multiple st2notifier processes can run in active-active mode, using connections to RabbitMQ and MongoDB and generating triggers based on
action execution completion as well as doing action rescheduling.
In an HA deployment there must be a minimum of 2 replicas of st2notifier running, requiring a coordination backend,
which in our case is etcd.
st2sensorcontainer manages StackStorm sensors: It starts, stops and restarts them as subprocesses.
By default, deployment is configured with 1 replica containing all the sensors.
st2sensorcontainer also supports a more Docker-friendly single-sensor-per-container mode as a way of Sensor Partitioning. This distributes the computing load between many pods and relies on K8s failover/reschedule mechanisms, instead of running everything on a single instance of st2sensorcontainer. The sensor(s) must be deployed as part of the custom packs image.
As an example, override the default Helm values as follows:
st2:
packs:
sensors:
- name: github
ref: githubwebhook.GitHubWebhookSensor
- name: circleci
ref: circle_ci.CircleCIWebhookSensor
Stackstorm workers that actually execute actions.
5 replicas for K8s Deployment are configured by default to increase StackStorm ability to execute actions without excessive queuing.
Relies on etcd for coordination. This is likely the first thing to lift if you have a lot of actions
to execute per time period in your StackStorm cluster.
Service that cleans up old executions and other operations data based on setup configurations.
Having 1 st2garbagecollector replica for K8s Deployment is enough, considering its periodic execution nature.
By default this process does nothing and needs to be configured in st2.conf settings (via values.yaml).
Purging stale data can significantly improve cluster abilities to perform faster and so it's recommended to configure st2garbagecollector in production.
StackStorm ChatOps service, based on hubot engine, custom stackstorm integration module and preinstalled list of chat adapters.
Due to Hubot limitation, st2chatops doesn't provide mechanisms to guarantee high availability and so only single 1 node of st2chatops is deployed.
This service is disabled by default. Please refer to Helm values.yaml about how to enable and configure st2chatops with ENV vars for your preferred chat service.
StackStorm works with MongoDB as a database engine. External Helm Chart is used to configure MongoDB HA ReplicaSet.
By default 3 nodes (1 primary and 2 secondaries) of MongoDB are deployed via K8s StatefulSet.
For more advanced MongoDB configuration, refer to official mongodb-replicaset
Helm chart settings, which might be fine-tuned via values.yaml.
The deployment of MongoDB to the k8s cluster can be disabled by setting the mongodb-ha.enabled key in values.yaml to false. Note: Stackstorm relies heavily on connections to a MongoDB instance. If the in-cluster deployment of MongoDB is disabled, a connection to an external instance of MongoDB must be configured. The st2.config key in values.yaml provides a way to configure stackstorm. See Configure MongoDB for configuration details.
RabbitMQ is a message bus StackStorm relies on for inter-process communication and load distribution.
External Helm Chart is used to deploy RabbitMQ cluster in Highly Available mode.
By default 3 nodes of RabbitMQ are deployed via K8s StatefulSet.
For more advanced RabbitMQ configuration, please refer to official rabbitmq-ha
Helm chart repository, - all settings could be overridden via values.yaml.
The deployment of RabbitMQ to the k8s cluster can be disabled by setting the rabbitmq-ha.enabled key in values.yaml to false. Note: Stackstorm relies heavily on connections to a RabbitMQ instance. If the in-cluster deployment of RabbitMQ is disabled, a connection to an external instance of RabbitMQ must be configured. The st2.config key in values.yaml provides a way to configure stackstorm. See Configure RabbitMQ for configuration details.
StackStorm employs etcd as a distributed coordination backend, required for st2 cluster components to work properly in HA scenario.
3 node Raft cluster is deployed via external official Helm chart dependency etcd-operator.
As any other Helm dependency, it's possible to further configure it for specific scaling needs via values.yaml.
In distributed environment of the Kubernetes cluster st2 pack install won’t work.
Instead, you need to bake the packs into a custom docker image, push it to a private or public docker registry and reference that image in Helm values.
Helm chart will take it from there, sharing /opt/stackstorm/{packs,virtualenvs} via a sidecar container in pods which require access to the packs.
For your convenience, we created a new st2-pack-install <pack1> <pack2> <pack3> utility and included it in a container that will help to install custom packs during the Docker build process without relying on live DB and MQ connection.
Please see https://github.com/StackStorm/st2packs-dockerfiles/ for instructions on how to build your custom st2packs image.
Update the st2.packs.configs section of Helm values:
For example:
configs:
email.yaml: |
---
# example email pack config file
vault.yaml: |
---
# example vault pack config file
Don't forget running Helm upgrade to apply new changes.
If you need to pull your custom packs Docker image from a private repository, create a Kubernetes Docker registry secret and pass it to Helm values. See K8s documentation for more info.
# Create a Docker registry secret called 'st2packs-auth'
kubectl create secret docker-registry st2packs-auth --docker-server=<your-registry-server> --docker-username=<your-name> --docker-password=<your-password>
Once secret created, reference its name in helm value: st2.packs.image.pullSecret.
Grab all logs for entire StackStorm cluster with dependent services in Helm release:
kubectl logs -l release=<release-name>
Grab all logs only for stackstorm backend services, excluding st2web and DB/MQ/etcd:
kubectl logs -l release=<release-name>,tier=backend
If you have any suggestions or ideas about how to extend this chart functionality,
we welcome you to collaborate in Issues
and contribute via Pull Requests.
However if you need something very custom and specific to your infra that doesn't fit official chart plans,
we strongly recommend you to create a parent Helm chart with custom K8s objects and referencing stackstorm-ha chart
as a child dependency.
This approach allows not only extending sub-chart with custom objects and templates within the same deployment,
but also adds flexibility to include many sub-chart dependencies and pin versions as well as include all the sub-chart values in one single place.
This approach is infra-as-code friendly and more reproducible. See official Helm documentation about
Subcharts and Dependencies.