Rollbar to improve code with new AI-assisted workflows and automation-grade grouping

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Rollbar wants to shift developers’ focus to continuously improving code, instead of having to continuously fix it. The continuous code improvement platform provider announced two new features designed to reduce the time spent monitoring, investigating and debugging code. 

The new AI-assisted workflows are automated workflows that help development teams catch and address errors before they reach users. 

Automation-grade grouping is the next-generation of Rollbar’s grouping engine, and provides the foundation of the AI-assisted workflows, and automatically groups similar errors. 

“Our AI-assisted workflows, powered by our automation-grade grouping, are an industry first to reduce the daily noise and manual work of fixing code for developers so they can focus on building and innovating,” said Brian Rue, CEO and co-founder of Rollbar. “Our investment in these automation features and our Continuous Code Improvement Platform – along with our company expansion, growing customer base, recent Series B funding, and new visual brand identity – highlight our commitment to help developers build software quickly and painlessly.”

With today’s announcement, Rollbar is announcing three AI-assisted workflows that are now available. 

  1. Rollbar toolkit for Kubernetes with integrations with Prometheus, Kubernetes, and Weaveworks Flagger. “This allows development teams to automate decision making for progressive deployments of new code versions using Rollbar data on unique new errors and regressions,” Lubos Parobek, who is on the product management team at Rollbar, wrote in a blog post.
  2. Automated feature flag triggers with LaunchDarkly integrations. This workflow will allow teams to automatically turn off feature flags with a kill switch. It features progressive delivery, test in production, proactive monitoring and A/B testing.
  3. Automated issue tracking with integration for issue tracking tools such as Hira, GitHub, and Clubhouse. “The difference now is that tickets can be automatically created for any new or critical error. Set up predetermined rules to have control over how tickets are automatically generated, Parobek wrote. 

Rollbar’s new automation-grade grouping uses machine learning to find patterns and identify unique errors in real time. It is currently available for Ruby, JavaScript, Java and Python. The company is working on support for Go, PHP and C#. 

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