Storage ======= .. raw:: html Storage is the most critical component in a database workload. Storage must always be available, scale, perform well, and guarantee consistency and durability. The same expectations and requirements that apply to traditional environments, such as virtual machines and bare metal, are also valid in container contexts managed by Kubernetes. .. Note:: When it comes to dynamically provisioned storage, Kubernetes has its own specifics. These include *storage classes*, *persistent volumes*, and *Persistent Volume Claims (PVCs)*. You need to own these concepts, on top of all the valuable knowledge you've built over the years in terms of storage for database workloads on VMs and physical servers. 　 There are two primary methods of access to storage: - **Network** – Either directly or indirectly. (Think of an NFS volume locally mounted on a host running Kubernetes.) - **Local** – Directly attached to the node where a pod is running. This also includes directly attached disks on bare metal installations of Kubernetes. Network storage, which is the most common usage pattern in Kubernetes, presents the same issues of throughput and latency that you can experience in a traditional environment. These issues can be accentuated in a shared environment, where I/O contention with several applications increases the variability of performance results. Local storage enables shared-nothing architectures, which is more suitable for high transactional and very large database (VLDB) workloads, as it guarantees higher and more predictable performance. .. Warning:: Before you deploy a PostgreSQL cluster with CloudNativePG, ensure that the storage you're using is recommended for database workloads. We recommend clearly setting performance expectations by first benchmarking the storage using tools such as `fio `_ and then the database using `pgbench `_ . 　 .. Note:: CloudNativePG doesn't use `StatefulSet` for managing data persistence. Rather, it manages PVCs directly. If you want to know more, see :ref:`Custom Pod Controller ` . 　 Backup and recovery ------------------- Since CloudNativePG supports volume snapshots for both backup and recovery, we recommend that you also consider this aspect when you choose your storage solution, especially if you manage very large databases. .. Note:: See the Kubernetes documentation for a list of all the supported `container storage interface (CSI) drivers `_ that provide snapshot capabilities. 　 Benchmarking CloudNativePG -------------------------- Before deploying the database in production, we recommend that you benchmark CloudNativePG in a controlled Kubernetes environment. Follow the guidelines in :ref:`Benchmarking ` . Briefly, we recommend operating at two levels: - Measuring the performance of the underlying storage using fio, with relevant metrics for database workloads such as throughput for sequential reads, sequential writes, random reads, and random writes - Measuring the performance of the database using pgbench, the default benchmarking tool distributed with PostgreSQL .. Note:: You must measure both the storage and database performance before putting the database into production. These results are extremely valuable not just in the planning phase (for example, capacity planning). They are also valuable in the production lifecycle, particularly in emergency situations when you don't have time to run this kind of test. Databases change and evolve over time, and so does the distribution of data, potentially affecting performance. Knowing the theoretical maximum throughput of sequential reads or writes is extremely useful in those situations. This is true especially in shared-nothing contexts, where results don't vary due to the influence of external workloads. Know your system: benchmark it. 　 Encryption at rest ------------------ Encryption at rest is possible with CloudNativePG. The operator delegates that to the underlying storage class. See the storage class for information about this important security feature. Persistent Volume Claim (PVC) ----------------------------- The operator creates a PVC for each PostgreSQL instance, with the goal of storing the ``PGDATA`` . It then mounts it into each pod. Additionally, it supports creating clusters with: - A separate PVC on which to store PostgreSQL WAL, as explained in :ref:`Volume for WAL ` - Additional separate volumes reserved for PostgreSQL tablespaces, as explained in :ref:`TablespaceState ` In CloudNativePG, the volumes attached to a single PostgreSQL instance are defined as a *PVC group*. Configuration via a storage class --------------------------------- .. Note:: CloudNativePG was designed to work interchangeably with all storage classes. As usual, we recommend properly benchmarking the storage class in a controlled environment before deploying to production. 　 