Monitoring ========== .. Important:: Installing Prometheus and Grafana is beyond the scope of this project. We assume they are correctly installed in your system. However, for experimentation we provide instructions in :ref:`Part 4 of the Quickstart ` . Monitoring Instances -------------------- For each PostgreSQL instance, the operator provides an exporter of metrics for `Prometheus `_ via HTTP or HTTPS, on port 9187, named ``metrics`` . The operator comes with a :ref:`Predefined set of metrics ` , as well as a highly configurable and customizable system to define additional queries via one or more ``ConfigMap`` or ``Secret`` resources (see the :ref:`User defined metrics ` below for details). .. Important:: EDB CloudNativePG Cluster, by default, installs a set of :ref:`predefined metrics <#default-set-of-metrics>` in a ``ConfigMap`` named ``default-monitoring`` . .. Note:: You can inspect the exported metrics by following the instructions in the :ref:`How to inspect the exported metrics ` section below. All monitoring queries that are performed on PostgreSQL are: - atomic (one transaction per query) - executed with the ``pg_monitor`` role - executed with ``application_name`` set to ``cnp_metrics_exporter`` - executed as user ``postgres`` Please refer to the “Predefined Roles” section in PostgreSQL `documentation `_ for details on the ``pg_monitor`` role. Queries, by default, are run against the *main database*, as defined by the specified ``bootstrap`` method of the ``Cluster`` resource, according to the following logic: - using ``initdb`` : queries will be run by default against the specified database in ``initdb.database`` , or ``app`` if not specified - using ``recovery`` : queries will be run by default against the specified database in ``recovery.database`` , or ``postgres`` if not specified - using ``pg_basebackup`` : queries will be run by default against the specified database in ``pg_basebackup.database`` , or ``postgres`` if not specified The default database can always be overridden for a given user-defined metric, by specifying a list of one or more databases in the ``target_databases`` option. .. Seealso:: If you are interested in evaluating the integration of EDB CloudNativePG Cluster with Prometheus and Grafana, you can find a quick setup guide in :ref:`Part 4 of the quickstart ` Prometheus Operator example ^^^^^^^^^^^^^^^^^^^^^^^^^^^ A specific PostgreSQL cluster can be monitored using the `Prometheus Operator's `_ resource `PodMonitor `_ . A ``PodMonitor`` that correctly points to the Cluster can be automatically created by the operator by setting ``.spec.monitoring.enablePodMonitor`` to ``true`` in the Cluster resource itself (default: ``false`` ). .. Important:: Any change to the `PodMonitor` created automatically will be overridden by the Operator at the next reconciliation cycle, in case you need to customize it, you can do so as described below. To deploy a ``PodMonitor`` for a specific Cluster manually, define it as follows and adjust as needed: .. code:: yaml apiVersion: monitoring.coreos.com/v1 kind: PodMonitor metadata: name: cluster-example spec: selector: matchLabels: "k8s.enterprisedb.io/cluster": cluster-example podMetricsEndpoints: - port: metrics .. Important:: Ensure you modify the example above with a unique name, as well as the correct cluster's namespace and labels (e.g., `cluster-example` ). .. Important:: The `postgresql` label, used in previous versions of this document, is deprecated and will be removed in the future. Please use the `k8s.enterprisedb.io/cluster` label instead to select the instances. Enabling TLS on the Metrics Port ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ To enable TLS communication on the metrics port, configure the ``.spec.monitoring.tls.enabled`` setting to ``true`` . This setup ensures that the metrics exporter uses the same server certificate used by PostgreSQL to secure communication on port 5432. .. Important:: Changing the `.spec.monitoring.tls.enabled` setting will trigger a rolling restart of the Cluster. If the ``PodMonitor`` is managed by the operator (``.spec.monitoring.enablePodMonitor`` set to ``true`` ), it will automatically contain the necessary configurations