implement X-Ray tracing for end-to-end observability

[pymonger]

Purpose

The purpose of this PR is to provide end-to-end observability of requests as they go from triggers, to the initiator (router) through to evaluators. This PR integrates AWS X-Ray into initiator framework and provides examples of how to instrument triggers and evaluators with traces.

Proposed Changes

• updated lambda build scripts to install new dependency, aws_xray_sdk, to provide instrumentation tools to emit traces
• instrumented the lambda_handler_base() function to emit trace messages annotated with the payload information of the request
• restructured deployment of sns-sqs-lambda evaluator to allow for trace instrumentation
• instrument traces in evaluator examples: sns-sqs-lambda
• instrumented traces in cmr-query trigger example
• created version of scheduled-task trigger that includes trace instrumentation: scheduled-task-instrumented
• fix bug in constructing payload message in the scheduled-task trigger
• updated instructions for running end-to-end demo in README.md

Issues

• Initiators: High-level logging & Traceability of initiators/triggers events unity-cs#439

Testing

• see regression/unit testing results at https://github.com/unity-sds/unity-initiator/actions
• manually tested by running through the end-to-end demo documented in the README.md
• example trace map of 2 triggers (cmr-query and s3-bucket-notification), the initiator, and 2 evaluators (eval_airs_ingest and eval_nisar_ingest)
  
• screen recording of observing errors in a pipeline and tracing it through to cloudwatch logs: https://drive.google.com/file/d/1gmrzsUrw5RAS2ucbE8GTe1t8QrsbyKrQ/view?usp=drive_link
• screen recording of searching on trace annotations to filter down to a pipeline execution: https://drive.google.com/file/d/19HG8pbHq04r8yY37KyYHbKAmnLMVCQ2l/view?usp=drive_link

[galenatjpl]

looks good to me!