zalando/postgres-operator
Postgres Operator
This project is a PostgreSQL Kubernetes operator and database orchestrator designed to automate the deployment, scaling, and lifecycle management of high-availability database clusters. It functions as a controller that uses declarative manifests to provision and synchronize the state of database instances within a cluster.
The system manages high availability through streaming replication and ensures constant availability during maintenance via rolling updates. It also serves as a backup and recovery manager, handling point-in-time recovery, logical backups, and cluster cloning using cloud storage providers.
Additional capabilities include managing storage volume resizing without process restarts and optimizing database connections through the integration of connection poolers. The operator also covers security and extensibility by managing TLS certificates for encrypted communication and deploying sidecar containers for monitoring and performance tuning.
Features
- PostgreSQL Kubernetes Administration - Provides specialized administration of high-availability PostgreSQL clusters using declarative manifests within Kubernetes.
- Database High Availability - Automates the deployment of high-availability PostgreSQL clusters with automated failover and replication.
- Backup and Recovery - Handles point-in-time recovery, cluster cloning, and logical backups using cloud storage providers.
- Backup & Recovery - Handles point-in-time recovery, cluster cloning, and logical backups using cloud storage providers.
- Cloud Storage Backups - Offloads database snapshots and write-ahead logs to cloud object storage for point-in-time recovery.
- Primary-Replica Replication - Ensures high availability by continuously replicating data from a primary node to standby replicas.
- Cluster State Reconciliation - Continuously aligns the live cluster state with the desired configuration to automate corrective updates.
- Custom Resource Controllers - Implements a controller loop that synchronizes the actual cluster state with declarative Kubernetes manifests.
- Database Cluster Orchestration - Deploys high-availability PostgreSQL clusters and associated resources based on declarative manifests.
- Database Lifecycle Management - Implements rolling minor updates and major version upgrades to manage the operational lifecycle of database clusters.
- Kubernetes Database Upgrades - Executes rolling minor updates and in-place major version upgrades across database clusters on Kubernetes.
- Database Connection Managers - Optimizes database connectivity through the integration of connection poolers and TLS certificate management.
- Connection Pool Managers - Integrates a connection pooler to manage and optimize database connections for applications.
- Database Performance Tuning - Offers database performance tuning via sidecar containers and storage volume resizing.
- Cluster Configuration Management - Applies configuration changes or new images to running clusters via rolling updates of pods.
- Cluster Extensibility - Provides interfaces to extend cluster functionality through the deployment of globally configurable sidecar containers.
- Dynamic Volume Resizing - Increases persistent disk volume sizes without requiring a restart of the running database process.
- Rolling Update Orchestrators - Executes sequential pod restarts to apply version upgrades or configuration changes without downtime.
- Sidecar Containers - Deploys auxiliary containers alongside the database for monitoring, tuning, and external tool connectivity.
- TLS Certificate Management - Automates the distribution and rotation of TLS security certificates for encrypted database traffic.
- Network Security - Implements custom TLS certificates to encrypt and secure communication between the application and database.
- Kubernetes Management - Operator for managing HA PostgreSQL clusters on Kubernetes.
- Kubernetes Operators - Automated PostgreSQL cluster management on Kubernetes.
Star history
How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
