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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsRunning a database on Kubernetes means its database process and data-management resources run in the cluster; an application connecting to a database hosted elsewhere is still using an external database. For PostgreSQL, an operator such as CloudNativePG can automate database-specific lifecycle tasks, but it does not remove the need to design storage, backups, recovery, monitoring, and upgrades.
What “on Kubernetes” means for a database
A database is a stateful workload: its data must persist beyond an individual container or pod, and its identity, failover, and recovery behavior need deliberate design. Kubernetes supplies building blocks such as persistent volume claims (PVCs), scheduling, and service discovery. A database operator adds database-aware behavior to those primitives, coordinating actions such as creating instances, managing primary and standby roles, and exposing connection services.
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CloudNativePG is one PostgreSQL example. It represents a PostgreSQL deployment with a custom Kubernetes Cluster resource and manages PVCs directly rather than using StatefulSets as its persistence mechanism. Its version 1.25 documentation describes that resource model; confirm behavior against the documentation for the operator version you deploy. The CloudNativePG project overview describes its PostgreSQL lifecycle, replication, persistence, and recovery capabilities.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware match“Next to Kubernetes” describes a different arrangement: the application runs in the cluster, but the database is hosted outside it, for example as a separately operated service. The application may still discover and connect to it over the network, but the database process and its data lifecycle are not managed as in-cluster resources.
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Should you run the database inside the cluster?
There is no universal winner between an in-cluster database and an external or managed one. The decision turns on who will operate it, what control the workload needs, how storage and failures behave in the chosen environment, and whether the team can meet its recovery goals. Microsoft cites control over PostgreSQL configuration, extensions, and architecture as reasons to run PostgreSQL on AKS in its AKS deployment guide. That is a provider-specific example, not a general recommendation for every team.
| Decision area | Database inside Kubernetes | Database outside Kubernetes |
|---|---|---|
| Operational ownership | The team operates the database and cluster integration. An operator can automate declared lifecycle procedures, but database and Kubernetes expertise are still needed. | Ownership depends on the external service and support arrangement; establish who handles upgrades, failover, monitoring, backup, and restore. |
| Configuration and topology | Offers direct control over deployment architecture and integration, with corresponding responsibility for operating those choices. | Configuration and topology depend on the external database service. Check that its capabilities fit the application. |
| Storage and failure behavior | Depends on the selected storage class, CSI provider, cluster topology, and database workload. Validate the actual combination. | Depends on the external service’s storage and failure design. Evaluate its documented guarantees for your requirements. |
| Application connectivity | Can use Kubernetes services that route connections according to database role; CloudNativePG and the GKE example document role-specific endpoints. | Requires network reachability and connection configuration between the cluster and the external database. |
| Cost and performance | No general cost or performance advantage is established; measure against your workload and operating assumptions. | No general cost or performance advantage is established; compare using equivalent workload and service assumptions. |
Choose in-cluster when the control and integration are valuable and the team can own the operational work. Prefer an external service when that better fits the organization’s support model or operational capacity. In either case, set recovery objectives and validate them rather than assuming a replica count or product label guarantees a particular outcome.
What an operator does—and what it does not
A database operator watches Kubernetes resources and applies database-specific procedures to the desired state. In CloudNativePG’s model, PostgreSQL streaming replication and Kubernetes API integration support primary and standby roles, while services provide connection paths that can follow role changes. The CloudNativePG architecture documentation explains the distinction between PostgreSQL’s application-level replication and Kubernetes orchestration.
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Plan the deployment in this order
- Choose the database and operating model. Decide whether the team has the Kubernetes and database skills to own an in-cluster deployment. For PostgreSQL, CloudNativePG is one option, not the only suitable operator. Review the project overview and the documentation for the version you intend to run.
- Define topology and failure domains. Choose the number of instances and their placement based on availability requirements, zone design, and available resource capacity. The Google Cloud GKE tutorial and the Microsoft AKS guide show multi-zone examples, but their configurations are specific to those provider environments.
