Amazon CloudWatch
by Amazon Web Services
Amazon CloudWatch collects metrics, alarms, log events and dashboards for AWS resources and applications, and Logs Insights runs queries over the logs. Retention there is priced by volume, so teams often keep less history than they would like. Keeping selected metrics and query results in your own Lake preserves the long view and lets you join operational signals with cost, deployments and incidents.
- Category
- IT, Security & Monitoring
- Type
- APM & observability
- Interface
- REST API
- Built with
- Connect Anything
- Credentials
- AWS access keys
02Data
What you can sync.
- Metrics
- Alarms
- Log events
- Dashboards
- Logs insights results
Join Amazon CloudWatch metrics with assets and people data to see risk by team, system and owner.
Need more? Name any other Amazon CloudWatch data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- AWS access keys
Amazon CloudWatch uses AWS access keys. You add the credentials once, when the AI asks for them, and it tells you where to create them in Amazon Web Services if you need help.
04Questions
Questions you can answer.
Once Amazon CloudWatch data is in your Lake, ask an AI Mind in plain words or build the answer in DataPrism BI.
- How often did each alarm fire last quarter, and how many of those firings led to an incident?
- How has p99 latency for each service changed from release to release?
- Which Lambda functions show rising error counts alongside rising invocation volume?
- What do Logs Insights error counts per service look like over the past year?
05How it works
How it works in DataMind.
-
Pick Amazon CloudWatch.
Open Lake, pick Amazon CloudWatch in the source picker and name the connection. Connect Anything opens with a ready prompt that points the AI at the Amazon CloudWatch API docs.
-
Answer a few questions.
The AI reads the Amazon CloudWatch documentation, then asks which credentials you will use, which data to sync (for example metrics and alarms), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
The connector agent writes a Python connector for Amazon CloudWatch, tests it against the live API and shows you sample rows. Then the data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
06Pairs
Works well with Amazon CloudWatch.
Sources teams join with Amazon CloudWatch in the Warehouse, each one connected the same way.
