Edit

Share via

Monitor metrics on Azure Database for PostgreSQL - Flexible Server

  • Article

APPLIES TO: Azure Database for PostgreSQL - Flexible Server

Monitoring data about your servers helps you troubleshoot and optimize for your workload. Azure Database for PostgreSQL flexible server provides various monitoring options to provide insight into how your server is performing.

Metrics

Azure Database for PostgreSQL flexible server provides various metrics that give insight into the behavior of the resources that support the Azure Database for PostgreSQL flexible server instance. Each metric is emitted at a 1-minute interval and has up to 93 days of history. You can configure alerts on the metrics. Other options include setting up automated actions, performing advanced analytics, and archiving the history. For more information, see the Azure Metrics overview.

Note

While metrics are stored for 93 days, you can only query (in the Metrics tile) for a maximum of 30 days' worth of data on any single chart. If you see a blank chart or your chart displays only part of metric data, verify that the difference between start and end dates in the time picker doesn't exceed the 30-day interval. After you've selected a 30-day interval, you can pan the chart to view the full retention window.

Default Metrics

The following metrics are available for an Azure Database for PostgreSQL flexible server instance:

Display name Metric ID Unit Description Default enabled
Active Connections active_connections Count Total number of connections to the database server, including all connection states such as active, idle, and others, as seen in pg_stat_activity view. This figure represents the overall sum of connections across all states, without distinguishing between specific states. For an in-depth analysis on a specific state, such as active connections, refer to the 'Sessions By State' metric. Yes
Backup Storage Used backup_storage_used Bytes Amount of backup storage used. This metric represents the sum of storage that's consumed by all the full backups, differential backups, and log backups that are retained based on the backup retention period that's set for the server. The frequency of the backups is service managed. For geo-redundant storage, backup storage usage is twice the usage for locally redundant storage. Yes
Failed Connections connections_failed Count Number of failed connections. Yes
Succeeded Connections connections_succeeded Count Number of succeeded connections. Yes
CPU Credits Consumed cpu_credits_consumed Count Number of credits used by the flexible server. Applies to the Burstable tier. Yes
CPU Credits Remaining cpu_credits_remaining Count Number of credits available to burst. Applies to the Burstable tier. Yes
CPU percent cpu_percent Percent Percentage of CPU in use. Yes
Database Size (preview) database_size_bytes Bytes Database size in bytes. Yes
Disk Queue Depth disk_queue_depth Count Number of outstanding I/O operations to the data disk. Yes
IOPS iops Count Number of I/O operations to disk per second. Yes
Maximum Used Transaction IDs maximum_used_transactionIDs Count Maximum number of transaction IDs in use. Yes
Memory percent memory_percent Percent Percentage of memory in use. Yes
Network Out network_bytes_egress Bytes Amount of outgoing network traffic. Yes
Network In network_bytes_ingress Bytes Amount of incoming network traffic. Yes
Read IOPS read_iops Count Number of data disk I/O read operations per second. Yes
Read Throughput read_throughput Bytes Bytes read per second from disk. Yes
Storage Free storage_free Bytes Amount of storage space that's available. Yes
Storage percent storage_percent Percentage Percent of storage space that's used. The storage that's used by the service can include database files, transaction logs, and server logs. Yes
Storage Used storage_used Bytes Amount of storage space that's used. The storage that's used by the service can include the database files, transaction logs, and the server logs. Yes
Transaction Log Storage Used txlogs_storage_used Bytes Amount of storage space that's used by the transaction logs. Yes
Write Throughput write_throughput Bytes Bytes written to disk per second. Yes
Write IOPS write_iops Count Number of data disk I/O write operations per second. Yes

Enhanced metrics

You can use enhanced metrics for Azure Database for PostgreSQL flexible server to get fine-grained monitoring and alerting on databases. You can configure alerts on the metrics. Some enhanced metrics include a Dimension parameter that you can use to split and filter metrics data by using a dimension like database name or state.

