AWS CodeCommit is a service that provides fully managed source control for hosting secure and scalable private Git repositories. The development team can use CodeCommit to store the program code and prepare for the CI/CD pipeline. CodeCommit integrates with other AWS services such as CodePipeline, CodeBuild, and CodeDeploy to automate the code build and deployment process.
References:
* [What Is AWS CodeCommit? - AWS CodeCommit]
* [AWS CodePipeline - AWS CodeCommit]

Comprehensive and Detailed Step-by-Step Explanation:
* Option D: Set up Amazon S3 Caching for CodeBuild:
* CodeBuild supports S3 caching to store intermediate build artifacts and dependencies. This reduces the time required to download dependencies during subsequent builds, effectively lowering costs and improving build performance.
* By using S3 caching, developers can optimize costs without changing the compute type or adding complexity.
* Why Other Options Are Incorrect:
* Option A:CodeBuild does not have a "reserved capacity fleet" option.
* Option B:AWS Lambda cannot be used as the compute mode for CodeBuild projects. CodeBuild uses its own managed build environments.
* Option C:CodeBuild already operates on an on-demand basis, so this does not address the need for optimization or reduced provisioning time.
References:
* AWS CodeBuild Caching Documentation

The requirement is to run a single analysis job once per day at a specific time, after branch offices have uploaded their daily reports. The most cost-effective and straightforward way to trigger a Lambda function on a fixed schedule is to use Amazon EventBridge scheduled rules (cron or rate expressions). With a scheduled rule, EventBridge invokes the Lambda function at the exact predefined time each day without requiring any continuously running resources, polling logic, or additional orchestration unless it is needed.
Option D fits perfectly: an EventBridge schedule is purpose-built for time-based triggers, and you pay only for the invocations and any EventBridge rule evaluations according to AWS pricing, with minimal operational overhead. The Lambda function will run exactly once each day and can then read all relevant objects from the S3 bucket and process them in a single pass as designed.
Option A (S3 event notifications) triggers the Lambda function per upload, which is not aligned with "single pass once per day." It could cause multiple invocations and additional cost and complexity (coordination, waiting for all branches, handling partial arrival). Option B (Step Functions) can schedule via EventBridge as well, but Step Functions introduces additional state machine costs and is unnecessary if the requirement is simply a scheduled single Lambda invocation. Option C is the least cost-effective: running continuously to
"wait" until a time wastes compute time and increases cost, and it is not an event-driven design.
Therefore, D is the most cost-effective solution: use an EventBridge scheduled rule to invoke the Lambda function once daily at the predefined time.

Amazon CloudWatch is the service that collects and stores logs from AWS Lambda functions. The developer can use CloudWatch Logs Insights to query and analyze the logs for errors and metrics. Option A is not correct because Amazon S3 is a storage service that does not store Lambda function logs. Option B is not correct because AWS CloudTrail is a service that records API calls and events for AWS services, not Lambda function logs. Option D is not correct because Amazon DynamoDB is a database service that does not store Lambda function logs.
References: AWS Lambda Monitoring, [CloudWatch Logs Insights]