AI Continues DevOps Expansion
AI gives us the potential to look through the clutter and pick out pieces of data that really matter. It’s no wonder, then, that AI is increasingly being used to target complex IT tasks, including DevOps.
For instance, the Swedish company CodeScene is finding success in using machine learning to analyze source code. The company’s offering, which is partly based on co-founder Adam Tornhill book “Your Code As A Crime Scene,” analyzes version control metadata over time to determine where “hot spots” in the code that companies should be paying more attention to.
CodeScene, which was founded in 2015, is owned by Empear AB and raised 30 million Swedish Kronor (about $3.6 million) earlier this year. Following the successful registration of a patent in the United States, CodeScene will be expanding its footprint to the U.S. in the summer of 2021, the company tells us.
Another one to watch is Haystack Analytics, a Y Combinator-based startup that is looking to mine GitHub data to boost software quality, remove bottlenecks, and optimize processes for development teams.
When development projects get bogged down or deliver subpar quality, it can be tough to know why. Haystack Analytics’s goal is to use data to identify exactly where the weak points are in the “delivery funnel” so that development teams can address the underlying cause.
The San Francisco-based company claims that customers are shipping releases 70% faster with its software. Last week it announced that it has secured $1.2 million in funding.
Speaking of code delivery processes, GitLab last week announced it has completed the acquisition of UnReview, a developer that uses machine learning that automatically identify the appropriate code reviewers. GitLab plans to apply it into its DevOps platform.
Three out of four DevOps professionals are either using machine learning and AI technology for testing and code review, or planning to use it, according to GitLab’s 2021 DevSecOps survey. The San Francisco-based company says this IT-specific trend parallels the larger business trend of automating AI and machine learning workloads with DataOps, MLOps, and ModelOps disciplines.
Businesses are investing in AI to automate code-related tasks to cut costs, says Jim Mercer, research director DevOps and DevSecOps at IDC.
“DevOps teams who can capitalize on cloud solutions that provide innovative technologies, such as machine learning, to remove friction from the DevOps pipeline while optimizing developer productivity are better positioned to improve code quality and security driving improved business outcomes,” Mercer says.