Enabling enhanced metrics

  • Most of these new metrics are disabled by default. There are a few exceptions though, which are enabled by default. Rightmost column in the following tables indicates whether each metric is enabled by default or not.
  • To enable those metrics which are not enabled by default, set the server parameter metrics.collector_database_activity to ON. This parameter is dynamic and doesn't require an instance restart.
List of enhanced metrics

You can choose from the following categories of enhanced metrics:

  • Activity
  • Database
  • Logical replication
  • Replication
  • Saturation
  • Traffic
Activity
Display name Metric ID Unit Description Dimension Default enabled
Sessions By State sessions_by_state Count Sessions by state as shown in pg_stat_activity view. It categorizes client backends into various states, such as active or idle. State No
Sessions By WaitEventType sessions_by_wait_event_type Count Sessions by the type of event for which the client backend is waiting. Wait Event Type No
Oldest Backend oldest_backend_time_sec Seconds Age in seconds of the oldest backend (irrespective of the state). Doesn't apply No
Oldest Query longest_query_time_sec Seconds Age in seconds of the longest query that's currently running. Doesn't apply No
Oldest Transaction longest_transaction_time_sec Seconds Age in seconds of the longest transaction (including idle transactions). Doesn't apply No
Oldest xmin oldest_backend_xmin Count The actual value of the oldest xmin. If xmin isn't increasing, it indicates that there are some long-running transactions that can potentially hold dead tuples from being removed. Doesn't apply No
Oldest xmin Age oldest_backend_xmin_age Count Age in units of the oldest xmin. Indicates how many transactions passed since the oldest xmin. Doesn't apply No
Database
Display name Metric ID Unit Description Dimension Default enabled
Backends numbackends Count Number of backends that are connected to this database. DatabaseName No
Deadlocks deadlocks Count Number of deadlocks that are detected in this database. DatabaseName No
Disk Blocks Hit blks_hit Count Number of times disk blocks were found already in the buffer cache, so that a read wasn't necessary. DatabaseName No
Disk Blocks Read blks_read Count Number of disk blocks that were read in this database. DatabaseName No
Temporary Files temp_files Count Number of temporary files that were created by queries in this database. DatabaseName No
Temporary Files Size temp_bytes Bytes Total amount of data that's written to temporary files by queries in this database. DatabaseName No
Total Transactions xact_total Count Number of total transactions that executed in this database. DatabaseName No
Transactions Committed xact_commit Count Number of transactions in this database that have been committed. DatabaseName No
Transactions per second (Preview) tps Count Number of transactions executed within a second. DatabaseName No
Transactions Rolled back xact_rollback Count Number of transactions in this database that have been rolled back. DatabaseName No
Tuples Deleted tup_deleted Count Number of rows that were deleted by queries in this database. DatabaseName No
Tuples Fetched tup_fetched Count Number of rows that were fetched by queries in this database. DatabaseName No
Tuples Inserted tup_inserted Count Number of rows that were inserted by queries in this database. DatabaseName No
Tuples Returned tup_returned Count Number of rows that were returned by queries in this database. DatabaseName No
Tuples Updated tup_updated Count Number of rows that were updated by queries in this database. DatabaseName No
Logical replication
Display name Metric ID Unit Description Dimension Default enabled
Max Logical Replication Lag logical_replication_delay_in_bytes Bytes Maximum lag across all logical replication slots. Doesn't apply Yes
Replication
Display name Metric ID Unit Description Dimension Default enabled
Max Physical Replication Lag physical_replication_delay_in_bytes Bytes Maximum lag across all asynchronous physical replication slots. Doesn't apply Yes
Read Replica Lag physical_replication_delay_in_seconds Seconds Read replica lag in seconds. Doesn't apply Yes
Saturation
Display name Metric ID Unit Description Dimension Default enabled
Disk Bandwidth Consumed Percentage disk_bandwidth_consumed_percentage Percent Percentage of data disk bandwidth consumed per minute. Doesn't apply Yes
Disk IOPS Consumed Percentage disk_iops_consumed_percentage Percent Percentage of data disk I/Os consumed per minute. Doesn't apply Yes
Traffic
Display name Metric ID Unit Description Dimension Default enabled
Max Connections ^ max_connections Count Number of maximum connections. Doesn't apply Yes

^ Max Connections represents the configured value for the max_connections server parameter. This metric is polled every 30 minutes.

