![]() Since values over 1.0 indicate over-utilization, you want to know before the load gets to that number. If this value is high, you can get less consistent query execution times and longer wait times. Values under 1.0 indicate that CPUs spent time idle during the given window. A load over 1.0 indicates that processes had to wait for CPU time in the given window (with higher values indicating more time spent by processes waiting). Heroku’s reported load metrics are normalized by dividing the system load by the number of CPUs.Ī load average of 1.0 over a given time window indicates full utilization of all CPUs. The load-avg metric shows average CPU load over the indicated periods. Additionally, knowing what statements cause blocks can help to identify application code that can be optimized to reduce locks. The blocking queries can then be terminated in order to resolve lock contention. You can use the pg-extras CLI plugin to help identify queries that are preventing other operations from taking place. Set up an alert for when there are any connections waiting for five consecutive minutes. Occasional lock waits are expected, but sustained lock waits can be a sign of mishandled database concurrency. The waiting-connections metric shows how many connections are waiting on database locks before they can proceed. ![]() Refer to the PgBouncer Configuration best practices document for more information. If you’re routinely approaching your connection limit, consider using connection pooling. For tier-3 plans and higher, the maximum is 500 connections, so 400 and 450 are good warning and critical numbers to start with here. Set up an alert for when the connection count approaches its hard maximum.Consider +50/+100 over your normal daily maximum. Alerting thresholds are dependent on your application’s connection count range, assessed under normal operating conditions. Significant changes from baseline connection numbers could be a sign of increased query and/or transaction run times. Set up an alert for sudden, large changes to the current connection count.There are two strategies for setting up alerts based on database connection counts: After that limit is reached no new connections can be created. Heroku Postgres enforces a connection limit in order to optimize Postgres memory usage and scaling.įor Heroku Postgres plans tier-3 and higher there’s a hard limit of 500 connections. The active-connections metric lists the number of established connections to your database. If you get close to maximum size, either upgrade your plan or delete data to stay within plan limits. We recommend setting a warning alert when your database gets to 80% of the allotted size for your plan and a critical alert when it gets to 90% of the allotted size. Set alerts based on your plans limit to give you some advanced notice if you start approaching it. In some cases, we set an enforcement date when you’re allowed only a single database connection and access is restricted to READ, DELETE, and TRUNCATE access until the database in back under the plan limit. If your Postgres database grows past the size allotted for your plan, you receive a warning email with directions on how to fix the issue. The db_size metric is the size of the database, including all table and index data, as well as database bloat. The following metrics have alerts set up to provide meaningful alarms pertaining to database health: db_size For details, see Monitoring Your App on Heroku.įor a full list of provided metrics, see Heroku Postgres Metrics Logs. Platform monitoring add-ons also provide insights on your apps and dynos.
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