to access the metrics via TLS. To manually deploy a ``PodMonitor`` suitable for reading metrics via TLS, define it as follows and adjust as needed: .. code:: yaml apiVersion: monitoring.coreos.com/v1 kind: PodMonitor metadata: name: cluster-example spec: selector: matchLabels: "k8s.enterprisedb.io/cluster": cluster-example podMetricsEndpoints: - port: metrics scheme: https tlsConfig: ca: secret: name: cluster-example-ca key: ca.crt serverName: cluster-example-rw .. Important:: Ensure you modify the example above with a unique name, as well as the correct Cluster's namespace and labels (e.g., `cluster-example` ). .. Important:: The `serverName` field in the metrics endpoint must match one of the names defined in the server certificate. If the default certificate is in use, the `serverName` value should be in the format `-rw` . Predefined set of metrics ^^^^^^^^^^^^^^^^^^^^^^^^^ Every PostgreSQL instance exporter automatically exposes a set of predefined metrics, which can be classified in two major categories: - PostgreSQL related metrics, starting with ``cnp_collector_*`` , including: - number of WAL files and total size on disk - number of ``.ready`` and ``.done`` files in the archive status folder - requested minimum and maximum number of synchronous replicas, as well as the expected and actually observed values - number of distinct nodes accommodating the instances - timestamps indicating last failed and last available backup, as well as the first point of recoverability for the cluster - flag indicating if replica cluster mode is enabled or disabled - flag indicating if a manual switchover is required - flag indicating if fencing is enabled or disabled - Go runtime related metrics, starting with ``go_*`` Below is a sample of the metrics returned by the ``localhost:9187/metrics`` endpoint of an instance. As you can see, the Prometheus format is self-documenting: .. code:: text # HELP cnp_collector_collection_duration_seconds Collection time duration in seconds # TYPE cnp_collector_collection_duration_seconds gauge cnp_collector_collection_duration_seconds{collector="Collect.up"} 0.0031393 # HELP cnp_collector_collections_total Total number of times PostgreSQL was accessed for metrics. # TYPE cnp_collector_collections_total counter cnp_collector_collections_total 2 # HELP cnp_collector_fencing_on 1 if the instance is fenced, 0 otherwise # TYPE cnp_collector_fencing_on gauge cnp_collector_fencing_on 0 # HELP cnp_collector_nodes_used NodesUsed represents the count of distinct nodes accommodating the instances. A value of -1 suggests that the metric is not available. A value of 1 suggests that all instances are hosted on a single node, implying the absence of High Availability (HA). Ideally this value should match the number of instances in the cluster. # TYPE cnp_collector_nodes_used gauge cnp_collector_nodes_used 3 # HELP cnp_collector_last_collection_error 1 if the last collection ended with error, 0 otherwise. # TYPE cnp_collector_last_collection_error gauge cnp_collector_last_collection_error 0 # HELP cnp_collector_manual_switchover_required 1 if a manual switchover is required, 0 otherwise # TYPE cnp_collector_manual_switchover_required gauge cnp_collector_manual_switchover_required 0 # HELP cnp_collector_pg_wal Total size in bytes of WAL segments in the /var/lib/postgresql/data/pgdata/pg_wal directory computed as (wal_segment_size * count) # TYPE cnp_collector_pg_wal gauge cnp_collector_pg_wal{value="count"} 9 cnp_collector_pg_wal{value="slots_max"} NaN cnp_collector_pg_wal{value="keep"} 32 cnp_collector_pg_wal{value="max"} 64 cnp_collector_pg_wal{value="min"} 5 cnp_collector_pg_wal{value="size"} 1.50994944e+08 cnp_collector_pg_wal{value="volume_max"} 128 cnp_collector_pg_wal{value="volume_size"} 2.147483648e+09 # HELP cnp_collector_pg_wal_archive_status Number of WAL segments in the /var/lib/postgresql/data/pgdata/pg_wal/archive_status directory (ready, done) # TYPE cnp_collector_pg_wal_archive_status gauge cnp_collector_pg_wal_archive_status{value="done"} 6 cnp_collector_pg_wal_archive_status{value="ready"} 0 # HELP cnp_collector_replica_mode 1 if the cluster is in replica mode, 0 otherwise # TYPE cnp_collector_replica_mode gauge