Monitor metrics on Azure Database for PostgreSQL - Flexible Server

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

• PgBouncer metrics are disabled by default.
• For PgBouncer metrics to work, both the server parameters pgbouncer.enabled and metrics.pgbouncer_diagnostics must be enabled.
• These parameters are dynamic and don't require an instance restart.

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:

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

• Learn more about how to configure and access logs.
• Learn more about Azure Monitor pricing.
• Learn more about audit logs.