The easiest way to configure the storage for a PostgreSQL class is to request storage of a certain size, like in the following example: .. code:: yaml apiVersion: postgresql.cnpg.io/v1 kind: Cluster metadata: name: postgresql-storage-class spec: instances: 3 storage: size: 1Gi Using the previous configuration, the generated PVCs are satisfied by the default storage class. If the target Kubernetes cluster has no default storage class, or even if you need your PVCs to be satisfied by a known storage class, you can set it into the custom resource: .. code:: yaml apiVersion: postgresql.cnpg.io/v1 kind: Cluster metadata: name: postgresql-storage-class spec: instances: 3 storage: storageClass: standard size: 1Gi Configuration via a PVC template -------------------------------- To further customize the generated PVCs, you can provide a PVC template inside the custom resource, like in the following example: .. code:: yaml apiVersion: postgresql.cnpg.io/v1 kind: Cluster metadata: name: postgresql-pvc-template spec: instances: 3 storage: pvcTemplate: accessModes: - ReadWriteOnce resources: requests: storage: 1Gi storageClassName: standard volumeMode: Filesystem Volume for WAL -------------- By default, PostgreSQL stores all its data in the so-called ``PGDATA`` (a directory). One of the core directories inside ``PGDATA`` is ``pg_wal`` , which contains the log of transactional changes that occurred in the database, in the form of segment files. (``pg_wal`` is historically known as ``pg_xlog`` in PostgreSQL.) .. Note:: Normally, each segment is 16MB in size, but you can configure the size using the `walSegmentSize` option. This option is applied at cluster initialization time, as described in :ref:`Bootstrap an empty cluster (`initdb` ) ` . 　 In most cases, having ``pg_wal`` on the same volume where ``PGDATA`` resides is fine. However, having WALs stored in a separate volume has a few benefits: - **I/O performance** – By storing WAL files on different storage from ``PGDATA`` , PostgreSQL can exploit parallel I/O for WAL operations (normally sequential writes) and for data files (tables and indexes for example), thus improving vertical scalability. - **More reliability** – By reserving dedicated disk space to WAL files, you can be sure that exhausting space on the ``PGDATA`` volume never interferes with WAL writing. This behavior ensures that your PostgreSQL primary is correctly shut down. - **Finer control** – You can define the amount of space dedicated to both ``PGDATA`` and ``pg_wal`` , fine tune `WAL configuration `_ and checkpoints, and even use a different storage class for cost optimization. - **Better I/O monitoring** – You can constantly monitor the load and disk usage on both ``PGDATA`` and ``pg_wal`` . You can also set alerts that notify you in case, for example, ``PGDATA`` requires resizing. .. Note:: See `Reliability and the Write-Ahead Log `_ in the PostgreSQL documentation for more information. 　 You can add a separate volume for WAL using the ``.spec.walStorage`` option. It follows the same rules described for the ``storage`` field and provisions a dedicated PVC. For example: .. code:: yaml apiVersion: postgresql.cnpg.io/v1 kind: Cluster metadata: name: separate-pgwal-volume spec: instances: 3 storage: size: 1Gi walStorage: size: 1Gi .. Note:: Removing `walStorage` isn't supported. Once added, a separate volume for WALs can't be removed from an existing Postgres cluster. 　 Volumes for tablespaces ----------------------- CloudNativePG supports declarative tablespaces. You can add one or more volumes, each dedicated to a single PostgreSQL tablespace. See :ref:`TablespaceState ` for details. Volume expansion ---------------- Kubernetes exposes an API allowing `expanding PVCs `_ that’s enabled by default. However, it needs to be supported by the underlying ``StorageClass`` . To check if a certain ``StorageClass`` supports volume expansion, you can read the ``allowVolumeExpansion`` field for your storage class: :: $ kubectl get storageclass -o jsonpath={$.allowVolumeExpansion} premium-storage true Using the volume expansion Kubernetes feature ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Given the storage class supports volume expansion, you can change the size requirement of the ``Cluster`` , and the operator applies the change to every PVC. If the ``StorageClass`` supports `online volume resizing `_ , the change is immediately applied to the pods. If the underlying storage class doesn’t support that, you must delete the pod to trigger the resize. The best way to proceed is to delete one pod at a time, starting from replicas and waiting for each pod to be back up. Re-creating storage ^^^^^^^^^^^^^^^^^^^ If the storage class doesn’t support volume expansion, you can still regenerate your cluster on different PVCs. Allocate new PVCs with increased storage and then move the database there. This operation is feasible only when the cluster contains more than one node. While you do that, you need to prevent the operator from changing the existing PVC by disabling the ``resizeInUseVolumes`` flag, like in the following example: .. code:: yaml apiVersion: postgresql.cnpg.io/v1 kind: Cluster metadata: name: postgresql-pvc-template spec: instances: 3 storage: storageClass: standard size: 1Gi resizeInUseVolumes: False To move the entire cluster to a different storage area, you need to re-create all the PVCs and all the pods. Suppose you have a cluster with three replicas, like in the following example: :: $ kubectl get pods NAME READY STATUS RESTARTS AGE cluster-example-1 1/1 Running 0 2m37s cluster-example-2 1/1 Running 0 2m22s cluster-example-3 1/1 Running 0 2m10s To re-create the cluster using different PVCs, you can edit the cluster definition to disable ``resizeInUseVolumes`` . Then re-create every instance in a different PVC. For example, re-create the storage for ``cluster-example-3`` : :: $ kubectl delete pvc/cluster-example-3 pod/cluster-example-3 .. Note:: If you created a dedicated WAL volume, both PVCs must be deleted during this process. The same procedure applies if you want to regenerate the WAL volume PVC. You can do this by also disabling `resizeInUseVolumes` for the `.spec.walStorage` section. 　 