cnp_collector_replica_mode 0 # HELP cnp_collector_sync_replicas Number of requested synchronous replicas (synchronous_standby_names) # TYPE cnp_collector_sync_replicas gauge cnp_collector_sync_replicas{value="expected"} 0 cnp_collector_sync_replicas{value="max"} 0 cnp_collector_sync_replicas{value="min"} 0 cnp_collector_sync_replicas{value="observed"} 0 # HELP cnp_collector_up 1 if PostgreSQL is up, 0 otherwise. # TYPE cnp_collector_up gauge cnp_collector_up{cluster="cluster-example"} 1 # HELP cnp_collector_postgres_version Postgres version # TYPE cnp_collector_postgres_version gauge cnp_collector_postgres_version{cluster="cluster-example",full="17.2"} 17.2 # HELP cnp_collector_last_failed_backup_timestamp The last failed backup as a unix timestamp # TYPE cnp_collector_last_failed_backup_timestamp gauge cnp_collector_last_failed_backup_timestamp 0 # HELP cnp_collector_last_available_backup_timestamp The last available backup as a unix timestamp # TYPE cnp_collector_last_available_backup_timestamp gauge cnp_collector_last_available_backup_timestamp 1.63238406e+09 # HELP cnp_collector_first_recoverability_point The first point of recoverability for the cluster as a unix timestamp # TYPE cnp_collector_first_recoverability_point gauge cnp_collector_first_recoverability_point 1.63238406e+09 # HELP cnp_collector_lo_pages Estimated number of pages in the pg_largeobject table # TYPE cnp_collector_lo_pages gauge cnp_collector_lo_pages{datname="app"} 0 cnp_collector_lo_pages{datname="postgres"} 78 # HELP cnp_collector_wal_buffers_full Number of times WAL data was written to disk because WAL buffers became full. Only available on PG 14+ # TYPE cnp_collector_wal_buffers_full gauge cnp_collector_wal_buffers_full{stats_reset="2023-06-19T10:51:27.473259Z"} 6472 # HELP cnp_collector_wal_bytes Total amount of WAL generated in bytes. Only available on PG 14+ # TYPE cnp_collector_wal_bytes gauge cnp_collector_wal_bytes{stats_reset="2023-06-19T10:51:27.473259Z"} 1.0035147e+07 # HELP cnp_collector_wal_fpi Total number of WAL full page images generated. Only available on PG 14+ # TYPE cnp_collector_wal_fpi gauge cnp_collector_wal_fpi{stats_reset="2023-06-19T10:51:27.473259Z"} 1474 # HELP cnp_collector_wal_records Total number of WAL records generated. Only available on PG 14+ # TYPE cnp_collector_wal_records gauge cnp_collector_wal_records{stats_reset="2023-06-19T10:51:27.473259Z"} 26178 # HELP cnp_collector_wal_sync Number of times WAL files were synced to disk via issue_xlog_fsync request (if fsync is on and wal_sync_method is either fdatasync, fsync or fsync_writethrough, otherwise zero). Only available on PG 14+ # TYPE cnp_collector_wal_sync gauge cnp_collector_wal_sync{stats_reset="2023-06-19T10:51:27.473259Z"} 37 # HELP cnp_collector_wal_sync_time Total amount of time spent syncing WAL files to disk via issue_xlog_fsync request, in milliseconds (if track_wal_io_timing is enabled, fsync is on, and wal_sync_method is either fdatasync, fsync or fsync_writethrough, otherwise zero). Only available on PG 14+ # TYPE cnp_collector_wal_sync_time gauge cnp_collector_wal_sync_time{stats_reset="2023-06-19T10:51:27.473259Z"} 0 # HELP cnp_collector_wal_write Number of times WAL buffers were written out to disk via XLogWrite request. Only available on PG 14+ # TYPE cnp_collector_wal_write gauge cnp_collector_wal_write{stats_reset="2023-06-19T10:51:27.473259Z"} 7243 # HELP cnp_collector_wal_write_time Total amount of time spent writing WAL buffers to disk via XLogWrite request, in milliseconds (if track_wal_io_timing is enabled, otherwise zero). This includes the sync time when wal_sync_method is either open_datasync or open_sync. Only available on PG 14+ # TYPE cnp_collector_wal_write_time gauge cnp_collector_wal_write_time{stats_reset="2023-06-19T10:51:27.473259Z"} 0 # HELP cnp_last_error 1 if the last collection ended with error, 0 otherwise. # TYPE cnp_last_error gauge cnp_last_error 0 # HELP go_gc_duration_seconds A summary of the pause duration of garbage collection cycles. # TYPE go_gc_duration_seconds summary go_gc_duration_seconds{quantile="0"} 5.01e-05 go_gc_duration_seconds{quantile="0.25"} 7.27e-05 go_gc_duration_seconds{quantile="0.5"} 0.0001748 