# tracing Tracing is an observability technique for representing the path of a request through an application as correlated spans. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Atlassian Automates Root Cause Analysis by Correlating Metrics, Logs and Traces DevFeed: [Atlassian Automates Root Cause Analysis by Correlating Metrics, Logs and Traces]() Original publisher: [Read original article]() Author: Craig Risi Published: 2026-09-15T12:00:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [incident](), [atlassian](), [telemetry](), [SIEM, Security, Observability](), [tracing](), [Cloud Native Ecosystem](), [OpenTelemetry]() Tags: [atlassian](), [atlassian-automated-rca](), [cloud-native](), [defects](), [devops](), [distributed](), [incident](), [incident-response](), [logging](), [logs](), [metrics](), [news](), [opentelemetry](), [root-cause-analysis](), [services](), [telemetry](), [traces](), [tracing]() ### AI overview Atlassian has outlined an approach to automating root cause analysis for large-scale cloud-native incidents. It correlates metrics, logs, distributed traces, and service topology to detect anomalies, align them in time, trace dependencies, and produce ranked hypotheses about likely fault origins and propagation paths. ### Source excerpt Atlassian has outlined a new approach to automating root cause analysis for large-scale cloud-native incidents, using correlation across metrics, logs, distributed traces, and service topology to generate ranked hypotheses about where failures originate and how they propagate. By Craig Risi ## It passed CI. It passed your evals. The customer still got the wrong answer. DevFeed: [It passed CI. It passed your evals. The customer still got the wrong answer.]() Original publisher: [Read original article]() Author: Sean O'Dell Published: 2026-09-13T14:00:00Z Content type: article Language: en Sources: [The New Stack]() Topics: [AI Agent](), [agent observability](), [observability](), [tracing](), [dynatrace](), [ci](), [coding]() Tags: [ai](), [ai-agent](), [ai-agents](), [ai-engineering](), [ci](), [coding](), [dynatrace](), [observability](), [post-contributed](), [sponsor-dynatrace](), [sponsored](), [sponsored-post-contributed](), [traces]() ### AI overview The article explains how AI-agent failures can pass CI and evaluations while still producing slow or incorrect customer-facing results. It presents distributed traces and agent trajectories--model calls, tool calls, arguments, and results--as evidence for debugging retrieval behavior, release context, and feature-flag state. ### Source excerpt A diff is not evidence. It's a statement of intent. The tests passed. The review's done. The change is live. The post It passed CI. It passed your evals. The customer still got the wrong answer. appeared first on The New Stack. ## Wrapture: a Python package for monkey patching, testing, and observability DevFeed: [Wrapture: a Python package for monkey patching, testing, and observability]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-09-11T13:51:32Z Content type: opinion Language: en Sources: [Simon Willison's Weblog]() Topics: [Python](), [Testing](), [observability](), [Instrumentation](), [tracing](), [OpenTelemetry](), [Flask](), [jupyterlab]() Tags: [code](), [graham-dumpleton](), [graham-dumpleton-6](), [how-to](), [instrumentation](), [monkey-patching](), [monkey-patching-10](), [observability](), [observability-10](), [open-source](), [open-source-320](), [opentelemetry](), [python](), [python-1-283](), [testing](), [testing-95](), [tracing]() ### AI overview This article reviews wrapture, an alpha Python package by Graham Dumpleton for monkey patching, unit testing, call recording, live and zero-code tracing, timing analysis, and OpenTelemetry export. It highlights tutorials and JupyterLab workshops covering the package and related instrumentation. ### Source excerpt Graham Dumpleton's new monkey patching package wrapture is shaping up to be an indispensable tool for Python developers. I'm not sure why I've seen so little buzz about it! Graham has been posting new tutorials for it almost daily since the initial release on August 31st. Here's everything he's published so far: Introducing wrapture - a new monkey patching library that serves both testing and observability (think New Relic style tracing) at the same time. Unit testing with wrapture - how to use it for the same kinds of thing as unittest.mock. Recording calls with wrapture - recording method calls as timelines and processing and displaying them as trees. Phased behaviour in wrapture - arranging patched methods to change behavior across multiple calls. Beyond callables in wrapture - monkey patching attributes, dictionaries, generators. Live