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Sentry Releases Application Metrics

Sentry announced the general availability of Application Metrics. 

With this launch, Sentry’s observability suite is now comprehensive, giving engineering teams errors, traces, logs, and metrics in one place. Application Metrics is high-cardinality and trace-connected, built for application debugging.

With Sentry Application Metrics, a developer instruments checkout latency once and attaches whatever context is relevant — region, plan type, browser, product category, user ID. From that point forward, any combination of those dimensions can be queried on demand, with no predefined aggregations and no re-instrumentation required. When a new question emerges mid-incident, the data is already there. This is made possible by Sentry’s decision to store metric events in full rather than pre-aggregating them.

Every metric event retains a direct connection to the trace it was emitted from, meaning a spike in any chart is one click away from exemplar traces, logs, and errors connected by trace ID. With Sentry Metrics, there is no pivoting between tools, no manual correlation by timestamp, and no guesswork.

“Developers don’t just want to know that something broke, they want to know why. For years, the tools haven’t matched that desire. Developers would see a spike in a chart and hit a wall when investigating because that spike didn’t provide the right context to understand what happened. They would spend unnecessary time correlating data from different tools in an effort to fill in the missing context. Application Metrics is Sentry’s answer to that wall. We want every developer to have the ability to go from ‘something is wrong’ to ‘here is exactly what happened and why.’ One tool, full context, no wasted time,” said Alex Jillard, Senior Engineering Manager at Sentry.

Getting started requires no additional infrastructure. If you’re already using Sentry, you can add metrics with your existing Sentry SDK. Instrument the signals you care about and they appear alongside your existing errors, traces, and logs.

Sentry Application Metrics is available now.

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Sentry Releases Application Metrics

Sentry announced the general availability of Application Metrics. 

With this launch, Sentry’s observability suite is now comprehensive, giving engineering teams errors, traces, logs, and metrics in one place. Application Metrics is high-cardinality and trace-connected, built for application debugging.

With Sentry Application Metrics, a developer instruments checkout latency once and attaches whatever context is relevant — region, plan type, browser, product category, user ID. From that point forward, any combination of those dimensions can be queried on demand, with no predefined aggregations and no re-instrumentation required. When a new question emerges mid-incident, the data is already there. This is made possible by Sentry’s decision to store metric events in full rather than pre-aggregating them.

Every metric event retains a direct connection to the trace it was emitted from, meaning a spike in any chart is one click away from exemplar traces, logs, and errors connected by trace ID. With Sentry Metrics, there is no pivoting between tools, no manual correlation by timestamp, and no guesswork.

“Developers don’t just want to know that something broke, they want to know why. For years, the tools haven’t matched that desire. Developers would see a spike in a chart and hit a wall when investigating because that spike didn’t provide the right context to understand what happened. They would spend unnecessary time correlating data from different tools in an effort to fill in the missing context. Application Metrics is Sentry’s answer to that wall. We want every developer to have the ability to go from ‘something is wrong’ to ‘here is exactly what happened and why.’ One tool, full context, no wasted time,” said Alex Jillard, Senior Engineering Manager at Sentry.

Getting started requires no additional infrastructure. If you’re already using Sentry, you can add metrics with your existing Sentry SDK. Instrument the signals you care about and they appear alongside your existing errors, traces, and logs.

Sentry Application Metrics is available now.

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Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

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