Operator capability levels ========================== .. raw:: html These capabilities were implemented by CloudNativePG, classified using the `Operator SDK definition of Capability Levels `_ framework. .. figure:: /images/operator-capability-level.png :width: 70% :alt: Operator Capability Levels Operator Capability Levels .. Note:: Based on the :ref:`Operator Capability Levels model ` , you can expect a "Level V - Auto Pilot" set of capabilities from the CloudNativePG operator. 　 Each capability level is associated with a certain set of management features the operator offers: 1. Basic install 2. Seamless upgrades 3. Full lifecycle 4. Deep insights 5. Auto pilot .. Note:: We consider this framework as a guide for future work and implementations in the operator. 　 Level 1: Basic install ---------------------- Capability level 1 involves installing and configuring the operator. This category includes usability and user experience enhancements, such as improvements in how you interact with the operator and a PostgreSQL cluster configuration. .. Note:: We consider information security part of this level. 　 Operator deployment via declarative configuration ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator is installed in a declarative way using a Kubernetes manifest that defines four major ``CustomResourceDefinition`` objects: ``Cluster`` , ``Pooler`` , ``Backup`` , and ``ScheduledBackup`` . PostgreSQL cluster deployment via declarative configuration ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ You define a PostgreSQL cluster (operand) using the ``Cluster`` custom resource in a fully declarative way. The PostgreSQL version is determined by the operand container image defined in the CR, which is automatically fetched from the requested registry. When deploying an operand, the operator also creates the following resources: ``Pod`` , ``Service`` , ``Secret`` , ``ConfigMap`` ,\ ``PersistentVolumeClaim`` , ``PodDisruptionBudget`` , ``ServiceAccount`` , ``RoleBinding`` , and ``Role`` . Override of operand images through the CRD ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator is designed to support any operand container image with PostgreSQL inside. By default, the operator uses the latest available minor version of the latest stable major version supported by the PostgreSQL community and published on ghcr.io. You can use any compatible image of PostgreSQL supporting the primary/standby architecture directly by setting the ``imageName`` attribute in the CR. The operator also supports ``imagePullSecrets`` to access private container registries, and it supports digests and tags for finer control of container image immutability. If you prefer not to specify an image name, you can leverage :ref:`image catalogs ` by simply referencing the PostgreSQL major version. Moreover, image catalogs enable you to effortlessly create custom catalogs, directing to images based on your specific requirements. Labels and annotations ^^^^^^^^^^^^^^^^^^^^^^ You can configure the operator to support inheriting labels and annotations that are defined in a cluster’s metadata. The goal is to improve the organization of the CloudNativePG deployment in your Kubernetes infrastructure. Self-contained instance manager ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Instead of relying on an external tool to coordinate PostgreSQL instances in the Kubernetes cluster pods, such as Patroni or Stolon, the operator injects the operator executable inside each pod, in a file named ``/controller/manager`` . The application is used to control the underlying PostgreSQL instance and to reconcile the pod status with the instance based on the PostgreSQL cluster topology. The instance manager also starts a web server that’s invoked by the ``kubelet`` for probes. Unix signals invoked by the ``kubelet`` are filtered by the instance manager. Where appropriate, they’re forwarded to the ``postgres`` process for fast and controlled reactions to external events. The instance manager is written in Go and has no external dependencies. Storage configuration ^^^^^^^^^^^^^^^^^^^^^ Storage is a critical component in a database workload. Taking advantage of the Kubernetes native capabilities and resources in terms of storage, the operator gives you enough flexibility to choose the right storage for your workload requirements, based on what the underlying Kubernetes environment can offer. This implies choosing a particular storage class in a public cloud environment or fine-tuning the generated PVC through a PVC template in the CR’s ``storage`` parameter. For better performance and finer control, you can also choose to host your cluster’s write-ahead log (WAL, also known as ``pg_wal`` ) on a separate volume, preferably on different storage. The :ref:`Benchmarking ` section of the documentation provides detailed