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APM Recommendations help you improve your applications’ performance and reliability by surfacing optimization opportunities from your collected telemetry. These recommendations are designed to:
Identify and resolve performance bottlenecks
Improve service reliability and uptime
Improve end-user experience
Prerequisites
Certain recommendations rely on specific Datadog products. Use the Recommendation Prerequisite dropdown to filter recommendations by the Datadog products in your setup.
How it works
APM Recommendations are based on data collected from different parts of your stack:
Distributed traces from Application Performance Monitoring (APM)
Database telemetry from Database Monitoring (DBM)
Sessions and user journeys from Real User Monitoring (RUM)
Datadog correlates these sources to identify opportunities to improve performance, reliability, and user experience.
Datadog ranks recommendations by computing a priority score that weighs the potential impact of an issue against telemetry signals, such as relative request volume and performance trends. The most critical insights for improving service reliability and performance 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 assign the recommendation to an owner and track related work in Case Management or Jira.
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
Performance
Unbalanced Read Load
Databases
A service is making read-only queries to a primary database instance when replicas are available. Routing these queries to replicas can reduce primary load and improve performance.
APM + DBM
Reliability
Aggressive Retries
Backend services
A backend application triggers rapid-fire retry attempts without adequate backoff, sustaining high pressure on struggling dependencies and risking prolonged outages by preventing system recovery during transient failures.
APM
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
Note: If you use both APM and Database Monitoring (DBM), you may see fewer Missing Index recommendations here than on the DBM Recommendations page. APM Recommendations only surface Missing Index issues that Datadog can associate with an instrumented application service. Missing Index recommendations that cannot be linked to a specific service appear only in DBM.
