Home / Companies / New Relic / Blog / Post Details
Content Deep Dive

Setting Up AWS Distro for OpenTelemetry with Container-Based Lambda Functions and New Relic

Blog post from New Relic

Post Details
Company
Date Published
Author
Zameer Fouzan, Lead Developer Relations Engineer
Word Count
1,581
Company Posts That Month
11
Language
English
Hacker News Points
-
Post removed?
No
Summary

AWS Distro for OpenTelemetry (ADOT) facilitates observability in serverless environments by providing a vendor-neutral method to collect and export telemetry, using OpenTelemetry APIs without locking into a specific backend. The traditional use of Lambda Layers for deploying ADOT is incompatible with containerized Lambda functions, necessitating an alternative method for integration. The solution involves embedding ADOT directly into the container image via a multi-stage Docker build, allowing telemetry data to be exported to New Relic. This process leverages the advantages of container images, such as larger package sizes, consistent CI/CD tooling, and control over runtime dependencies, while addressing the challenge of bypassing AWS's mechanism for injecting layer content. The approach involves downloading and extracting ADOT layer content during the Docker build, configuring the Serverless Application Model (SAM) template for environment variables, and integrating custom metrics and instrumentation for enhanced observability in New Relic. The guide highlights the benefits of combining container deployments with OpenTelemetry for deep, actionable telemetry, despite some operational overhead like cold starts and memory usage, and encourages developers to explore this integration further with resources provided.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
Serverless 29 707 172 77 -35%
OpenTelemetry 16 269 57 34 -21%
Observability 8 2,104 424 141 -21%
Vector Search 2 1,668 286 111 +15%
Use This Data

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.