instructions on benchmarking both storage and the database before production. It relies on the ``cnpg`` plugin to ensure optimal performance and reliability. Replica configuration ^^^^^^^^^^^^^^^^^^^^^ The operator detects replicas in a cluster through a single parameter, called ``instances`` . If set to ``1`` , the cluster comprises a single primary PostgreSQL instance with no replica. If higher than ``1`` , the operator manages ``instances -1`` replicas, including high availability (HA) through automated failover and rolling updates through switchover operations. CloudNativePG manages replication slots for all replicas in the high-availability cluster. It also supports user-defined physical replication slots on the primary and enables logical decoding failover—natively for PostgreSQL 17 and later using ``sync_replication_slots`` , and through the ``pg_failover_slots`` extension for earlier versions. Service Configuration ^^^^^^^^^^^^^^^^^^^^^ By default, CloudNativePG creates three Kubernetes :ref:`ManagedServices ` for applications to access the cluster via the network: - One pointing to the primary for read/write operations. - One pointing to replicas for read-only queries. - A generic one pointing to any instance for read operations. You can disable the read-only and read services via configuration. Additionally, you can leverage the service template capability to create custom service resources, including load balancers, to access PostgreSQL outside Kubernetes. This is particularly useful for DBaaS purposes. Database configuration ^^^^^^^^^^^^^^^^^^^^^^ The operator is designed to bootstrap a PostgreSQL cluster with a single database. The operator transparently manages network access to the cluster through three Kubernetes services provisioned and managed for read-write, read, and read-only workloads. Using the convention-over-configuration approach, the operator creates a database called ``app`` , by default owned by a regular Postgres user with the same name. You can specify both the database name and the user name, if required, as part of the bootstrap. Additional databases can be created or managed via :ref:`declarative database management ` using the ``Database`` CRD, also supporting extensions, schemas, foreign data wrappers (FDW), and foreign servers. Although no configuration is required to run the cluster, you can customize both PostgreSQL runtime configuration and PostgreSQL host-based authentication rules in the ``postgresql`` section of the CR. Configuration of Postgres roles, users, and groups ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ CloudNativePG supports :ref:`management of PostgreSQL roles, users, and groups through declarative configuration ` using the ``.spec.managed.roles`` stanza. Pod security standards ^^^^^^^^^^^^^^^^^^^^^^ For InfoSec requirements, the operator doesn’t require privileged mode for any container. It enforces a read-only root filesystem to guarantee containers immutability for both the operator and the operand pods. It also explicitly sets the required security contexts. Affinity ^^^^^^^^ The cluster’s ``affinity`` section enables fine-tuning of how pods and related resources, such as persistent volumes, are scheduled across the nodes of a Kubernetes cluster. In particular, the operator supports: - Pod affinity and anti-affinity - Node selector - Taints and tolerations Topology spread constraints ^^^^^^^^^^^^^^^^^^^^^^^^^^^ The cluster’s ``topologySpreadConstraints`` section enables additional control of scheduling pods across topologies, enhancing what affinity and anti-affinity can offer. Command-line interface ^^^^^^^^^^^^^^^^^^^^^^ CloudNativePG doesn’t have its own command-line interface. It relies on the best command-line interface for Kubernetes, kubectl, by providing a plugin called ``cnpg`` . This plugin enhances and simplifies your PostgreSQL cluster management experience. Current status of the cluster ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator continuously updates the status section of the CR with the observed status of the cluster. The entire PostgreSQL cluster status is continuously monitored by the instance manager running in each pod. The instance manager is responsible for applying the required changes to the controlled PostgreSQL instance to converge to the required status of the cluster. (For example, if the cluster status reports that pod ``-1`` is the primary, pod ``-1`` needs to promote itself while the other pods need to follow pod ``-1`` .) The same status is used by the ``cnpg`` plugin for kubectl to provide details. Operator’s certification authority ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator creates a certification authority for itself. It creates and signs with the operator certification authority a leaf certificate for the webhook server to use. This