- Select and validate persistent storage. Check durability, attachment and recovery behavior, throughput, latency, capacity expansion, and scheduling constraints for the chosen storage class and CSI provider. CloudNativePG’s storage guidance recommends benchmarking in a controlled Kubernetes environment before production. Its guidance also warns that pre-provisioned volumes can affect the operator’s high-availability and self-healing behavior; verify the advice for your operator version and storage provider.
- Set up connections and security. Decide how applications will connect, how credentials will be managed, and how connections will be encrypted. CloudNativePG can provide services for client connections, while the GKE tutorial demonstrates services and TLS-related resources. Adapt examples to your security model rather than carrying sample secrets into production.
- Define backup and recovery. Specify recovery point and recovery time objectives, backup location, retention, and the people and procedures needed to restore. CloudNativePG documents object-store backups and point-in-time recovery; the GKE tutorial and AKS guide show provider-specific object-storage examples. Keep backups independent of the primary database storage so they remain a recovery path if that storage is unavailable.
- Exercise failover and restore. Verify how clients behave when the primary changes, and perform a restore from backup in a suitable test environment. Documentation describing a capability is not evidence that a particular deployment has met its recovery objectives.
- Add monitoring and manage change. Establish visibility into database health, replication, storage, and backup activity. The GKE tutorial includes a Prometheus exporter path and an example of rolling minor PostgreSQL updates. Treat upgrade procedures and compatibility as version-specific, and plan how you will evaluate and apply changes.
Storage choices can change the failure story
A PVC is a request for storage, not a complete durability or performance design. The database’s behavior depends on the volume implementation, its availability and attachment characteristics, and how those fit the database workload and cluster topology. Benchmark the actual combination under controlled conditions before production; CloudNativePG’s storage recommendations specifically call for this validation.
Provider examples should not be transplanted blindly. The GKE tutorial recommends its premium-rwo storage class, using SSD-backed disks, for its own design. That is a GKE-specific recommendation, not a Kubernetes-wide requirement.
The AKS guide distinguishes local ephemeral disks from persistent cloud storage: data on a local ephemeral disk can be lost when the hosting VM or node is stopped or deallocated. Its example uses periodic Azure Blob Storage backups as another recovery route. This describes that AKS scenario; it is not a universal statement about every local disk or CSI driver. Make sure the selected storage and backup design cover the failures relevant to your environment.
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Replicas improve availability; backups enable recovery
Replicas can help a database remain available when an instance fails, and a database-aware operator can coordinate primary and standby roles. They are not independent backups. A replication setup can propagate unwanted changes, and a replica does not by itself provide a separate restore point or a tested restore procedure.
Best Value
Keep the failure cases distinct when designing recovery:
- Instance or node failure: Determine whether another instance can become primary and whether applications will reconnect through the service endpoint.
- Storage or cluster failure: Confirm whether the surviving replicas and storage are in independent failure domains, and whether the backup remains reachable if the cluster is unavailable.
- Logical error or unwanted change: Identify the backup and point-in-time recovery path that can return the database to an earlier state.
- Recovery validation: Record when a restore was last exercised, what it recovered, and how long the procedure took; do not claim an achieved recovery objective without deployment-specific evidence.
CloudNativePG documents continuous backup and point-in-time recovery, while the AKS example stores backups in Azure Blob Storage. These are documented capabilities and examples, not proof of a particular installation’s recovery results. Do not promise zero downtime, zero data loss, or a specific recovery point or recovery time without measurements and tests for the deployment.
What to decide before production
- Who owns PostgreSQL operations, Kubernetes operations, and incident response?
- Which database and operator versions will be deployed, and how will upgrades be reviewed and applied?
- What storage class and failure behavior have been validated against the workload?
- How are instances placed across the failure domains that matter in this environment?
- Where are backups stored, what is retained, and can the team restore if the cluster or primary storage is unavailable?
- Have failover and restore procedures been exercised, with results documented against the required recovery objectives?
- How will applications obtain credentials and connect securely to the appropriate database service?
For teams that want vendor-backed support for CloudNativePG, EnterpriseDB maintains supported CloudNativePG documentation. Assess support scope and availability directly with the provider; an operator choice does not itself settle the organization’s support needs.
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