Step-by-step deployment option uses kubectl and Helm commands to facilitate a more customized deployment plan
Why do we have a step-by-step deployment alternative?
While it is possible to automate all the deployment steps listed in this section, since one of core propositions of Rierino is an open architecture, we provide our clients full transparency over the list of activities that are happening.
This approach also allows customization of each step based on performance and cost optimization decisions.
Set-up the Deployer
Rierino platform uses a central deployment coordinator, facilitated through Kubernetes jobs and services. As the first step for deployment, this coordinator should be configured.
Now, you can start deploying Rierino workloads and services using the deployer job and deployer api service.
Deployer jobs use Ansible playbooks, which in turn install helm charts, for service deployments. While it is possible to use helm charts directly for service deployments instead, this approach allows centralized management of asset credentials, as well as more structured utilization of deployment asset files to set details of chart parameters.
Populate Assets
Rierino deployment requires various configurations on prerequisite systems, which are executed using initialization playbooks.
You can add --set values.mongodb_uri=[MONGODB_URI] parameter if MongoDB servers are not already tagged and can be discovered by Ansible inventory plugin.
You can add --set values.kafkaServers=[KAFKA_SERVERS] parameter if Kafka servers are not already tagged and can be discovered by Ansible inventory plugin.
You can add --set values.kc_api_uri=[KEYCLOAK_URI] parameter if Keycloak server is not already tagged and can be discovered by Ansible inventory plugin.
If additional systems will be utilized, you can use related deployment assets (e.g. Elasticsearch, Druid imports) as well.
Deploy Admin Core Runners
The first set of Rierino services provide the admin core runners, which can be utilized afterwards to deploy additional services through the admin UI itself.
Depending on your MongoDB, Kafka, Keycloak configurations as well as your cloud service provider, you may need to override parameters in Global Helm playbook.