certificate ensures safe communication between the Kubernetes API server and the operator. Cluster’s certification authority ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator creates a certification authority for every PostgreSQL cluster. This certification authority is used to issue and renew TLS certificates for clients’ authentication, including streaming replication standby servers (instead of passwords). Support for a custom certification authority for client certificates is available through secrets, which also includes integration with cert-manager. Certificates can be issued with the ``cnpg`` plugin for kubectl. TLS connections ^^^^^^^^^^^^^^^ The operator transparently and natively supports TLS/SSL connections to encrypt client/server communications for increased security using the cluster’s certification authority. Support for custom server certificates is available through secrets, which also includes integration with cert-manager. Certificate authentication for streaming replication ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ To authorize streaming replication connections from the standby servers, the operator relies on TLS client certificate authentication. This method is used instead of relying on a password (and therefore a secret). Continuous configuration management ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator enables you to apply changes to the ``Cluster`` resource YAML section of the PostgreSQL configuration. Depending on the configuration option, it also makes sure that all instances are properly reloaded or restarted. .. Note:: Changes with `ALTER SYSTEM` aren't detected, meaning that the cluster state isn't enforced. 　 Import of existing PostgreSQL databases ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator provides a declarative way to import existing Postgres databases in a new CloudNativePG cluster in Kubernetes, using offline migrations. The same feature also covers offline major upgrades of PostgreSQL databases. Offline means that applications must stop their write operations at the source until the database is imported. The feature extends the ``initdb`` bootstrap method to create a new PostgreSQL cluster using a logical snapshot of the data available in another PostgreSQL database. This data can be accessed by way of the network through a superuser connection. Import is from any supported version of Postgres. It relies on ``pg_dump`` and ``pg_restore`` being executed from the new cluster primary for all databases that are part of the operation and, if requested, for roles. PostGIS clusters ^^^^^^^^^^^^^^^^ CloudNativePG supports the installation of clusters with the :ref:`PostGIS clusters ` open source extension for geographical databases. This extension is one of the most popular extensions for PostgreSQL. Basic LDAP authentication for PostgreSQL ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator allows you to configure LDAP authentication for your PostgreSQL clients, using either the *simple bind* or *search+bind* mode, as described in the `LDAP authentication section of the PostgreSQL documentation `_ . Multiple installation methods ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator can be installed through a Kubernetes manifest by way of ``kubectl apply`` , to be used in a traditional Kubernetes installation in public and private cloud environments. CloudNativePG also supports installation by way of a Helm chart or OLM bundle from OperatorHub.io. Convention over configuration ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator supports the convention-over-configuration paradigm, deciding standard default values while allowing you to override them and customize them. You can specify a deployment of a PostgreSQL cluster using the ``Cluster`` CRD in a couple of lines of YAML code. Level 2: Seamless upgrades -------------------------- Capability level 2 is about enabling updates of the operator and the actual workload, in this case PostgreSQL servers. This includes PostgreSQL minor release updates (security and bug fixes normally) as well as major online upgrades. Operator Upgrade ^^^^^^^^^^^^^^^^ Upgrading the operator is seamless and can be done as a new deployment. After upgrading the controller, a rolling update of all deployed PostgreSQL clusters is initiated. You can choose to update all clusters simultaneously or distribute their upgrades over time. Thanks to the instance manager’s injection, upgrading the operator does not require changes to the operand, allowing the operator to manage older versions of it. Additionally, CloudNativePG supports :ref:`In-place updates of the instance manager ` following an operator upgrade. In-place updates do not require a rolling update or a subsequent switchover of the cluster. Upgrade of the managed workload ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operand