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Join the Preview!
APM Recommendations are in Preview. Features and recommendations may change before general availability. To request access, fill out this form.
APM Recommendations help you improve your applications’ performance and reliability by providing optimization opportunities based on the telemetry collected on your applications. These recommendations are designed to:
Identify and resolve performance bottlenecks
Improve service reliability and uptime
Reduce error rates and improve end-user experience
Prerequisites
Certain recommendations rely on specific Datadog products. Use the Recommendation Prerequisite dropdown to filter for the recommendations you can expect to see based on your specific setup.
How it works
APM Recommendations are based on data collected from different parts of your stack:
Sessions and user journeys from Real User Monitoring (RUM)
Distributed traces from Application Performance Monitoring (APM)
Error data from Error Tracking
Database telemetry from Database Monitoring (DBM)
By looking at these sources together, Datadog finds ways to help you improve performance, reliability, and user experience.
Datadog prioritizes recommendations by computing a severity score that weighs the potential impact of an issue against telemetry signals, such as relative request volume and performance trends. This ensures that the most critical insights for improving service health appear first.
Using APM Recommendations
To review recommendations that need your attention:
Select a recommendation from the list to see a detailed description of the issue.
Review the problem, impact, and Datadog’s recommendation for resolving it.
After you’ve reviewed the recommendation, you can use the FOR REVIEW dropdown to change the recommendation status to Reviewed, Ignored, or Resolved. Alternatively, you can click Create Ticket to assign the recommendation to an owner and track related work in Jira or Case Management.
Supported recommendations
Recommendation Category
Recommendation Type
Scope of Recommendation
Recommendation Description
Recommendation Prerequisite
Performance
N+1 Queries on Database
Backend services
A backend application calls the same database sequentially instead of batching queries.
APM
Performance
Repeated Sequential API calls
Backend services
A backend application repeatedly retries failing API calls without sufficient backoff, increasing system load and masking underlying reliability issues.
APM
Performance
Persistent Retries
Backend services
A backend application issues an excessive number of retry attempts when calling a downstream API, extending request duration and risking cascading failures under strain.
APM
Performance
Missing index
Databases
The query’s execution plan performs expensive sequential scans. When detected, Datadog recommends using an index to expedite the query.
APM + DBM
User experience
User frustration action
Browser applications
Common rage or dead actions are detected on elements on a page signaling misleading UI or broken elements.
RUM
User experience
Unoptimized bundle size
Browser applications and web views on mobile applications
Large JS resources causing delays in the initial page render signaling misleading UI or broken elements.
RUM
Reliability
High Exception Volumes
Backend services
A backend application is throwing a high number of exceptions as control-flow, adding CPU and memory overhead.
APM + Continuous Profiler
Further reading
Documentation, liens et articles supplémentaires utiles:
