Common Tanzu Observability time limits and best practices

This article applies to:

Visualizing Data/Querying/Alerting 

Product edition: All

Feature Category:  Query

 

Overview:

Tanzu Observability has some timeout limits which serve as guardrails to protect the overall customer experience. The intent of these limits is to ensure a user running expensive actions on the platform does not lead to degradation of the users' experience. This knowledge base article lists the common timeout limits the platform has implemented. 

 

Action

Timeout Limit

Explanation and Best Practice

Query

300s (5min)

When a user issues a query at Wavefront, the time limit for that query to complete is 300s or 5 minutes. If a query does not complete in this time, the chart/API times out.

 

Best practice: Use specific sources and/or point tags in the queries to drill down into specific data that is required.

Alert

60s (1min)

When the alerting service runs a query, the time limit it has to complete is 60s or 1 minute. Alerting service, by default, runs every minute so, if a query does not complete within a minute, the alert is rendered not functioning.

 

Best practice: Use specific sources and/or point tags in the queries to drill down into specific data that is required.

Dynamic Dashboard Variables

60s (1min)

Dynamic dashboard variables populate drop downs based on meta data of a query. If that query does not complete in 60s, it is cancelled by the server. The reason is that it can become a bottleneck in loading a dashboard and hence, leads to a ‘slow’ user experience.

 

Best practice: Use specific sources and/or point tags in the queries to drill down into specific data that is required.

Derived Metric

300s (5min)

Derived metrics are used to synthetically create metrics based on existing metrics and then reingested as regular metrics. The query that runs for a derived metric, like a regular query, has a 300s or 5 minute timeout.

 

Best practice: Use specific sources and/or point tags in the queries to drill down into specific data that is required.



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