Operations | Monitoring | ITSM | DevOps | Cloud

Sentry AI code review, now in beta: break production less

This could’ve been prevented. This should have been prevented. This too. We all hate getting tagged in PRs. The time, the blame for when you inevitably miss something, and constant “I wouldn’t have written it that way” feeling is just hard to shake. LLMs promised this would get easier. Promised they would do it for us. But as we’ve seen, we’re not there yet. But this is what Sentry does for a living. We catch bugs… in prod.

Agentic AI Becomes Essential: Why Adoption Is Accelerating and What Comes Next

The cautious optimism business leaders held towards AI agents has evolved into more widespread enthusiasm. In our last survey from April 2025, just over half (51%) of companies had deployed AI agents in their organization. Six months later, 75% of companies are deploying more than one agent, according to PagerDuty’s latest research.

Smarter AI Cost Optimization With Guardrails That Scale

AI adoption is reshaping how organizations innovate. It’s also driving cloud costs higher. CloudZero’s State Of AI Costs In 2025 report finds that for mature FinOps and engineering leaders, visibility into AI costs is a critical first step, but it’s not enough. To enable fast, responsible AI and machine learning innovation at scale, teams need pragmatic, flexible guardrails. They don’t need rigid budgets or knee-jerk shutdowns that slow progress or push teams into shadow ML.

Your Next Observability RFP is All Wrong. Why AI Changes Everything

AI-first observability addresses two of the most pressing troubleshooting challenges: complex IT environments and AI-generated code. But understanding how to implement AI in a way that brings ROI, requires cutting through the hype and maintaining realistic expectations, while keeping a forward-thinking vision. In this blog post, we bring practical tips for including AI in your next observability RFP. The article is based on a webinar held with Logz.io founders, CEO Tomer Levy and CTO Asaf Yigal.

{Unscripted} AI Verification and Rollback

Our first AI/ML capability, Continuous Verification, made Harness the first Continuous Delivery tool to understand observability telemetry and trigger rollbacks when deployments caused trouble. We knew we could do more to eliminate the friction involved in its setup. Deploying with confidence shouldn't require a coordination meeting between DevOps, SREs, and developers just to configure the right health checks. That’s why we’re introducing the next generation: AI Verification and Rollback. We’ve moved beyond just AI-powered analysis to AI-powered setup.

Future-proofing Singapore as an AI-first nation with Search AI

During the 2025 National Day Rally, Singapore’s Prime Minister Lawrence Wong announced a renewed commitment to empower Singaporean workers with AI and transform the nature of jobs as Singapore takes steps to adopt AI in business processes. He referenced an AI-powered orthopantomogram (OPG) scanner that flags dental conditions when analyzing X-rays, reducing the time taken for assessment from 15–20 minutes to 15–20 seconds.

Automate Your Infrastructure Analysis with Scheduled AI Reports

The least exciting part of an operations or SRE role is often the manual, repetitive task of generating reports. It’s the Monday morning scramble to summarize weekly infrastructure health for the team, or the end-of-quarter push to build a capacity planning document. This is boilerplate work that pulls you away from critical engineering tasks. We believe that if a process is repeatable, it should be automated. That’s why we’re introducing Scheduled AI Investigations and Insights.