can be upgraded using a declarative configuration approach as part of changing the CR and, in particular, the ``imageName`` parameter. This is normally initiated by security updates or Postgres minor version updates. In the presence of standby servers, the operator performs rolling updates starting from the replicas. It does this by dropping the existing pod and creating a new one with the new requested operand image that reuses the underlying storage. Depending on the value of the ``primaryUpdateStrategy`` , the operator proceeds with a switchover before updating the former primary (``unsupervised`` ). Or, it waits for the user to manually issue the switchover procedure (``supervised`` ) by way of the ``cnpg`` plugin for kubectl. The setting to use depends on the business requirements, as the operation might generate some downtime for the applications. This downtime can range from a few seconds to minutes, based on the actual database workload. Offline In-Place Major Upgrades of PostgreSQL ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ CloudNativePG supports declarative offline in-place major upgrades when a new operand container image with a higher PostgreSQL major version is applied to a cluster. The upgrade can be triggered by updating the image tag via the ``.spec.imageName`` option or by using an image catalog to manage version changes. During the upgrade, all cluster pods are shut down to ensure data consistency. A new job is then created to validate the upgrade conditions, execute ``pg_upgrade`` , and create new directories for ``PGDATA`` , WAL files, and tablespaces if needed. Once the upgrade is complete, replicas are re-created. Failed upgrades can be rolled back. Display cluster availability status during upgrade ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ At any time, convey the cluster’s high availability status, for example, ``Setting up primary`` , ``Creating a new replica`` , ``Cluster in healthy state`` , ``Switchover in progress`` , ``Failing over`` , ``Upgrading cluster`` , and ``Upgrading Postgres major version`` . Level 3: Full lifecycle ----------------------- Capability level 3 requires the operator to manage aspects of business continuity and scalability. - Disaster recovery\* is a business continuity component that requires that both backup and recovery of a database work correctly. While as a starting point, the goal is to achieve :ref:`PgBouncerPoolMode ` < 5 minutes, the long-term goal is to implement RPO=0 backup solutions. *High availability* is the other important component of business continuity. Through PostgreSQL native physical replication and hot standby replicas, it allows the operator to perform failover and switchover operations. This area includes enhancements in: - Control of PostgreSQL physical replication, such as synchronous replication, (cascading) replication clusters, and so on - Connection pooling, to improve performance and control through a connection pooling layer with pgBouncer PostgreSQL WAL archive ^^^^^^^^^^^^^^^^^^^^^^ The operator supports PostgreSQL continuous archiving of WAL files to an object store (AWS S3 and S3-compatible, Azure Blob Storage, Google Cloud Storage, and gateways like MinIO). WAL archiving is defined at the cluster level, declaratively, through the ``backup`` parameter in the cluster definition. This is done by specifying an S3 protocol destination URL (for example, to point to a specific folder in an AWS S3 bucket) and, optionally, a generic endpoint URL. WAL archiving, a prerequisite for continuous backup, doesn’t require any further user action. The operator transparently sets the ``archive_command`` to rely on ``barman-cloud-wal-archive`` to ship WAL files to the defined endpoint. You can decide the compression algorithm, as well as the number of parallel jobs to concurrently upload WAL files in the archive. In addition, ``Instance Manager`` checks the correctness of the archive destination by performing the ``barman-cloud-check-wal-archive`` command before beginning to ship the first set of WAL files. PostgreSQL Backups ^^^^^^^^^^^^^^^^^^ CloudNativePG provides a pluggable interface (CNPG-I) for managing application-level backups using PostgreSQL’s native physical backup mechanisms—namely base backups and continuous WAL archiving. This design enables flexibility and extensibility while ensuring consistency and performance. The CloudNativePG Community officially supports the `Barman Cloud Plugin `_ , which enables continuous physical backups to object stores, along with full and Point-In-Time Recovery (PITR) capabilities. In addition to CNPG-I plugins, CloudNativePG also natively supports backups using Kubernetes volume snapshots, when supported by the underlying storage class and CSI driver. You can initiate base backups in two ways: - On-demand, using