terraform-aws-jaeger VS opentelemetry-lambda

It's really not that intense. I basically set up my last co's telemetry infrastructure all by myself, using terraform, otel-python, jaeger, and AWS elasticsearch.

This TF project does most of the heavy lift. https://github.com/telia-oss/terraform-aws-jaeger

I mean, sure, you can improve performance a bit by increasing the RAM/compute capacity on the Lambda. But it always adds a pretty steep overhead right now, no matter how much capacity you throw at it.

https://github.com/open-telemetry/opentelemetry-lambda/issue...

https://github.com/aws-observability/aws-otel-lambda/issues/...

OpenTelemetry AWS Lambda repository

With the sample apps from the opentelemetry-lambda repository the Lambda part itself was easy to implement. What took me some time was to provide the jaeger Fargate service with IaC ouside of an k8s environment. But with ECS and ServiceDiscovery that was easy in the end. This should be even more simple in an EKS environment with the jaegertracing helm-charts.

OpenTelemetry recently released https://github.com/open-telemetry/opentelemetry-lambda, but they also have this in the official docs https://opentelemetry.io/docs/instrumentation/js/serverless/. What do you consider to be the better option?

opentelemetry-lambda

You don’t have to create an opentelemetry configuration file such as this for each of your lambdas. In fact, you shouldn’t. In AWS, you can use Lambda Layers. You can define the OpenTelemetry tracing piece of code as a Lambda layer and use it in any Lambda you want. Furthermore, OpenTelemetry went ahead and implemented this opentelemetry-lambda layer for us. All we need to do is use it with our config.

Sorry you're having trouble working with the ADOT Lambda Layers :(. Have you had a chance to open an issue on the GitHub repo for OTel Lambda or ADOT Lambda? You should add your expected vs your actual output!