go_gc_duration_seconds{quantile="0.75"} 0.0002959 go_gc_duration_seconds{quantile="1"} 0.0012776 go_gc_duration_seconds_sum 0.0035741 go_gc_duration_seconds_count 13 # HELP go_goroutines Number of goroutines that currently exist. # TYPE go_goroutines gauge go_goroutines 25 # HELP go_info Information about the Go environment. # TYPE go_info gauge go_info{version="go1.20.5"} 1 # HELP go_memstats_alloc_bytes Number of bytes allocated and still in use. # TYPE go_memstats_alloc_bytes gauge go_memstats_alloc_bytes 4.493744e+06 # HELP go_memstats_alloc_bytes_total Total number of bytes allocated, even if freed. # TYPE go_memstats_alloc_bytes_total counter go_memstats_alloc_bytes_total 2.1698216e+07 # HELP go_memstats_buck_hash_sys_bytes Number of bytes used by the profiling bucket hash table. # TYPE go_memstats_buck_hash_sys_bytes gauge go_memstats_buck_hash_sys_bytes 1.456234e+06 # HELP go_memstats_frees_total Total number of frees. # TYPE go_memstats_frees_total counter go_memstats_frees_total 172118 # HELP go_memstats_gc_cpu_fraction The fraction of this programs available CPU time used by the GC since the program started. # TYPE go_memstats_gc_cpu_fraction gauge go_memstats_gc_cpu_fraction 1.0749468700447189e-05 # HELP go_memstats_gc_sys_bytes Number of bytes used for garbage collection system metadata. # TYPE go_memstats_gc_sys_bytes gauge go_memstats_gc_sys_bytes 5.530048e+06 # HELP go_memstats_heap_alloc_bytes Number of heap bytes allocated and still in use. # TYPE go_memstats_heap_alloc_bytes gauge go_memstats_heap_alloc_bytes 4.493744e+06 # HELP go_memstats_heap_idle_bytes Number of heap bytes waiting to be used. # TYPE go_memstats_heap_idle_bytes gauge go_memstats_heap_idle_bytes 5.8236928e+07 # HELP go_memstats_heap_inuse_bytes Number of heap bytes that are in use. # TYPE go_memstats_heap_inuse_bytes gauge go_memstats_heap_inuse_bytes 7.528448e+06 # HELP go_memstats_heap_objects Number of allocated objects. # TYPE go_memstats_heap_objects gauge go_memstats_heap_objects 26306 # HELP go_memstats_heap_released_bytes Number of heap bytes released to OS. # TYPE go_memstats_heap_released_bytes gauge go_memstats_heap_released_bytes 5.7401344e+07 # HELP go_memstats_heap_sys_bytes Number of heap bytes obtained from system. # TYPE go_memstats_heap_sys_bytes gauge go_memstats_heap_sys_bytes 6.5765376e+07 # HELP go_memstats_last_gc_time_seconds Number of seconds since 1970 of last garbage collection. # TYPE go_memstats_last_gc_time_seconds gauge go_memstats_last_gc_time_seconds 1.6311727586032727e+09 # HELP go_memstats_lookups_total Total number of pointer lookups. # TYPE go_memstats_lookups_total counter go_memstats_lookups_total 0 # HELP go_memstats_mallocs_total Total number of mallocs. # TYPE go_memstats_mallocs_total counter go_memstats_mallocs_total 198424 # HELP go_memstats_mcache_inuse_bytes Number of bytes in use by mcache structures. # TYPE go_memstats_mcache_inuse_bytes gauge go_memstats_mcache_inuse_bytes 14400 # HELP go_memstats_mcache_sys_bytes Number of bytes used for mcache structures obtained from system. # TYPE go_memstats_mcache_sys_bytes gauge go_memstats_mcache_sys_bytes 16384 # HELP go_memstats_mspan_inuse_bytes Number of bytes in use by mspan structures. # TYPE go_memstats_mspan_inuse_bytes gauge go_memstats_mspan_inuse_bytes 191896 # HELP go_memstats_mspan_sys_bytes Number of bytes used for mspan structures obtained from system. # TYPE go_memstats_mspan_sys_bytes gauge go_memstats_mspan_sys_bytes 212992 # HELP go_memstats_next_gc_bytes Number of heap bytes when next garbage collection will take place. # TYPE go_memstats_next_gc_bytes gauge go_memstats_next_gc_bytes 8.689632e+06 # HELP go_memstats_other_sys_bytes Number of bytes used for other system allocations. # TYPE go_memstats_other_sys_bytes gauge go_memstats_other_sys_bytes 2.566622e+06 # HELP go_memstats_stack_inuse_bytes Number of bytes in use by the stack allocator. # TYPE go_memstats_stack_inuse_bytes gauge go_memstats_stack_inuse_bytes 1.343488e+06 # HELP go_memstats_stack_sys_bytes Number of bytes obtained from system for stack allocator. # TYPE go_memstats_stack_sys_bytes gauge go_memstats_stack_sys_bytes 1.343488e+06 # HELP go_memstats_sys_bytes Number of bytes obtained from