Better availability and automated code reviews with ML
summary
Shows how to use AWS AI services and machine learning to automate code review and operational tasks for distributed applications, with the goal of improving application performance and availability. Describes reducing manual, error‑prone work across development and deployment pipelines by applying AWS ML/AI services to monitor and manage code and production readiness.
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chapters (12)
- 0:00Introduction
- 1:05A typical software workflow
- 2:04Challenges in the application lifecycle
- 3:42Amazon CodeGuru
- 4:32Strengthening different steps in the application development cycle
- 5:14Add CodeGuru to the software workflow
- 5:49A typical code review process is manual and increases complexity
- 6:43CodeGuru Reviewer automates code review
- 7:42Benefits of CodeGuru Reviewer
- 10:09What if we have a system that...
- 10:40Benefits of CodeGuru Profiler
- 15:54Learn ML with AWS Training and Certification
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