Tamás Bazsonyi
Engineering Velocity in the Age of AI: Lessons from Mobile CI/CD
#1about 1 minute
Calculating the business value of faster CI/CD builds
A cost-benefit analysis shows how a 20-minute reduction in build time can save a 10-person team up to €250,000 annually.
#2about 3 minutes
Using AI to identify pipeline optimization opportunities
An AI assistant analyzes a project's CI/CD setup and suggests three key areas for improvement: parallelization, caching, and workflow splitting.
#3about 4 minutes
Improving build speed with Gradle parallelization
Enabling the Gradle parallel flag significantly reduces build times, especially when paired with larger virtual machines that can handle the increased CPU load.
#4about 6 minutes
Implementing remote and dependency build caching
Using a co-located remote build cache can improve build times by up to 95% in ideal scenarios by reusing previously generated outputs.
#5about 4 minutes
Analyzing and debugging build cache performance
Use critical path analysis and diagnostic builds to identify cache misses and optimize task cachability for better performance.
#6about 3 minutes
Accelerating tests by parallelizing workflows and sharding
Splitting test suites into parallel shards and using distributed test execution can dramatically reduce the total time spent on testing.
#7about 2 minutes
Exploring other AI use cases in the development lifecycle
Beyond CI/CD optimization, AI can also be used to automate code reviews and act as a debugging assistant by analyzing logs and suggesting solutions.
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