system. # TYPE go_memstats_sys_bytes gauge go_memstats_sys_bytes 7.6891144e+07 # HELP go_threads Number of OS threads created. # TYPE go_threads gauge go_threads 18 .. Note:: `cnp_collector_postgres_version` is a GaugeVec metric containing the `Major.Minor` version of Postgres (either PostgreSQL or EPAS). The full semantic version `Major.Minor.Patch` can be found inside one of its label field named `full` . .. Note:: `cnp_collector_first_recoverability_point` and `cnp_collector_last_available_backup_timestamp` will be zero until your first backup to the object store. This is separate from the WAL archival. User defined metrics ^^^^^^^^^^^^^^^^^^^^ This feature is currently in *beta* state and the format is inspired by the `queries.yaml file (release 0.12) `_ of the PostgreSQL Prometheus Exporter. Custom metrics can be defined by users by referring to the created ``Configmap`` /``Secret`` in a ``Cluster`` definition under the ``.spec.monitoring.customQueriesConfigMap`` or ``customQueriesSecret`` section as in the following example: .. code:: yaml apiVersion: postgresql.k8s.enterprisedb.io/v1 kind: Cluster metadata: name: cluster-example namespace: test spec: instances: 3 storage: size: 1Gi monitoring: customQueriesConfigMap: - name: example-monitoring key: custom-queries The ``customQueriesConfigMap`` /``customQueriesSecret`` sections contain a list of ``ConfigMap`` /``Secret`` references specifying the key in which the custom queries are defined. Take care that the referred resources have to be created **in the same namespace as the Cluster** resource. .. Note:: If you want ConfigMaps and Secrets to be **automatically** reloaded by instances, you can add a label with key `k8s.enterprisedb.io/reload` to it, otherwise you will have to reload the instances using the `kubectl cnp reload` subcommand. .. Important:: When a user defined metric overwrites an already existing metric the instance manager prints a json warning log, containing the message:`Query with the same name already found. Overwriting the existing one.` and a key `queryName` containing the overwritten query name. Example of a user defined metric ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Here you can see an example of a ``ConfigMap`` containing a single custom query, referenced by the ``Cluster`` example above: .. code:: yaml apiVersion: v1 kind: ConfigMap metadata: name: example-monitoring namespace: test labels: k8s.enterprisedb.io/reload: "" data: custom-queries: | pg_replication: query: "SELECT CASE WHEN NOT pg_is_in_recovery() THEN 0 ELSE GREATEST (0, EXTRACT(EPOCH FROM (now() - pg_last_xact_replay_timestamp()))) END AS lag, pg_is_in_recovery() AS in_recovery, EXISTS (TABLE pg_stat_wal_receiver) AS is_wal_receiver_up, (SELECT count(*) FROM pg_stat_replication) AS streaming_replicas" metrics: - lag: usage: "GAUGE" description: "Replication lag behind primary in seconds" - in_recovery: usage: "GAUGE" description: "Whether the instance is in recovery" - is_wal_receiver_up: usage: "GAUGE" description: "Whether the instance wal_receiver is up" - streaming_replicas: usage: "GAUGE" description: "Number of streaming replicas connected to the instance" A list of basic monitoring queries are as below that is already installed in your EDB CloudNativePG Cluster deployment (see :ref:`Default set of metrics ` ). Example of a user defined metric with predicate query ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The ``predicate_query`` option allows the user to execute the ``query`` to collect the metrics only under the specified conditions. To do so the user needs to provide a predicate query that returns at most one row with a single ``boolean`` column. The predicate query is executed in the same transaction as the main query and against the same databases. .. code:: yaml some_query: | predicate_query: | SELECT some_bool as predicate FROM some_table query: | SELECT count(*) as rows FROM some_table metrics: - rows: usage: "GAUGE" description: "number of rows" Example of a user defined metric running on multiple databases ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ If the ``target_databases`` option lists more than one database the metric is collected from each of them. Database auto-discovery can be enabled for a specific query by specifying a *shell-like pattern* (i.e., containing ``*`` , ``?