tracing with wrapture - tracing a live application to see exactly how it works. Zero-code tracing with wrapture - configuring tracing in a separate TOML file without modifying Python code at all. Tracing Flask with wrapture - using the separate wrapture-instrumenation package to instrument a Flask application. That package also provides instrumentation for aiohttp.client, aiohttp.web, django, fastapi, flask, grpc, http.client, httpx, jinja2, requests, sqlalchemy, sqlite3, starlette, urllib.request, urllib3, uvicorn, werkzeug.serving, wsgiref.simple_server, xmlrpc.client, xmlrpc.server. Finding slow code with wrapture - wrapture's tools for recording timing information, both individually and aggregated across multiple calls. OpenTelemetry export in wrapture - exporting traces to OpenTelemetry. Graham also has a set of interactive workshops for wrapture, implemented as JupyterLab notebooks. Wrapture is still alpha software but it's already very usable - especially given you can configure and try it out with a TOML file without modifying any Python code at all. This feels like one of those Swiss Army Knife packages that, once mastered ## OpenTelemetry proposes environment variables for context propagation across processes DevFeed: [OpenTelemetry proposes environment variables for context propagation across processes]() Original publisher: [Read original article]() Author: OpenTelemetry Authors; Docs CC BY Published: 2026-09-11T11:01:22Z Content type: article Language: en Sources: [Blog on OpenTelemetry]() Topics: [context](), [tracing](), [OpenTelemetry](), [Processes](), [CI/CD](), [data-processing]() Tags: [ci-cd](), [data-processing](), [environment-variables](), [opentelemetry](), [processes](), [spans](), [tracing](), [w3c]() ### AI overview The OpenTelemetry Specification has a release candidate for using environment variables to carry trace context and baggage between processes. The article explains how this can connect spans across workflow runners, shells, build tools, test processes, and similar workloads when protocol headers or message metadata are unavailable, and requests feedback before the specification becomes Stable. ### Source excerpt A trace does not always cross a network boundary. A workflow runner starts a shell, the shell launches a build tool, and the build tool starts test processes. Batch and data-processing systems create similar chains of child processes. Without a shared way to pass trace information across these boundaries, spans from each process can end up in separate traces. If context propagation is new to you, it is the mechanism that carries information from one service or process to the next. For tracing, this includes the trace and span identifiers that let new spans join the same trace. It can also carry baggage: application-defined key-value pairs that are passed to downstream work. ## Debugging our AI search assistant with agent tracing DevFeed: [Debugging our AI search assistant with agent tracing]() Original publisher: [Read original article]() Author: Dominik Buszowiecki; Shaun Kaasten Published: 2026-09-11T09:00:00Z Content type: article Language: en Sources: [Sentry Blog]() Topics: [AI search](), [agent observability](), [debugging](), [tracing](), [Large Language Model]() Tags: [agent](), [ai](), [api](), [debugging](), [errors](), [eval](), [llm](), [search](), [sentry](), [tracing]() ### AI overview Sentry engineers describe how they debugged the Search Query Assistant, which converts natural-language prompts into Sentry Syntax queries. They used evals for performance measurement and AI Conversation tracing to investigate failures, including a bug involving custom numerical attributes that caused queries to return no results. ### Source excerpt See how Sentry engineers used AI Conversations to debug a natural language search assistant and fix a tricky query generation bug. ## How Heurist Finance built an AI-native investment workbench on Amazon Bedrock AgentCore DevFeed: [How Heurist Finance built an AI-native investment workbench on Amazon Bedrock AgentCore]() Original publisher: [Read original article]() Author: JW Wang Published: 2026-09-09T18:11:12Z Content type: article Language: en Sources: [Artificial Intelligence]() Topics: [Amazon Bedrock](), [Claude](), [Orchestration](), [tracing]() Tags: [advanced-300](), [agent](), [ai](), [amazon-bedrock-agentcore](), [anthropic-claude](), [customer-solutions](), [identity](), [memory](), [observability](), [sandbox](), [tracing]() ### AI overview Heurist Finance uses Amazon Bedrock AgentCore to run a conversational investment workbench that accesses premium data per query and produces auditable, personalized research responses. ### Source