the ``Backup`` custom resource - Scheduled, using the ``ScheduledBackup`` custom resource, with a cron-like schedule format Volume snapshots leverage the Kubernetes API and are particularly effective for very large databases (VLDBs) due to their speed and storage efficiency. Both volume snapshots and CNPG-I-based backups support: - Hot backups: Taken while PostgreSQL is running, ensuring minimal disruption. - Cold backups: Performed by temporarily stopping PostgreSQL to ensure a fully consistent snapshot, when required. Backups from a standby ^^^^^^^^^^^^^^^^^^^^^^ The operator supports offloading base backups onto a standby without impacting the :ref:`PgBouncerPoolMode ` of the database. This allows resources to be preserved on the primary, in particular I/O, for standard database operations. Full restore from a backup ^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator enables you to bootstrap a new cluster (with its settings) starting from an existing and accessible backup, either on a volume snapshot, or in an object store, or via a plugin. Once the bootstrap process is completed, the operator initiates the instance in recovery mode. It replays all available WAL files from the specified archive, exiting recovery and starting as a primary. Subsequently, the operator clones the requested number of standby instances from the primary. CloudNativePG supports parallel WAL fetching from the archive. Point-in-time recovery (PITR) from a backup ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator enables you to create a new PostgreSQL cluster by recovering an existing backup to a specific point in time, defined with a timestamp, a label, or a transaction ID. This capability is built on top of the full restore one and supports all the options available in `PostgreSQL for PITR `_ . Zero-Data-Loss Clusters Through Synchronous Replication ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ CloudNativePG enables *zero-data-loss (RPO=0)* high-availability clusters by combining synchronous replication with optional :ref:`Failover Quorum (Quorum-based Failover) ` : you can define how many synchronous standby replicas must be available at any given time, ensuring that failover only proceeds when data is safely replicated. Both quorum-based and priority-based synchronous replication are supported, and the operator provides full flexibility in configuring the ``synchronous_standby_names`` setting to match your durability and performance requirements. Replica clusters ^^^^^^^^^^^^^^^^ Establish a robust cross-Kubernetes cluster topology for PostgreSQL clusters, harnessing the power of native streaming and cascading replication. With the ``replica`` option, you can configure an autonomous cluster to consistently replicate data from another PostgreSQL source of the same major version. This source can be located anywhere, provided you have access to a WAL archive for fetching WAL files or a direct streaming connection via TLS between the two endpoints. Notably, the source PostgreSQL instance can exist outside the Kubernetes environment, whether in a physical or virtual setting. Replica clusters can be instantiated through various methods, including volume snapshots, a recovery object store (using the Barman Cloud backup format), or streaming using ``pg_basebackup`` . Both WAL file shipping and WAL streaming are supported. The deployment of replica clusters significantly elevates the business continuity posture of PostgreSQL databases within Kubernetes, extending across multiple data centers and facilitating hybrid and multi-cloud setups. (While anticipating Kubernetes federation native capabilities, manual switchover across data centers remains necessary.) Additionally, the flexibility extends to creating delayed replica clusters intentionally lagging behind the primary cluster. This intentional lag aims to minimize the Recovery Time Objective ( :ref:`Backup Frequency and RTO ` ) in the event of unintended errors, such as incorrect ``DELETE`` or ``UPDATE`` SQL operations. Distributed Database Topologies ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Leverage replica clusters to define :ref:`Distributed Database Topologies ` for PostgreSQL that span across various Kubernetes clusters, facilitating hybrid and multi-cloud deployments. With CloudNativePG, you gain powerful capabilities, including: - **Declarative Primary Control**: Easily specify which PostgreSQL cluster acts as the primary. - **Seamless Primary Switchover**: Effortlessly demote the current primary and promote another PostgreSQL cluster, typically located in a different region, without needing to re-clone the former primary. This setup can efficiently operate across two or more regions, can rely entirely on object stores for replication, and guarantees a maximum RPO (Recovery Point Objective) of 5 