Ubicloud Managed PostgreSQL provides metrics for monitoring the performance and health of your PostgreSQL instances. These metrics can be accessed through the details view of your PostgreSQL instance.

The time-range dropdown allows you to choose a time-frame for the graphs, ranging from 30 minutes to 30 days. Each graph displays about 480 datapoints. The graphs auto-update every 5 minutes. You can also manually update the graphs with the refresh button.

If you recently provisioned the PostgreSQL database, it might take a few minutes for the metrics to become available. For databases with HA enabled, the metrics from the primary node are displayed.

Here are some of the key metrics provided and details on how to interpret them.

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Resource Usage Metrics

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CPU Usage

This shows the CPU usage, broken down into percentage of CPU time spent in user, system, iowait and steal modes. The user time reflects processing in the Postgres instance, while the system time reflects operating system (i.e., kernel) operations.

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Load average

Load Average shows average CPU usage over the last 1, 5, and 15 minutes. Typically, a load average equal to the number of CPU cores indicates full utilization of all CPUs. A load average higher than the number of CPU cores indicates that the system is overloaded, and processes are waiting for CPU time.

If you are consistently seeing high load averages, you might want to consider upgrading to a larger database size.

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Memory Usage

This shows the memory usage, broken down into Used, Cached & Buffered memory. A high amount of memory usage for Cache & Buffers is normal and indicates that the database is using the available memory efficiently. A consistently high (> 90%) value for Used memory indicates that the database might be running low on available memory, which can lead to performance issues.

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Disk Usage

Disk Usage is the disk space utilization for the database, specifically the Postgres data_directory. This includes the database contents, log files, and WAL files, among other things. If your instance is approaching 100% disk usage, you might want to consider upgrading to a larger database size.

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Disk I/O

This metric shows the disk read and write operations per second for the database instance. High values for this metric can indicate that the database is experiencing high I/O load, which can lead to performance issues.

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Network Traffic

This metric shows the incoming and outgoing network traffic for the database instance. Generally, this should match the behavior of other metrics for the instance. Unusual activity in this metric might indicate a problem with the network or the database instance itself.

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Database Performance Metrics

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Connection Count

This shows the Active and Total number of connected Postgres clients. Total connection count refers to all currently connected clients, while Active connection count refers to clients that are currently executing a query. By default, the maximum number of connections is set to 500. If your database is consistently at or near this limit, you might want to consider increasing this limit or using connection pooling via PgBouncer.

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Cache Hit Ratio

This metric indicates how many content requests were served from the cache. For normal workloads, this should typically be above 99%. If this value is low, it might indicate that the database performance might improve with a larger instance with more memory.

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Operation Throughput

This graph shows the rate of row fetches, inserts, updates, and deletes per second. This can be useful for identifying unexpected changes in usage patterns and their effects on database performance.

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Deadlocks

This metric shows the rate of deadlocks detected per second in the database. Deadlocks occur when two or more transactions are waiting on resources held by others, resulting in a situation where none of them can proceed. A non-zero or high value indicates bad transaction design, which can lead to degraded performance.

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Database Size

This graph shows the size of the 5 largest databases in the instance. This can be useful in identifying databases that are growing unexpectedly or are due for cleanup or archiving.

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Transactions

This graph shows the rate of transactions committed and rolled back per second. This can be useful for identifying unexpected changes in usage patterns and their effects on database performance.