Considerations for using enhanced metrics
  • Enhanced metrics that use the DatabaseName dimension have a 50-database limit.
  • On the Burstable SKU, the limit is 10 databases for metrics that use the DatabaseName dimension.
  • The DatabaseName dimension limit is applied on the database identifier (datid) column of the pg_stat_database system view, which reflects the order of creation for the database.
  • The DatabaseName in the metrics dimension is case insensitive. That means that after querying pg_stat_database view, filtering out rows in which datname is either template1 or template0, ordering by datid, and limiting the returned rows to the first 50 (or 10 in the case of Burstable SKU), the metrics for database names in that result set, that are the same except for case (for example, contoso_database and Contoso_database) will be merged and might not show accurate data.

Autovacuum metrics

Autovacuum metrics can be used to monitor and tune autovacuum performance for Azure Database for PostgreSQL - Flexible Server. Each metric is emitted at a 30-minute interval and has up to 93 days of retention. You can create alerts for specific metrics, and you can split and filter metrics data by using the DatabaseName dimension.

How to enable autovacuum metrics

  • Autovacuum metrics are disabled by default.
  • To enable these metrics, set the server parameter metrics.autovacuum_diagnostics to ON.
  • This parameter is dynamic, so an instance restart isn't required.

List of autovacuum metrics

Display name Metric ID Unit Description Dimension Default enabled
Analyze Counter User Tables analyze_count_user_tables Count Number of times user-only tables have been manually analyzed in this database. DatabaseName No
AutoAnalyze Counter User Tables autoanalyze_count_user_tables Count Number of times user-only tables have been analyzed by the autovacuum daemon in this database. DatabaseName No
AutoVacuum Counter User Tables autovacuum_count_user_tables Count Number of times user-only tables have been vacuumed by the autovacuum daemon in this database. DatabaseName No
Bloat Percent (Preview) bloat_percent Percent Estimated bloat percentage for user only tables. DatabaseName No
Estimated Dead Rows User Tables n_dead_tup_user_tables Count Estimated number of dead rows for user-only tables in this database. DatabaseName No
Estimated Live Rows User Tables n_live_tup_user_tables Count Estimated number of live rows for user-only tables in this database. DatabaseName No
Estimated Modifications User Tables n_mod_since_analyze_user_tables Count Estimated number of rows that were modified since user-only tables were last analyzed. DatabaseName No
User Tables Analyzed tables_analyzed_user_tables Count Number of user-only tables that have been analyzed in this database. DatabaseName No
User Tables AutoAnalyzed tables_autoanalyzed_user_tables Count Number of user-only tables that have been analyzed by the autovacuum daemon in this database. DatabaseName No
User Tables AutoVacuumed tables_autovacuumed_user_tables Count Number of user-only tables that have been vacuumed by the autovacuum daemon in this database. DatabaseName No
User Tables Counter tables_counter_user_tables Count Number of user-only tables in this database. DatabaseName No
User Tables Vacuumed tables_vacuumed_user_tables Count Number of user-only tables that have been vacuumed in this database. DatabaseName No
Vacuum Counter User Tables vacuum_count_user_tables Count Number of times user-only tables have been manually vacuumed in this database (not counting VACUUM FULL). DatabaseName No

Considerations for using autovacuum metrics

  • Autovacuum metrics that use the DatabaseName dimension have a 30-database limit.
  • On the Burstable SKU, the limit is 10 databases for metrics that use the DatabaseName dimension.
  • The DatabaseName dimension limit is applied on the OID column, which reflects the order of creation for the database.

PgBouncer metrics

You can use PgBouncer metrics to monitor the performance of the PgBouncer process, including details for active connections, idle connections, total pooled connections, and the number of connection pools. Each metric is emitted at a 1-minute interval and has up to 93 days of history. Customers can configure alerts on the metrics and also access the new metrics dimensions to split and filter metrics data by database name.

How to enable PgBouncer metrics

  • To monitor PgBouncer metrics, ensure that the pgbouncer feature is enabled via the server parameter pgbouncer.enabled and metrics parameter metrics.pgbouncer_diagnostics is enabled.
  • These parameters are dynamic and don't require an instance restart.
  • PgBouncer metrics are disabled by default.