`` or ``[]`` ) in the list of ``target_databases`` . If provided, the operator will expand the list of target databases by adding all the databases returned by the execution of ``SELECT datname FROM pg_database WHERE datallowconn AND NOT datistemplate`` and matching the pattern according to `path.Match() `_ rules. .. Note:: The `*` character has a `special meaning `_ in yaml, so you need to quote (`"*"` ) the `target_databases` value when it includes such a pattern. It is recommended that you always include the name of the database in the returned labels, for example using the ``current_database()`` function as in the following example: .. code:: yaml some_query: | query: | SELECT current_database() as datname, count(*) as rows FROM some_table metrics: - datname: usage: "LABEL" description: "Name of current database" - rows: usage: "GAUGE" description: "number of rows" target_databases: - albert - bb - freddie This will produce in the following metric being exposed: .. code:: text cnp_some_query_rows{datname="albert"} 2 cnp_some_query_rows{datname="bb"} 5 cnp_some_query_rows{datname="freddie"} 10 Here is an example of a query with auto-discovery enabled which also runs on the ``template1`` database (otherwise not returned by the aforementioned query): .. code:: yaml some_query: | query: | SELECT current_database() as datname, count(*) as rows FROM some_table metrics: - datname: usage: "LABEL" description: "Name of current database" - rows: usage: "GAUGE" description: "number of rows" target_databases: - "*" - "template1" The above example will produce the following metrics (provided the databases exist): .. code:: text cnp_some_query_rows{datname="albert"} 2 cnp_some_query_rows{datname="bb"} 5 cnp_some_query_rows{datname="freddie"} 10 cnp_some_query_rows{datname="template1"} 7 cnp_some_query_rows{datname="postgres"} 42 Structure of a user defined metric ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Every custom query has the following basic structure: .. code:: yaml : query: "" metrics: - : usage: "" description: "" Here is a short description of all the available fields: - ```` : the name of the Prometheus metric - ``name`` : override ```` , if defined - ``query`` : the SQL query to run on the target database to generate the metrics - ``primary`` : whether to run the query only on the primary instance - ``master`` : same as ``primary`` (for compatibility with the Prometheus PostgreSQL exporter’s syntax - deprecated) - ``runonserver`` : a semantic version range to limit the versions of PostgreSQL the query should run on (e.g. ``">=11.0.0"`` or ``">=12.0.0 <=15.0.0"`` ) - ``target_databases`` : a list of databases to run the ``query`` against, or a :ref:`shell-like pattern <#example-of-a-user-defined-metric-running-on-multiple-databases>` to enable auto discovery. Overwrites the default database if provided. - ``predicate_query`` : a SQL query that returns at most one row and one ``boolean`` column to run on the target database. The system evaluates the predicate and if ``true`` executes the ``query`` . - ``metrics`` : section containing a list of all exported columns, defined as follows: - ```` : the name of the column returned by the query - ``name`` : override the ``ColumnName`` of the column in the metric, if defined - ``usage`` : one of the values described below - ``description`` : the metric’s description - ``metrics_mapping`` : the optional column mapping when ``usage`` is set to ``MAPPEDMETRIC`` The possible values for ``usage`` are: .. csv-table:: :header: Column Usage Label,Description :widths: 10,30 :align: left :class: longtable `DISCARD`,this column should be ignored `LABEL`,use this column as a label `COUNTER`,use this column as a counter `GAUGE`,use this column as a gauge `MAPPEDMETRIC`,use this column with the supplied mapping of text values `DURATION`,use this column as a text duration (in milliseconds) `HISTOGRAM`,use this column as a histogram Please visit the `Metric Types `_ from the Prometheus documentation for more information. Output of a user defined metric ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Custom