minutes. This advanced feature is uniquely provided by CloudNativePG, ensuring robust data integrity and continuity across diverse environments. Tablespace support ^^^^^^^^^^^^^^^^^^ CloudNativePG seamlessly integrates robust support for PostgreSQL tablespaces by facilitating the declarative definition of individual persistent volumes. This innovative feature empowers you to efficiently distribute I/O operations across a diverse array of storage devices. Through the transparent orchestration of tablespaces, CloudNativePG enhances the performance and scalability of PostgreSQL databases, ensuring a streamlined and optimized experience for managing large scale data storage in cloud-native environments. Support for temporary tablespaces is also included. Customizable Startup, Liveness, and Readiness Probes ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ CloudNativePG configures startup, liveness, and readiness probes for PostgreSQL containers, which are managed by the Kubernetes kubelet. These probes interact with the ``/startupz`` , ``/healthz`` , and ``/readyz`` endpoints exposed by the instance manager’s web server to monitor the Pod’s health and readiness. All probes are configured with default settings but can be fully customized to meet specific needs, allowing for fine-tuning to align with your environment and workloads. For detailed configuration options and advanced usage, refer to the :ref:`Postgres Instance Manager ` documentation. Rolling deployments ^^^^^^^^^^^^^^^^^^^ The operator supports rolling deployments to minimize the downtime. If a PostgreSQL cluster is exposed publicly, the service load-balances the read-only traffic only to available pods during the initialization or the update. Scale up and down of replicas ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator allows you to scale up and down the number of instances in a PostgreSQL cluster. New replicas are started up from the primary server and participate in the cluster’s HA infrastructure. The CRD declares a “scale” subresource that allows you to use the ``kubectl scale`` command. Maintenance window and PodDisruptionBudget for Kubernetes nodes ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator creates a ``PodDisruptionBudget`` resource to limit the number of concurrent disruptions to one primary instance. This configuration prevents the maintenance operation from deleting all the pods in a cluster, allowing the specified number of instances to be created. The PodDisruptionBudget is applied during the node-draining operation, preventing any disruption of the cluster service. While this strategy is correct for Kubernetes clusters where storage is shared among all the worker nodes, it might not be the best solution for clusters using local storage or for clusters installed in a private cloud. The operator allows you to specify a maintenance window and configure the reaction to any underlying node eviction. The ``ReusePVC`` option in the maintenance window section enables to specify the strategy to use. Allocate new storage in a different PVC for the evicted instance, or wait for the underlying node to be available again. Fencing ^^^^^^^ Fencing is the process of protecting the data in one, more, or even all instances of a PostgreSQL cluster when they appear to be malfunctioning. When an instance is fenced, the PostgreSQL server process is guaranteed to be shut down, while the pod is kept running. This ensures that, until the fence is lifted, data on the pod isn’t modified by PostgreSQL and that you can investigate file system for debugging and troubleshooting purposes. Hibernation ^^^^^^^^^^^ CloudNativePG supports :ref:`hibernation of a running PostgreSQL cluster ` in a declarative manner, through the ``cnpg.io/hibernation`` annotation. Hibernation enables saving CPU power by removing the database pods while keeping the database PVCs. This feature simulates scaling to 0 instances. Reuse of persistent volumes storage in pods ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ When the operator needs to create a pod that was deleted by the user or was evicted by a Kubernetes maintenance operation, it reuses the ``PersistentVolumeClaim`` , if available. This ability avoids the need to clone the data from the primary again. CPU and memory requests and limits ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator allows administrators to control and manage resource usage by the cluster’s pods in the ``resources`` section of the manifest. In particular, you can set ``requests`` and ``limits`` values for both CPU and RAM. Connection pooling with PgBouncer ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ CloudNativePG provides native support for connection pooling with :ref:`PgBouncerIntegrationStatus ` , one of the most popular open source connection poolers for PostgreSQL. From