List of PgBouncer metrics

Display name Metric ID Unit Description Dimension Default enabled
Active client connections client_connections_active Count Connections from clients that are associated with an Azure Database for PostgreSQL - Flexible Server connection. DatabaseName No
Waiting client connections client_connections_waiting Count Connections from clients that are waiting for an Azure Database for PostgreSQL - Flexible Server connection to service them. DatabaseName No
Active server connections server_connections_active Count Connections to Azure Database for PostgreSQL - Flexible Server that are in use by a client connection. DatabaseName No
Idle server connections server_connections_idle Count Connections to Azure Database for PostgreSQL - Flexible Server that are idle and ready to service a new client connection. DatabaseName No
Total pooled connections total_pooled_connections Count Current number of pooled connections. DatabaseName No
Number of connection pools num_pools Count Total number of connection pools. DatabaseName No

Considerations for using the PgBouncer metrics

  • PgBouncer metrics that use the DatabaseName dimension have a 30-database limit.
  • On the Burstable SKU, the limit is 10 databases that have the DatabaseName dimension.
  • The DatabaseName dimension limit is applied to the OID column, which reflects the order of creation for the database.

Database availability metric

Is-db-alive is a database server availability metric for Azure Database for PostgreSQL flexible server that returns [1 for available] and [0 for not-available]. Each metric is emitted at a 1 minute frequency, and has up to 93 days of retention. Customers can configure alerts on the metric.

Display Name Metric ID Unit Description Dimension Default enabled
Database Is Alive is_db_alive Count Indicates if the database is up or not. N/a Yes

Considerations when using the Database availability metrics

  • Aggregating this metric with MAX() will allow customers to determine whether the server has been up or down in the last minute.
  • Customers have option to further aggregate these metrics with any desired frequency (5m, 10m, 30m etc.) to suit their alerting requirements and avoid any false positive.
  • Other possible aggregations are AVG() and MIN().

Filter and split on dimension metrics

In the preceding tables, some metrics have dimensions like DatabaseName or State. You can use filtering and splitting for the metrics that have dimensions. These features show how various metric segments (or dimension values) affect the overall value of the metric. You can use them to identify possible outliers.

  • Filtering: Use filtering to choose which dimension values are included in the chart. For example, you might want to show idle connections when you chart the Sessions-by-State metric. You set the filter for Idle in the State dimension.
  • Splitting: Use splitting to control whether the chart displays separate lines for each value of a dimension or if it aggregates the values in a single line. For example, you can see one line for a Sessions-by-State metric across all sessions. You can see separate lines for each session grouped by State value. Apply splitting on the State dimension to see separate lines.

The following example demonstrates splitting by the State dimension and filtering on specific State values:

Screenshot that shows an example of splitting and filtering on metrics and dimensions.

For more information about setting up charts for dimensional metrics, see Metric chart examples.

Metrics visualization

There are several options to visualize Azure Monitor metrics.

Component Description Required training and/or configuration
Overview page Most Azure services have an Overview page in the Azure portal that includes a Monitor section with charts that show recent critical metrics. This information is intended for owners of individual services to quickly assess the performance of the resource. This page is based on platform metrics that are collected automatically. No configuration is required.
Metrics Explorer You can use Metrics Explorer to interactively work with metric data and create metric alerts. You need minimal training to use Metrics Explorer, but you must be familiar with the metrics you want to analyze. - Once data collection is configured, no other configuration is required.
- Platform metrics for Azure resources are automatically available.
- Guest metrics for virtual machines are available after an Azure Monitor agent is deployed to the virtual machine.
- Application metrics are available after Application Insights is configured.
Grafana You can use Grafana for visualizing and alerting on metrics. All versions of Grafana include the Azure Monitor datasource plug-in to visualize your Azure Monitor metrics and logs. To become familiar with Grafana dashboards, some training is required. However, you can simplify the process by downloading a prebuilt Azure Database for PostgreSQL flexible server grafana monitoring dashboard, which allows for easy monitoring of all Azure Database for PostgreSQL flexible server instances within your organization.

Logs

In addition to the metrics, you can use Azure Database for PostgreSQL flexible server to configure and access Azure Database for PostgreSQL standard logs. For more information, see Logging concepts.

Logs visualization

Component Description Required training and/or configuration
Log Analytics With Log Analytics, you can create log queries to interactively work with log data and create log query alerts. Some training is required for you to become familiar with the query language, although you can use prebuilt queries for common requirements.

Next steps