excerpt Learn how Heurist built Heurist Finance, a conversational AI investment workbench, on Amazon Bedrock AgentCore. This customer story shows how AgentCore payments, Identity, Memory, Code Interpreter, and Observability let a small team buy premium market data per query, isolate analysis in a sandbox, and keep every action auditable. ## Making Rust observability reliable at scale with OpenTelemetry DevFeed: [Making Rust observability reliable at scale with OpenTelemetry]() Original publisher: [Read original article]() Author: Björn Antonsson; Paul Le Grand des Cloizeaux; Scott Gerring Published: 2026-09-01T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [tracing](), [telemetry](), [Traces](), [Instrumentation]() Tags: [apm](), [instrumentation](), [latency](), [observability](), [opentelemetry](), [production](), [rust](), [scale](), [traces](), [tracing]() ### AI overview Datadog describes building an opinionated Rust tracer on OpenTelemetry to improve trace propagation, sampling consistency, and trace quality in production services. ### Source excerpt Learn how Datadog improved Rust tracing by building an opinionated OpenTelemetry-based library to help ensure consistent sampling, propagation, and trace quality at scale. ## Closing the AI agent trust gap with graduated autonomy DevFeed: [Closing the AI agent trust gap with graduated autonomy]() Original publisher: [Read original article]() Author: Dev Arora Published: 2026-08-26T17:33:03Z Content type: article Language: en Sources: [AWS Architecture Blog]() Topics: [Artificial Intelligence](), [AI Agent](), [Authorization](), [Amazon Bedrock](), [Amazon Web Services](), [Large Language Model](), [tracing](), [configuration](), [Provisioning]() Tags: [agent](), [agents](), [ai](), [ai-agent](), [ai-agents](), [amazon](), [amazon-bedrock](), [amazon-bedrock-agentcore](), [api](), [aws](), [compliance](), [evaluation](), [infrastructure](), [large-language-model](), [logs](), [model](), [policy](), [production](), [thought-leadership](), [tracing]() ### AI overview This article presents graduated autonomy as an architectural pattern for closing the trust gap in AI agents. Agents gain permissions through sustained reliability and lose them when performance degrades, using trust scoring, autonomy tiers, pre- and post-execution controls, policy enforcement, provenance, reversibility, and delivery gates. The design uses Amazon Bedrock AgentCore, Amazon DynamoDB, and AWS CodePipeline. ### Source excerpt Most teams give AI agents either full access or read-only, leaving value unused or risk unmanaged. This post describes graduated autonomy, an architectural pattern in which agents earn expanded permissions through sustained reliability and lose them when performance degrades, built on Amazon Bedrock AgentCore, Amazon DynamoDB, and AWS CodePipeline. ## Monitor Azure Functions across every hosting plan with Datadog DevFeed: [Monitor Azure Functions across every hosting plan with Datadog]() Original publisher: [Read original article]() Author: Duncan Harvey; Kathie Huang; Piyali Banerjee Published: 2026-08-24T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Azure](), [serverless monitoring](), [Serverless](), [telemetry](), [tracing](), [Traces](), [Application Performance Management (APM)](), [cpu](), [Node.js](), [Python](), [.NET]() Tags: [apm](), [azure](), [azure-functions](), [cpu](), [digital-experience-monitoring](), [metrics](), [monitor](), [monitoring](), [net](), [node-js](), [observability](), [performance](), [python](), [serverless](), [serverless-monitoring](), [telemetry](), [traces](), [tracing]() ### AI overview Datadog Serverless Monitoring expands observability for Azure Functions across Linux and Windows hosting plans, with telemetry collection, distributed tracing, enhanced CPU metrics, and continuous profiling. ### Source excerpt Trace requests, get enhanced CPU metrics, and profile code across Azure Functions hosting plans with Datadog Serverless Monitoring. ## Always-on tracing for production and preview traffic DevFeed: [Always-on tracing for production and preview traffic]() Original publisher: [Read original article]() Author: wits Published: 2026-08-21T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [tracing](), [Traces](), [Vercel](), [Command-line interface](), [telemetry]() Tags: [cli](), [debug](), [infrastructure](), [logs](), [traces](), [tracing](), [vercel]() ### AI overview Vercel introduces always-on tracing for production and preview traffic, allowing teams to debug real user requests through continuously collected, sampled traces. Sampling rules control collection by environment and path, with CLI management, automatic infrastructure and outbound