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Overview

The goal of PGO, the Postgres Operator from Crunchy Data is to provide a means to quickly get your applications up and running on Postgres for both development and production environments. To understand how PGO does this, we want to give you a tour of its architecture, with explains both the architecture of the PostgreSQL Operator itself as well as recommended deployment models for PostgreSQL in production!

PGO Architecture

The Crunchy PostgreSQL Operator extends Kubernetes to provide a higher-level abstraction for rapid creation and management of PostgreSQL clusters. The Crunchy PostgreSQL Operator leverages a Kubernetes concept referred to as “Custom Resources” to create several custom resource definitions (CRDs) that allow for the management of PostgreSQL clusters.

The main custom resource definition is postgresclusters.postgres-operator.crunchydata.com. This allows you to control all the information about a Postgres cluster, including:

  • General information
  • Resource allocation
  • High availability
  • Backup management
  • Where and how it is deployed (affinity, tolerations, topology spread constraints)
  • Disaster Recovery / standby clusters
  • Monitoring

and more.

PGO itself runs as a Deployment and is composed of a single container.

  • operator (image: postgres-operator) - This is the heart of the PostgreSQL Operator. It contains a series of Kubernetes controllers that place watch events on a series of native Kubernetes resources (Jobs, Pods) as well as the Custom Resources that come with the PostgreSQL Operator (Pgcluster, Pgtask)

The main purpose of PGO is to create and update information around the structure of a Postgres Cluster, and to relay information about the overall status and health of a PostgreSQL cluster. The goal is to also simplify this process as much as possible for users. For example, let’s say we want to create a high-availability PostgreSQL cluster that has multiple replicas, supports having backups in both a local storage area and Amazon S3 and has built-in metrics and connection pooling, similar to:

PostgreSQL Cluster Architecture

This can be accomplished with a relatively simple manifest. Please refer to the tutorial for how to accomplish this, or see the Postgres Operator examples repo.

The Postgres Operator handles setting up all of the various StatefulSets, Deployments, Services and other Kubernetes objects.

You will also notice that high-availability is enabled by default if you deploy at least one Postgres replica. The Crunchy PostgreSQL Operator uses a distributed-consensus method for PostgreSQL cluster high-availability, and as such delegates the management of each cluster’s availability to the clusters themselves. This removes the PostgreSQL Operator from being a single-point-of-failure, and has benefits such as faster recovery times for each PostgreSQL cluster. For a detailed discussion on high-availability, please see the High-Availability section.

Kubernetes StatefulSets: The PGO Deployment Model

PGO, the Postgres Operator from Crunchy Data, uses Kubernetes StatefulSets for running Postgres instances, and will use Deployments for more ephemeral services.

PGO deploys Kubernetes Statefulsets in a way to allow for creating both different Postgres instance groups and be able to support advanced operations such as rolling updates that minimize or eliminate Postgres downtime. Additional components in our PostgreSQL cluster, such as the pgBackRest repository or an optional PgBouncer, are deployed with Kubernetes Deployments.

With the PGO architecture, we can also leverage Statefulsets to apply affinity and toleration rules across every Postgres instance or individual ones. For instance, we may want to force one or more of our PostgreSQL replicas to run on Nodes in a different region than our primary PostgreSQL instances.

What’s great about this is that PGO manages this for you so you don’t have to worry! Being aware of this model can help you understand how the Postgres Operator gives you maximum flexibility for your PostgreSQL clusters while giving you the tools to troubleshoot issues in production.

The last piece of this model is the use of Kubernetes Services for accessing your PostgreSQL clusters and their various components. The PostgreSQL Operator puts services in front of each Deployment to ensure you have a known, consistent means of accessing your PostgreSQL components.

Note that in some production environments, there can be delays in accessing Services during transition events. The PostgreSQL Operator attempts to mitigate delays during critical operations (e.g. failover, restore, etc.) by directly accessing the Kubernetes Pods to perform given actions.

Additional Architecture Information

There is certainly a lot to unpack in the overall architecture of PGO. Understanding the architecture will help you to plan the deployment model that is best for your environment. For more information on the architectures of various components of the PostgreSQL Operator, please read onward!