defined metrics are returned by the Prometheus exporter endpoint (``:9187/metrics`` ) with the following format: .. code:: text cnp__{= ... } .. Note:: `LabelColumnName` are metrics with `usage` set to `LABEL` and their `Value` Considering the ``pg_replication`` example above, the exporter’s endpoint would return the following output when invoked: .. code:: text # HELP cnp_pg_replication_in_recovery Whether the instance is in recovery # TYPE cnp_pg_replication_in_recovery gauge cnp_pg_replication_in_recovery 0 # HELP cnp_pg_replication_lag Replication lag behind primary in seconds # TYPE cnp_pg_replication_lag gauge cnp_pg_replication_lag 0 # HELP cnp_pg_replication_streaming_replicas Number of streaming replicas connected to the instance # TYPE cnp_pg_replication_streaming_replicas gauge cnp_pg_replication_streaming_replicas 2 # HELP cnp_pg_replication_is_wal_receiver_up Whether the instance wal_receiver is up # TYPE cnp_pg_replication_is_wal_receiver_up gauge cnp_pg_replication_is_wal_receiver_up 0 Default set of metrics ^^^^^^^^^^^^^^^^^^^^^^ The operator can be configured to automatically inject in a Cluster a set of monitoring queries defined in a ConfigMap or a Secret, inside the operator’s namespace. You have to set the ``MONITORING_QUERIES_CONFIGMAP`` or ``MONITORING_QUERIES_SECRET`` key in the :ref:`Operator configuration ` , respectively to the name of the ConfigMap or the Secret; the operator will then use the content of the ``queries`` key. Any change to the ``queries`` content will be immediately reflected on all the deployed Clusters using it. The operator installation manifests come with a predefined ConfigMap, called ``postgresql-operator-default-monitoring`` , to be used by all Clusters. ``MONITORING_QUERIES_CONFIGMAP`` is by default set to ``postgresql-operator-default-monitoring`` in the operator configuration. If you want to disable the default set of metrics, you can: - disable it at operator level: set the ``MONITORING_QUERIES_CONFIGMAP`` /``MONITORING_QUERIES_SECRET`` key to ``""`` (empty string), in the operator ConfigMap. Changes to operator ConfigMap require an operator restart. - disable it for a specific Cluster: set ``.spec.monitoring.disableDefaultQueries`` to ``true`` in the Cluster. .. Important:: The ConfigMap or Secret specified via `MONITORING_QUERIES_CONFIGMAP` /`MONITORING_QUERIES_SECRET` will always be copied to the Cluster's namespace with a fixed name: `postgresql-operator-default-monitoring` . So that, if you intend to have default metrics, you should not create a ConfigMap with this name in the cluster's namespace. Differences with the Prometheus Postgres exporter ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ EDB CloudNativePG Cluster is inspired by the PostgreSQL Prometheus Exporter, but presents some differences. In particular, the ``cache_seconds`` field is not implemented in EDB CloudNativePG Cluster’ exporter. Monitoring the operator ----------------------- The operator internally exposes `Prometheus `_ metrics via HTTP on port 8080, named ``metrics`` . .. Note:: You can inspect the exported metrics by following the instructions in the :ref:`How to inspect the exported metrics ` section below. Currently, the operator exposes default ``kubebuilder`` metrics, see `kubebuilder documentation `_ for more details. .. _prometheus-operator-example-1: Prometheus Operator example ^^^^^^^^^^^^^^^^^^^^^^^^^^^ The operator deployment can be monitored using the `Prometheus Operator `_ by defining the following `PodMonitor `_ resource: .. code:: yaml apiVersion: monitoring.coreos.com/v1 kind: PodMonitor metadata: name: postgresql-operator-controller-manager spec: selector: matchLabels: app.kubernetes.io/name: cloud-native-postgresql podMetricsEndpoints: - port: metrics How to inspect the exported metrics ----------------------------------- In this section we provide some basic instructions on how to inspect the metrics exported by a specific PostgreSQL instance manager (primary or replica) or the operator, using a temporary pod running ``curl`` in the same namespace. .. Note:: In the example below we assume we are working in the default namespace, alongside with the PostgreSQL