Sentry announced the launch of Seer Agent, a new feature that enables developers to investigate and resolve production problems using natural language.
Seer Agent uses Sentry’s complete telemetry (errors, spans, logs, traces, and code context) to surface answers and connections that would take considerable time and deep insights for teams to find on their own. The launch marks a major addition to Sentry’s Seer platform and dramatically reduces the time spent debugging, so developers can get back to building what they want to build instead of chasing bugs.
Developers can ask Seer Agent questions like:
Why is this page slow?
What caused this spike?
What changed before this started?
“When something breaks in production, you’re working across errors, spans, logs, metrics, and more, simultaneously. The volume of data alone makes it hard to know where to start,” said Indragie Karunaratne, Senior Director of Engineering, Sentry. “Seer Agent queries all of the sources, connects the relevant signals, and identifies what went wrong and where. Investigations that used to take hours now take minutes.”
Seer Agent is built on three core capabilities:
- Natural language queries: Ask any question about your application without needing to know exactly where to look in Sentry.
- Connected context: Surface relationships across errors, spans, logs, traces, and code context that a developer might never have found through manual navigation.
- Agentic investigation: Walks developers through complex production problems by reasoning through evidence in real time, surfacing what matters from Sentry’s vast data.
In addition, Seer Agent is now available in Slack, allowing users to start an investigation by messaging Seer Agent in any channel. It makes the experience multi-player, by allowing anyone in the channel to query it, redirect mid-step, and add context the agent didn’t previously have. Alternatively, channel participants can watch the team go from incident to resolution as an observer to better learn the system.
“Most teams don’t struggle to know something’s broken. They struggle to know what to fix. Sentry has spent more than a decade building the production telemetry that answers that, and Seer is how we put it to work everywhere developers already are - powering the most complete root cause analysis, automations that hand fixes off to coding agents like Cursor and Claude Code, and opening up our data through MCP and the CLI,” said Milin Desai, CEO, Sentry. “In Slack, the investigation becomes multiplayer. The dev team can swarm an incident, redirect Seer mid-step, and leave the thread behind as a record of how it got solved. Seer Agent is one more way to engage with it.”
Seer Agent is available for all Sentry users while in beta.
The Latest
Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...
For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...
When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...