Docker announced general availability of the Docker Desktop for Mac [Apple Silicon], enabling developers to leverage the advantages of the latest Macs powered by the M1 chip and extending the reach of their Docker collaborative application development platform to a new architecture.
Sourcegraph announced Batch Changes, a solution that allows enterprises to automate and track large-scale code changes across all repositories and code hosts.
In the same way that Big Data has disrupted data teams, Big Code is creating hurdles for enterprise engineering teams who struggle to navigate and make changes across increasingly large and complex codebases. Last year, over 800K developers used Sourcegraph to search and understand all of their code. With Batch Changes, enterprises can now automate large-scale code refactors, security fixes, and migrations across thousands of repositories.
To accelerate developer productivity and overcome the challenges of Big Code, some tech giants like Google developed internal proprietary tools to automate up to 70 percent of code changes. However, most enterprises lack the technology they need to make large-scale code changes and instead resort to manually creating and tracking thousands of pull requests.
“The sheer amount of code most enterprises have creates a massive drag on development velocity,” said Quinn Slack, Co-Founder and CEO of Sourcegraph. “When the developer experience is slow and painful, the pace of product development lags and the entire business suffers. Batch Changes closes the productivity gap by empowering enterprises to easily keep code up-to-date and pay down tech debt across every business unit, repository, and code host the company uses.”
Batch Changes provides developers with a declarative structure for finding and modifying code across thousands of repositories, and features a simple UI to help enterprises manage the resulting changesets through checks and code reviews, so they can be confident each change is merged.
By automating large-scale code changes, enterprises can:
- Reduce the time it takes to make large-scale code changes by 80%
- Increase speed and accuracy while reducing the risk of introducing breaking changes
- Improve code quality throughout the organization by reducing the risk of bugs or bad code making it to production
Instead of manually managing thousands of pull requests to remove legacy code, fixing critical security issues, or updating dependencies, enterprises can now automate large-scale code changes with Batch Changes. Enterprises can more effectively mitigate the challenges associated with Big Code, improve development velocity, and innovate faster.