cluster. Please feel free to adapt this example to your use case, by applying basic Kubernetes knowledge. Create the ``curl.yaml`` file with this content: .. code:: yaml apiVersion: v1 kind: Pod metadata: name: curl spec: containers: - name: curl image: curlimages/curl:8.2.1 command: [sleep, 3600] Then create the pod: .. code:: shell kubectl apply -f curl.yaml In case you want to inspect the metrics exported by an instance, you need to connect to port 9187 of the target pod. This is the generic command to be run (make sure you use the correct IP for the pod): .. code:: shell kubectl exec -ti curl -- curl -s :9187/metrics For example, if your PostgreSQL cluster is called ``cluster-example`` and you want to retrieve the exported metrics of the first pod in the cluster, you can run the following command to programmatically get the IP of that pod: .. code:: shell POD_IP=$(kubectl get pod cluster-example-1 --template {{.status.podIP}}) And then run: .. code:: shell kubectl exec -ti curl -- curl -s ${POD_IP}:9187/metrics If you enabled TLS metrics, run instead: .. code:: shell kubectl exec -ti curl -- curl -sk https://${POD_IP}:9187/metrics In case you want to access the metrics of the operator, you need to point to the pod where the operator is running, and use TCP port 8080 as target. At the end of the inspection, please make sure you delete the ``curl`` pod: .. code:: shell kubectl delete -f curl.yaml Auxiliary resources ------------------- .. Important:: These resources are provided for illustration and experimentation, and do not represent any kind of recommendation for your production system In the :ref:`doc/src/samples/monitoring/ ` directory you will find a series of sample files for observability. Please refer to :ref:`Part 4 of the quickstart ` section for context: - ``kube-stack-config.yaml`` : a configuration file for the kube-stack helm chart installation. It ensures that Prometheus listens for all PodMonitor resources. - ``prometheusrule.yaml`` : a ``PrometheusRule`` with alerts for EDB CloudNativePG Cluster. NOTE: this does not include inter-operation with notification services. Please refer to the `Prometheus documentation `_ . - ``podmonitor.yaml`` : a ``PodMonitor`` for the EDB CloudNativePG Cluster Operator deployment. In addition, we provide the “raw” sources for the Prometheus alert rules in the ``alerts.yaml`` file. The `Grafana dashboard `_ has a dedicated repository now. Note that, for the configuration of ``kube-prometheus-stack`` , other fields and settings are available over what we provide in ``kube-stack-config.yaml`` . You can execute ``helm show values prometheus-community/kube-prometheus-stack`` to view them. For further information, please refer to the `kube-prometheus-stack `_ page. Monitoring on OpenShift ----------------------- Starting on Openshift 4.6 there is a complete monitoring stack called :ref:`Monitoring for user-defined projects ` which can be enabled by cluster administrators. Cloud Native PostgreSQL will automatically create a ``PodMonitor`` object if the option ``spec.monitoring.enablePodMonitor`` of the ``Cluster`` definition is set to ``true`` . To enable cluster wide ``user-defined`` monitoring you must first create a ``ConfigMap`` with the name ``cluster-monitoring-config`` in the ``openshift-monitoring`` namespace/project with the following content: .. code:: yaml apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | enableUserWorkload: true If the ``ConfigMap`` already exists, just add the variable ``enableUserWorkload: true`` . .. Important:: This will enable the monitoring for the whole cluster, if it is needed only for one namespace/project please refer to the official Red Hat documentation or talk with your cluster administrator. After that, just create the proper PodMonitor in the namespace/project with something similar to this: .. code:: yaml apiVersion: monitoring.coreos.com/v1 kind: PodMonitor metadata: name: cluster-sample spec: selector: matchLabels: postgresql: cluster-sample podMetricsEndpoints: - port: metrics .. Note:: We currently don’t use `ServiceMonitor` because our service doesn’t define a port pointing to the metrics. If we added a metric port this could expose sensitive data.