{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/2"}],"enrichment":{"capability":"Generates CloudWatch metrics embedded within structured log events, allowing you to visualize and alarm on custom metrics while preserving detailed event context for querying.","skillfed_tags":["aws-native","observability"],"use_cases":["Emit custom metrics from Lambda functions without custom batching or blocking network calls","Link metrics to high-cardinality context (request IDs, device IDs) queryable via CloudWatch Logs Insights","Monitor aggregated values across EC2, ECS, EKS, or on-premises compute while preserving detailed event logs","Track both standard (1-minute) and high-resolution (sub-minute) metrics from application code","Automatically capture environment metadata (Lambda version, instance IDs) alongside custom metrics"],"what_it_does":"aws-embedded-metrics is a Python library for publishing custom CloudWatch metrics alongside structured log events. It wraps metric emission in the Embedded Metric Format (EMF), which CloudWatch automatically extracts so you can visualize, alarm on, and aggregate metrics in real time without writing custom batching code or making blocking network requests. The library automatically injects environment metadata (Lambda version, EC2 instance IDs, etc.) into logs and supports both standard and high-resolution metrics.\n\nYou decorate your function with @metric_scope, then call methods like put_metric(), put_dimensions(), and set_property() on the metrics object to record values and context. The library handles flushing metrics to CloudWatch and formatting them according to EMF. It works across Lambda, EC2, ECS, EKS, and on-premises environments (the latter via CloudWatch Agent), and integrates with CloudWatch Logs Insights for querying high-cardinality context that wouldn't be suitable as metric dimensions.","worth_installing":"Yes. The package is production-stable, actively maintained, has low install friction, permissive licensing, and no known vulnerabilities. It solves a real AWS monitoring problem\u2014emitting custom metrics without blocking calls or external dependencies\u2014and is widely used (top 5000 PyPI packages). Install it if you need to publish CloudWatch metrics from Lambda or other AWS compute environments."},"id":"aws-embedded-metrics","links":{"html":"https://skillfed.io/packages/aws-embedded-metrics","md":"https://skillfed.io/packages/aws-embedded-metrics.md","pypi":"https://pypi.org/project/aws-embedded-metrics/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-03-27","license_spdx":null,"license_treatment":"permissive","name":"aws-embedded-metrics","python_support":"supports_current","summary":"AWS Embedded Metrics Package"},"popularity":{"monthly_downloads":1791041,"position":3555,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"3.5.0"}