fetch spans, optional framework and custom instrumentation through @vercel/otel, and trace viewing in Logs or via the CLI. ### Source excerpt With always-on tracing, you can now debug your real user requests without reproducing them. Always-on tracing continuously collects traces from your production and preview traffic. Unlike session tracing, which only captures requests from your own browser, it samples your live traffic. You control what's collected with sampling rules. Each rule sets a trace rate for an environment (All, Production, or Preview), optionally scoped to a path prefix like /checkout. Nothing is collected until you add a rule, so you pay only for what you choose to trace. You can also manage sampling rules from the CLI. vercel traces config set adds a rule, or changes the rate of an existing one when you run it again with the same environment and path prefix: Infrastructure and outbound fetch spans are captured automatically. To add framework and custom spans, instrument your app with @vercel/otel. To view a trace, open the Logs or run vercel traces get . Always-on tracing is is now in beta and available to teams on all plans. Tracing is priced at $0.50 per 1M span units. Traces follow your runtime log retention: 1 hour on Hobby, 1 day on Pro and 3 days on Enterprise. Get started by adding a rule in Settings -> Tracing or from the settings icon in Logs. Learn more in the documentation. Read more ## Control trace volume with OpenTelemetry tail-based sampling DevFeed: [Control trace volume with OpenTelemetry tail-based sampling]() Original publisher: [Read original article]() Author: Bill Meyer; Eddie Cai Published: 2026-08-21T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [OpenTelemetry](), [Traces](), [tracing](), [observability](), [Application Performance Management (APM)](), [configuration](), [Latency]() Tags: [apm](), [architecture](), [distributed-systems](), [how-to](), [latency](), [learn](), [metrics](), [observability](), [opentelemetry](), [rideshare](), [synthetic](), [traces]() ### AI overview A guide to using OpenTelemetry tail-based sampling to reduce exported trace volume while retaining errors, slow requests, and other diagnostically valuable traces. It explains the difference between head- and tail-based sampling, the role of Span Metrics, and the collector architecture required to evaluate complete traces. ### Source excerpt Learn how to configure tail-based sampling in the OpenTelemetry Collector to drop noisy traces, keep the ones that matter, and control APM costs. ## Connect client traces to your logs DevFeed: [Connect client traces to your logs]() Original publisher: [Read original article]() Author: Katerina Skroumpelou; Steven Eubank Published: 2026-08-18T07:00:00Z Content type: tutorial Language: en Sources: [Supabase Blog]() Topics: [Supabase](), [tracing](), [OpenTelemetry](), [client](), [Amazon API Gateway](), [browser](), [SIEM, Security, Observability]() Tags: [api](), [backend](), [browser](), [how-to](), [integration](), [opentelemetry](), [traces](), [tracing]() ### AI overview A walkthrough of connecting client-side traces to Supabase logs by propagating W3C Trace Context. It explains how to configure a tracer and client propagation so requests can be followed from the browser through Supabase's API Gateway and Edge Function logs, including with external log backends. ### Source excerpt supabase-js now propagates W3C Trace Context to Supabase, so a client trace and the matching Supabase log share one trace_id. ## Observability best practices for Lambda durable functions DevFeed: [Observability best practices for Lambda durable functions]() Original publisher: [Read original article]() Author: D Surya Sai Published: 2026-08-14T12:49:49Z Content type: tutorial Language: en Sources: [AWS Compute Blog]() Topics: [AWS Lambda](), [observability](), [Monitoring](), [log management](), [tracing](), [Instrumentation](), [debugging](), [Amazon API Gateway](), [stripe](), [Serverless]() Tags: [advanced-300](), [amazon-api-gateway](), [aws](), [aws-lambda](), [debugging](), [instrumentation](), [logging](), [metrics](), [monitoring](), [observability](), [payment](), [payment-processing](), [payments](), [serverless](), [technical-how-to](), [tracing]() ### AI overview This tutorial presents an observability pattern for AWS Lambda durable functions using a Stripe payment-processing workflow. It covers durable-function metrics, custom business metrics, alarms, structured logging, AWS X-Ray tracing, instrumentation across suspension boundaries, and end-to-end debugging of callback timeouts. ### Source excerpt Learn observability best practices for AWS Lambda durable functions, including CloudWatch