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StackGres Operator, Full Stack PostgreSQL on Kubernetes
StackGres is the Stack required for enterprise production PostGres. A fully-featured platform to run Postgres on Kubernetes. Fully Open Source, StackGres supports both a declarative approach suitable for GitOps workflows and a complete Web Console for the best user experience.
Built by OnGres ("On PostGres"), StackGres requires little to no prior Postgres experience. StackGres can perform fully automated deployments; fully automated database operations ("Day 2 operations") and comes with advanced database tuning by default. Yet remaining highly customizable for Postgres expert DBAs.
StackGres integrates the most renowned and production-tested high availability software for Postgres: Patroni. It’s fully integrated, there’s nothing else to do. If any pod, any node, anything fails, in a matter of seconds the cluster will reheal automatically, without human intervention. StackGres exposes one read-write (always pointing to the master) and one read-only (load balancer distributing load to replicas) connection for the applications, that will automatically be updated after any disruptive event happens.
Backups are a critical part of a database, and are key to any Disaster Recovery strategy. StackGres includes backups based on continuous archiving, which allows for zero data loss recovery and PITR (restore a database into an arbitrary past instant of time).
StackGres also provides automated lifecycle management of the backups. And backups are always stored in the most durable media available today: cloud object storage like Amazon’s S3, Google Cloud Storage or Azure Blob. You can also use Minio or other S3-compatible software to store your backups.
Just provide your bucket access information and credentials, configure the retention window, and everything else is automated. You can also create manual backups with a simple YAML file at any time.
If you have Prometheus Operator installed in your Kubernetes, you are just a click or a boolean flag in a YAML file away from having fully automatic integration with Prometheus (see prometheusAutobind). Check the Helm values that you may specify when installing StackGres to also autodetect Grafana, and you are ready to go!
You will get all the metrics from the clusters in Prometheus. You will also get StackGres predefined custom Grafana dashboards, curated by expert Postgres DBAs, all integrated into the web console.
Tired of typing kubectl exec into each and one of the N pods of your cluster, to then grep+awk the Postgres logs to get the information you are looking for? There’s a better way with StackGres.
Query the logs with SQL, from a centralized location! StackGres supports centralized, distributed logs. With a simple YAML-based CRD, or from the web console, you can create a Distributed Log Cluster in seconds. Then reference it from the cluster(s) you create.
Query your logs with SQL to unleash the full DBA potential. Or visualize them on the web console, which includes search and filter capabilities. All logs are enhanced with very rich metadata. Postgres troubleshooting, we’ve got you covered.
Due to the Postgres process model, it is highly advisable to have connection pooling in most production scenarios. Yet it is not an easy topic.
StackGres comes by default with integrated server-side connection pooling. It is deployed as a sidecar to the Postgres container. Server-side pooling enables controlling the connections fan-in, that is, the incoming connections to Postgres, and making sure Postgres is not overwhelmed with traffic that may cause significant performance degradation.
You can tune the low-level configuration or even entirely disable connection pooling (see PoolConfig CRD), and of course manage it from the web console.
StackGres also exports relevant connection pooling metrics to Prometheus, and specialized dashboards are shown in the Grafana integrated into the web console.
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Partner validated products are tested by Red Hat Partners and supported as defined in the Red Hat Third Party Component Policy.
Red Hat OpenShift 4.12, 4.14, 4.16, 4.17, 4.18, 4.19, 4.20, 4.21
Red Hat OpenShift 4.12, 4.14, 4.16, 4.17, 4.18, 4.19, 4.20, 4.21, 4.22