cloudwatch-get_metric_statistics
Retrieve CloudWatch metric statistics to monitor AWS resources like EC2, RDS, and Lambda functions with customizable time ranges, dimensions, and statistical calculations.
Instructions
Retrieve CloudWatch metric statistics with full configurability for monitoring AWS resources.
This tool fetches time-series data points for CloudWatch metrics, supporting custom statistics,
dimensions, and time ranges. Essential for monitoring EC2 instances, RDS databases, Lambda functions,
and other AWS services.
**Required Parameters:**
- profile_name (str): AWS profile name from ~/.aws/credentials
- region (str): AWS region (e.g., 'us-east-1', 'eu-west-1')
- metric_name (str): CloudWatch metric name (e.g., 'CPUUtilization', 'NetworkIn', 'DatabaseConnections')
- namespace (str): AWS service namespace (e.g., 'AWS/EC2', 'AWS/RDS', 'AWS/Lambda')
- start_time (str): Start time in ISO 8601 format (e.g., '2024-01-01T00:00:00Z')
- end_time (str): End time in ISO 8601 format (e.g., '2024-01-02T00:00:00Z')
- period (int): Data point interval in seconds (60, 300, 3600, etc. - must align with metric resolution)
**Optional Parameters:**
- statistics (List[str]): Standard statistics to calculate. Default: ['Average']
Options: 'Average', 'Sum', 'SampleCount', 'Maximum', 'Minimum'
Example: ['Average', 'Maximum'] for CPU utilization trends
- extended_statistics (List[str]): Percentile statistics for detailed analysis
Format: 'p{percentile}' (e.g., 'p99', 'p95', 'p90', 'p50')
Example: ['p99', 'p95'] for latency analysis
- dimensions (List[Dict[str, str]]): Filter metrics by specific resource attributes
Common dimension examples:
* EC2: [{'Name': 'InstanceId', 'Value': 'i-1234567890abcdef0'}]
* RDS: [{'Name': 'DBInstanceIdentifier', 'Value': 'mydb-instance'}]
* Lambda: [{'Name': 'FunctionName', 'Value': 'my-function'}]
* ELB: [{'Name': 'LoadBalancerName', 'Value': 'my-load-balancer'}]
- unit (str): Expected unit of measurement for validation
Common units: 'Seconds', 'Percent', 'Count', 'Bytes', 'Bits/Second'
**Common Use Cases:**
1. Monitor EC2 CPU: namespace='AWS/EC2', metric_name='CPUUtilization', statistics=['Average', 'Maximum']
2. Track RDS connections: namespace='AWS/RDS', metric_name='DatabaseConnections', statistics=['Average']
3. Lambda duration analysis: namespace='AWS/Lambda', metric_name='Duration', extended_statistics=['p99', 'p95']
4. ELB response times: namespace='AWS/ELB', metric_name='Latency', extended_statistics=['p95', 'p99']
**Time Range Guidelines:**
- For high-resolution metrics: Use 60-second periods, max 3 hours of data
- For standard metrics: Use 300-second periods, up to 15 days of data
- For long-term analysis: Use 3600-second periods, up to 455 days of data
Returns detailed metric data points with timestamps, values, and units for analysis and alerting.Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| profile_name | Yes | ||
| region | Yes | ||
| metric_name | Yes | ||
| namespace | Yes | ||
| start_time | Yes | ||
| end_time | Yes | ||
| period | Yes | ||
| statistics | No | ||
| extended_statistics | No | ||
| dimensions | No | ||
| unit | No |