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Answer: Modify the CodePipeline configuration to run actions for each Lambda function in parallel by specifying the same runOrder.
The correct answer is C. Modifying the CodePipeline configuration to run actions for each Lambda function in parallel by specifying the same runOrder will significantly improve the pipeline's completion time. This approach leverages parallel execution, allowing multiple Lambda functions to be built and deployed simultaneously, thus speeding up the overall process. The runOrder parameter in CodePipeline allows actions with the same runOrder to run in parallel, effectively reducing the total time required for the pipeline to complete.
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A DevOps engineer has developed a CI/CD pipeline for an application comprising five independent AWS Lambda functions. The pipeline, utilizing AWS CodePipeline and AWS CodeBuild, sequentially builds, tests, packages, and deploys each Lambda function. It is triggered by an Amazon EventBridge rule to initiate promptly upon source code changes. However, the engineer has observed that the pipeline's completion time is excessive. What strategy should the engineer adopt to enhance the pipeline's efficiency?
A
Modify the CodeBuild projects within the pipeline to use a compute type with more available network throughput.
B
Create a custom CodeBuild execution environment that includes a symmetric multiprocessing configuration to run the builds in parallel.
C
Modify the CodePipeline configuration to run actions for each Lambda function in parallel by specifying the same runOrder.
D
Modify each CodeBuild project to run within a VPC and use dedicated instances to increase throughput.
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