For Agents
Query database load and wait-event data from Amazon RDS and Aurora instances by dimension, slice, and time range.
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the AWS Performance Insights, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
What an agent can do with AWS Performance Insights API.
Retrieve top dimension keys (SQL, host, user, wait event) contributing to DB load over a time window
Pull time-series resource metrics like db.load.avg and db.SQL.tokenized for an RDS or Aurora instance
Get detailed dimension metadata including full SQL text and execution plan for a specific dimension key
List the metrics available for a given Performance Insights resource
GET STARTED
Use for: I need to find the top SQL statements driving load on an RDS instance, Retrieve database load broken down by wait event for the last hour, Get the full SQL text for a specific dimension key from Performance Insights, List the metrics available for a Performance Insights resource
Not supported: Does not modify database configuration, kill sessions, or run SQL — use for read-only Performance Insights load and metric queries on RDS, Aurora, and DocumentDB only.
Jentic publishes the only available OpenAPI document for AWS Performance Insights, keeping it validated and agent-ready.
Jentic publishes the only available OpenAPI specification for AWS Performance Insights, keeping it validated and agent-ready. AWS Performance Insights is a database performance monitoring service that visualizes load on Amazon RDS, Aurora, and DocumentDB instances and lets you slice it by SQL, host, user, or wait event. The API exposes six query operations to retrieve dimension keys, time-series resource metrics, and metadata about which dimensions and metrics are available for a given DB engine. It is the programmatic surface behind the Performance Insights console for engineers who want to pull DB load data into their own dashboards, anomaly detection pipelines, or incident workflows.
Discover which dimensions can be queried for a database engine and metric combination
Read resource metadata such as feature support flags for a Performance Insights identifier
Patterns agents use AWS Performance Insights API for, with concrete tasks.
★ Slow-Query Investigation
Identify the SQL statements driving load on an Amazon RDS or Aurora instance during a slow-down. DescribeDimensionKeys returns the top db.sql_tokenized dimension keys ranked by db.load.avg over a time window, and GetDimensionKeyDetails fetches the full SQL text for any key. Engineers can build a 'top SQL during incident' view without opening the AWS console.
Call DescribeDimensionKeys for the RDS resource ARN with Metric 'db.load.avg', GroupBy db.sql_tokenized, StartTime 30 minutes ago, and EndTime now, then call GetDimensionKeyDetails on the top key to retrieve full SQL text
Wait-Event Analysis
Diagnose contention by grouping DB load by wait event over an incident window. DescribeDimensionKeys with GroupBy db.wait_event returns ranked wait events such as IO:DataFileRead or Lock:transactionid, letting an engineer or agent reason about whether the bottleneck is IO, locking, or CPU. Pair with GetResourceMetrics for the same window to see the load envelope.
Call DescribeDimensionKeys with GroupBy db.wait_event for the RDS resource over the last 60 minutes and return the top 10 wait events by db.load.avg
Custom DB Load Dashboards
Pull Performance Insights time-series into a custom dashboard or data warehouse. GetResourceMetrics returns db.load.avg and other metrics at a configurable PeriodInSeconds, optionally grouped by dimension. Teams who already centralize observability outside CloudWatch can ingest these series alongside their other DB telemetry for unified alerting.
Call GetResourceMetrics for the RDS resource with MetricQueries [{Metric: 'db.load.avg'}], StartTime 24 hours ago, EndTime now, and PeriodInSeconds 300
AI Agent DB Health Tool via Jentic
An incident-response agent uses Jentic to discover Performance Insights operations, load their schemas, and call them when a paged engineer asks 'what's wrong with the DB right now'. Jentic stores the AWS access key in its vault and signs each request with SigV4, so the agent can return ranked top-SQL and wait-event summaries without ever holding raw AWS credentials.
