Add helper functions for distributed micro benchmarks

[PranjalC100]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @PranjalC100, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a suite of Python helper modules designed to facilitate and automate distributed micro-benchmarking workflows on Google Cloud Platform. The new functionalities cover the entire lifecycle of a distributed benchmark, from setting up test environments and distributing workloads to collecting, aggregating, and reporting results. This significantly enhances the framework's capability to run complex, multi-VM benchmarks efficiently and reliably.

Highlights

• Gcloud Utilities: New gcloud_utils.py module for robust gcloud command execution, including retry logic and specific functions for Google Cloud Storage (GCS) and Compute Engine operations.
• Google Cloud Storage Operations: New gcs.py module providing high-level Google Cloud Storage interactions for benchmark artifacts, such as uploading/downloading JSON data, test cases, FIO job files, listing manifests, and checking for cancellation flags.
• Job Generation and Distribution: New job_generator.py module to automate the creation and distribution of benchmark jobs, supporting loading test cases/configurations from CSVs and generating comprehensive test matrices.
• Report Generation: New report_generator.py module for generating comprehensive benchmark reports in CSV format, with options for combined or separate reports and detailed metric formatting for FIO results.
• Result Aggregation: New result_aggregator.py module to collect and process FIO benchmark results from multiple distributed VMs, extracting key performance indicators like bandwidth and latency metrics.
• VM Management: New vm_manager.py module for orchestrating VM-related tasks, including listing running VMs, securely executing worker scripts via SSH, fetching logs, and monitoring benchmark completion with timeout and cancellation mechanisms.

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[gemini-code-assist]

Code Review

This pull request introduces a comprehensive set of helper modules for running distributed micro-benchmarks. The code is well-structured, with clear separation of concerns for interacting with gcloud/GCS, generating test jobs, aggregating results, and generating reports.

I've identified several issues, including a critical typo in an exception name, a few high-severity bugs that could lead to crashes or incorrect results (potential division by zero, incorrect metric aggregation, and malformed CSV output), and a potential file creation issue with unsanitized input. I've also included several medium-severity suggestions to improve error handling, code consistency, and adherence to Python style conventions (PEP 8), such as adding missing newlines at the end of files and improving documentation.

Overall, this is a solid foundation for the benchmarking framework. Addressing the identified issues will significantly improve its robustness and maintainability.

[gemini-code-assist]

The successful_vms counter is incremented for each successfully processed test, not for each VM. This will lead to an incorrect summary message at the end (e.g., "Successfully aggregated results from 100/10 VMs"). This counter should be incremented only once per VM, likely after its manifest has been successfully downloaded and opened.

[PranjalC100]

WIll have a look at this later.