For example, if a PVC dedicated to WAL storage is present: :: $ kubectl delete pvc/cluster-example-3 pvc/cluster-example-3-wal pod/cluster-example-3 Having done that, the operator orchestrates creating another replica with a resized PVC: :: $ kubectl get pods NAME READY STATUS RESTARTS AGE cluster-example-1 1/1 Running 0 5m58s cluster-example-2 1/1 Running 0 5m43s cluster-example-4-join-v2 0/1 Completed 0 17s cluster-example-4 1/1 Running 0 10s Static provisioning of persistent volumes ----------------------------------------- CloudNativePG was designed to work with dynamic volume provisioning. This capability allows storage volumes to be created on demand when requested by users by way of storage classes and PVC templates. See :ref:`Re-creating storage ` . However, in some cases, Kubernetes administrators prefer to manually create storage volumes and then create the related ``PersistentVolume`` objects for their representation inside the Kubernetes cluster. This is also known as *pre-provisioning* of volumes. .. Note:: We recommend that you avoid pre-provisioning volumes, as it has an effect on the high availability and self-healing capabilities of the operator. It breaks the fully declarative model on which CloudNativePG was built. 　 To use a pre-provisioned volume in CloudNativePG: 1. Manually create the volume outside Kubernetes. 2. Create the ``PersistentVolume`` object to match this volume using the correct parameters as required by the actual CSI driver (that is, ``volumeHandle`` , ``fsType`` , ``storageClassName`` , and so on). 3. Create the Postgres ``Cluster`` using, for each storage section, a coherent :ref:`pvcTemplate ` section that can help Kubernetes match the ``PersistentVolume`` and enable CloudNativePG to create the needed ``PersistentVolumeClaim`` . .. Warning:: With static provisioning, it's your responsibility to ensure that Postgres pods can be correctly scheduled by Kubernetes where a pre-provisioned volume exists. (The scheduling configuration is based on the affinity rules of your cluster.) Make sure you check for any pods stuck in `Pending` after you deploy the cluster. If the condition persists, investigate why it's happening. 　 Block storage considerations (Ceph/Longhorn) -------------------------------------------- Most block storage solutions in Kubernetes, such as Longhorn and Ceph, recommend having multiple replicas of a volume to enhance resiliency. This approach works well for workloads that lack built-in resiliency. However, CloudNativePG integrates this resiliency directly into the Postgres ``Cluster`` through the number of instances and the persistent volumes attached to them, as explained in :ref:`Synchronizing the state ` . As a result, defining additional replicas at the storage level can lead to write amplification, unnecessarily increasing disk I/O and space usage. For CloudNativePG usage, consider reducing the number of replicas at the block storage level to one, while ensuring that no single point of failure (SPoF) exists at the storage level for the entire ``Cluster`` resource. This typically means ensuring that a single storage host—and ultimately, a physical disk—does not host blocks from different instances of the same ``Cluster`` , in alignment with the broader *shared-nothing architecture* principle. In Longhorn, you can mitigate this risk by enabling strict-local data locality when creating a custom storage class. Detailed instructions for creating a volume with strict-local data locality are available `here `_ . This setting ensures that a pod’s data volume resides on the same node as the pod itself. Additionally, your Postgres ``Cluster`` should have :ref:`pod anti-affinity rules ` in place to ensure that the operator deploys pods across different nodes, allowing Longhorn to place the data volumes on the corresponding hosts. If needed, you can manually relocate volumes in Longhorn by temporarily setting the volume replica count to 2, reducing it afterward, and then removing the old replica. If a host becomes corrupted, you can use the :ref:`postgresql.cnpg.io/v1 ` the affected instance. CloudNativePG will then recreate the instance on another host and replicate the data. In Ceph, this can be configured through CRUSH rules. The documentation for configuring CRUSH rules is available `here `_ . These rules aim to ensure one volume per pod per node. You can also relocate volumes by importing them into a different pool.