an architectural point of view, the native implementation of a PgBouncer connection pooler introduces a new layer to access the database. This optimizes the query flow toward the instances and makes the use of the underlying PostgreSQL resources more efficient. Instead of connecting directly to a PostgreSQL service, applications can now connect to the PgBouncer service and start reusing any existing connection. Logical Replication ^^^^^^^^^^^^^^^^^^^ CloudNativePG supports PostgreSQL’s logical replication in a declarative manner using ``Publication`` and ``Subscription`` custom resource definitions. Logical replication is particularly useful together with the import facility for online data migrations (even from public DBaaS solutions) and major PostgreSQL upgrades. Level 4: Deep insights ---------------------- Capability level 4 is about *observability*: monitoring, alerting, trending, and log processing. This might involve the use of external tools, such as Prometheus, Grafana, and Fluent Bit, as well as extensions in the PostgreSQL engine for the output of error logs directly in JSON format. CloudNativePG was designed to provide everything needed to easily integrate with industry-standard and community-accepted tools for flexible monitoring and logging. Prometheus exporter with configurable queries ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The instance manager provides a pluggable framework. By way of its own web server listening on the ``metrics`` port (9187), it exposes an endpoint to export metrics for the `Prometheus `_ monitoring and alerting tool. The operator supports custom monitoring queries defined as ``ConfigMap`` or ``Secret`` objects using a syntax that’s compatible with `postgres_exporter `_ . CloudNativePG provides a set of basic monitoring queries for PostgreSQL that can be integrated and adapted to your context. Grafana dashboard ^^^^^^^^^^^^^^^^^ CloudNativePG comes with a Grafana dashboard that you can use as a base to monitor all critical aspects of a PostgreSQL cluster, and customize. Standard output logging of PostgreSQL error messages in JSON format ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Every log message is delivered to standard output in JSON format. The first level is the definition of the timestamp, the log level, and the type of log entry, such as ``postgres`` for the canonical PostgreSQL error message channel. As a result, every pod managed by CloudNativePG can be easily and directly integrated with any downstream log processing stack that supports JSON as source data type. Real-time query monitoring ^^^^^^^^^^^^^^^^^^^^^^^^^^ CloudNativePG transparently and natively supports: - The essential `pg_stat_statements `_ , which enables tracking of planning and execution statistics of all SQL statements executed by a PostgreSQL server - The `auto_explain `_ , which provides a means for logging execution plans of slow statements automatically, without having to manually run ``EXPLAIN`` (helpful for tracking down un-optimized queries) - The `pg_failover_slots `_ , which makes logical replication slots usable across a physical failover, ensuring resilience in change data capture (CDC) contexts based on PostgreSQL’s native logical replication Audit ^^^^^ CloudNativePG allows database and security administrators, auditors, and operators to track and analyze database activities using PGAudit for PostgreSQL. Such activities flow directly in the JSON log and can be properly routed to the correct downstream target using common log brokers like Fluentd. Kubernetes events ^^^^^^^^^^^^^^^^^ Record major events as expected by the Kubernetes API, such as creating resources, removing nodes, and upgrading. Events can be displayed by using the ``kubectl describe`` and ``kubectl get events`` commands. Level 5: Auto pilot ------------------- Capability level 5 is focused on automated scaling, healing, and tuning through the discovery of anomalies and insights that emerged from the observability layer. Automated failover for self-healing ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ In case of detected failure on the primary, the operator changes the status of the cluster by setting the most aligned replica as the new target primary. As a consequence, the instance manager in each alive pod initiates the required procedures to align itself with the requested status of the cluster. It does this by either becoming the new primary or by following it. In case the former primary comes back up, the same mechanism avoids a split-brain by preventing applications from reaching it, running ``pg_rewind`` on the server and restarting it as a standby. Automated recreation of a standby ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ If the pod hosting a standby is removed, the operator initiates the procedure to re-create a standby server.