Use Jentic to search 'find top sql by load on rds', load DescribeDimensionKeys, and execute it for the affected RDS ARN with the last 30 minutes as the time range
6 endpoints — jentic publishes the only available openapi specification for aws performance insights, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
/#X-Amz-Target=PerformanceInsightsv20180227.DescribeDimensionKeys
Top dimension keys for a metric grouped by SQL, host, user, or wait event
/#X-Amz-Target=PerformanceInsightsv20180227.GetResourceMetrics
Time-series values for Performance Insights metrics on a resource
/#X-Amz-Target=PerformanceInsightsv20180227.GetDimensionKeyDetails
Full detail for a dimension key, including full SQL text
/#X-Amz-Target=PerformanceInsightsv20180227.ListAvailableResourceMetrics
List metrics available for a resource
/#X-Amz-Target=PerformanceInsightsv20180227.ListAvailableResourceDimensions
List dimensions available for a resource and metric
/#X-Amz-Target=PerformanceInsightsv20180227.GetResourceMetadata
Resource metadata and feature support flags
/#X-Amz-Target=PerformanceInsightsv20180227.DescribeDimensionKeys
Top dimension keys for a metric grouped by SQL, host, user, or wait event
/#X-Amz-Target=PerformanceInsightsv20180227.GetResourceMetrics
Time-series values for Performance Insights metrics on a resource
/#X-Amz-Target=PerformanceInsightsv20180227.GetDimensionKeyDetails
Full detail for a dimension key, including full SQL text
/#X-Amz-Target=PerformanceInsightsv20180227.ListAvailableResourceMetrics
List metrics available for a resource
/#X-Amz-Target=PerformanceInsightsv20180227.ListAvailableResourceDimensions
List dimensions available for a resource and metric
Three things that make agents converge on Jentic-routed access.
Credential isolation
AWS access keys are stored encrypted in the Jentic vault. SigV4 signatures are generated per request, so the agent never sees the raw secret access key.
Intent-based discovery
Agents search by intent (e.g., 'find top sql by load on rds') and Jentic returns the matching Performance Insights operation with its input schema and parameter constraints.
Time to first call
Direct integration: 1-2 days for AWS SDK setup, IAM scoping, and SigV4 signing. Through Jentic: under 30 minutes — search, load schema, execute.
Alternatives and complements available in the Jentic catalogue.
Amazon CloudWatch
Pair Performance Insights' fine-grained DB load with CloudWatch's instance-level CPU, memory, and IO metrics
Use CloudWatch for instance vitals and alerting; use Performance Insights when the agent needs SQL- or wait-event-level attribution of load.
AWS RDS Data API
Execute SQL surfaced by Performance Insights without managing a connection pool
After Performance Insights identifies a slow SQL statement on an Aurora Serverless cluster, use the RDS Data API to run EXPLAIN or remediation SQL.
Amazon Redshift Data API
Run SQL and inspect query history on Redshift, which has its own performance views rather than Performance Insights
Choose Redshift Data API when investigating Redshift workload performance; Performance Insights does not cover Redshift.
Specific to using AWS Performance Insights API through Jentic.
Why is there no official OpenAPI spec for AWS Performance Insights?
AWS does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call AWS Performance Insights via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.
What authentication does AWS Performance Insights use?
Performance Insights uses AWS SigV4 HMAC request signing with an AWS access key ID and secret. Through Jentic, AWS credentials live in the vault and SigV4 signatures are produced per call so the agent never holds raw secrets.
Can I retrieve the full SQL text behind a top dimension key?
Yes. After DescribeDimensionKeys returns a Key with a sql_tokenized dimension, call GetDimensionKeyDetails with the same identifier and dimension group to fetch the full SQL text and any redacted markers.
Which database engines does this API support?
Performance Insights supports Amazon RDS for MySQL, MariaDB, PostgreSQL, Oracle, SQL Server, Aurora MySQL, Aurora PostgreSQL, and Amazon DocumentDB. Performance Insights must be enabled on the instance for the API to return data.
What are the rate limits for the Performance Insights API?
Performance Insights enforces account-level request quotas per region; calls beyond the quota return a Throttling exception. AWS does not publish fixed per-second numbers, so back off and retry on Throttling responses and batch dimension queries with sensible PeriodInSeconds.
How do I find the top SQL on an RDS instance through Jentic?
Search Jentic for 'find top sql by load on rds', load DescribeDimensionKeys, and execute it with your RDS resource identifier, Metric 'db.load.avg', and GroupBy db.sql_tokenized. Install with pip install jentic; AWS keys are read from the Jentic vault.
/#X-Amz-Target=PerformanceInsightsv20180227.GetResourceMetadata
Resource metadata and feature support flags