CodeSee updated its code visibility platform to enable instant mapping of application services, directories, file dependencies and code changes.
CodeSee CEO Shanea Leven said CodeSee Enterprise 2.0 should extend the appeal of the platform beyond developers to include software engineers managing DevOps workflows.
CodeSee Enterprise 2.0 provides real-time visibility across multiple repositories regardless of whether the application is a monolith or based on a microservices architecture, she noted.
In addition, a Code Automations module enables developers to set granular conditions and actions down to the function level, requiring checklists to be complete before allowing developers to move on.
CodeSee Maps now includes the ability to click to view code directly, while a streamlined Review Maps module has decreased code review time by 30%. Developers can easily share maps to discuss proposed changes or keep necessary code changes as automatic permanent artifacts.
Finally, CodeSee is making available a dedicated solutions engineering team that provides guidance to connect an organization’s Datadog or OpenTelemetry trace data to CodeSee in less than an hour without storing code or having to first dive deep into traces, noted Leven.
The core open source CodeSee tool was created because it takes too long today for most developers to pore over a codebase to understand where they might contribute. The larger a codebase becomes, the longer it takes for a developer or software engineer to be onboarded to a new project.
The overall goal is to improve developer productivity, noted Leven. That’s become a critical issue because many organizations are hesitant to hire additional developers during uncertain economic times; they first want to ensure they maximize the utilization of the teams they already have.
Application development, of course, is now a team sport. The days when a lone developer cared for an entire application are long over. The issue is finding a way for teams of developers to collaborate more easily in an era where many of them may never have met in person.
In the longer term, Leven said she also expects that generative artificial intelligence (AI) platforms such as ChatGPT will supplement code visualization tools. Many developers are already starting to use these tools to help generate code faster. That code should, in theory, have fewer errors because it has essentially been copied from other previously validated sources. CodeSee provides a means to visualize that code before deploying it to ensure it will function as promised in increasingly complex application environments.
One way or another, the tools being provided to developers to boost productivity are advancing. It’s not clear what metrics should be employed to track developer productivity, but the amount of code simultaneously moving through DevOps workflows is going to increase. The challenge DevOps teams face now is keeping track of all the dependencies that exist in that code as application environments are continuously updated.