metrics, custom alarms, structured logging, and X-Ray tracing for debugging callback timeouts end-to-end. ## Automated agent triage with Agent Tracing and Claude Routines DevFeed: [Automated agent triage with Agent Tracing and Claude Routines]() Original publisher: [Read original article]() Author: Trevor Elkins Published: 2026-08-13T09:00:00Z Content type: article Language: en Sources: [Sentry Blog]() Topics: [Claude](), [AI Agent](), [tracing](), [Model Context Protocol](), [agent observability]() Tags: [agent](), [ai-agent](), [claude](), [mcp](), [model-context-protocol-server](), [report](), [tool](), [tracing]() ### AI overview Sentry describes a Claude Routine that uses the Sentry MCP to query Agent Tracing data from roughly 800 overnight AI agent conversations. It aggregates error statistics, samples traces and conversations, reviews the Seer codebase, and files new Linear tickets for findings that are not already tracked. ### Source excerpt How Sentry uses a Claude Routine and the Sentry MCP to automatically triage 800 AI agent conversations overnight and file bugs. ## What's new in Sentry Logs: The summer 2026 roundup DevFeed: [What's new in Sentry Logs: The summer 2026 roundup]() Original publisher: [Read original article]() Author: Ben Coe; Allison Rogers Published: 2026-08-11T09:00:00Z Content type: release Language: en Sources: [Sentry Blog]() Topics: [Usability](), [tracing](), [data]() Tags: [2026](), [changelog](), [improvements](), [logs](), [usability]() ### AI overview A summer 2026 roundup of Sentry Logs updates, including log pinning, shareable URL state, large-scale exports with JSONL support, aggregate-aware exports, faster loading, and log viewer usability improvements. ### Source excerpt Everything that shipped for Sentry Logs this summer: log pinning, JSONL exports, terabyte-scale search, and a dozen usability improvements. ## Connecting OpenTelemetry Traces with Sentry Errors in One Trace Waterfall DevFeed: [Connecting OpenTelemetry Traces with Sentry Errors in One Trace Waterfall]() Original publisher: [Read original article]() Author: Johannes Daxböck; Neel Shah Published: 2026-08-05T09:00:00Z Content type: tutorial Language: en Sources: [Sentry Blog]() Topics: [OpenTelemetry](), [tracing](), [telemetry](), [SDKs]() Tags: [errors](), [instrumentation](), [logs](), [opentelemetry](), [sdk](), [sdks](), [sentry](), [tracing]() ### AI overview Sentry's OtlpIntegration connects OpenTelemetry traces with Sentry errors and other events, allowing them to appear together in a trace waterfall. It reads the active OTel trace context and associates it with Sentry events while configuring an OTLP exporter for Sentry. ### Source excerpt The OtlpIntegration bridges OTel traces and Sentry errors. Keep your OTel setup, add Sentry for errors, and see both in one trace waterfall. ## What's new in Svelte: August 2026 DevFeed: [What's new in Svelte: August 2026]() Original publisher: [Read original article]() Author: Dani Sandoval Published: 2026-08-01T00:00:00Z Content type: news Language: en Sources: [Svelte blog]() Topics: [Svelte](), [releases](), [Routing (disambiguation)](), [API](), [tracing](), [Availability]() Tags: [api](), [availability](), [changelog](), [forms](), [news](), [releases](), [routing](), [svelte](), [tracing](), [validation]() ### AI overview An August 2026 roundup of Svelte and SvelteKit updates, led by the first SvelteKit 3 preview releases. It covers new modules, improved service-worker support, built-in shallow routing, remote-form changes, validation improvements, production sourcemaps, tracing, deployment detection, and related stable-line updates. ### Source excerpt The biggest news this month is the first @next releases of SvelteKit 3. Thirteen preview versions shipped in July: previewing new $app/manifest and $app/service-worker modules, improved API availability and type checking in service workers, tracing out of the experimental namespace, shallow routing baked into goto and a lot more. It's a prerelease, but it's worth trying out to see what's coming to SvelteKit! Alongside the preview releases, the stable line kept moving with submitted on remote forms and a new home for defineEnvVars. The language tools also picked up zero-config +error.svelte props so error pages get their page and error types with no extra setup. And, in case you missed it, Svelte Summit Ljubljana 2026 is happening November 19-20, with a workshop day on November 18, the day before the summit. Save the date! What's new in SvelteKit Remote forms now expose a submitted property so you can react to the moment a form is submitted without waiting for the response (2.69.0, Docs, #14811) defineEnvVars has moved from @sveltejs/kit to @sveltejs/kit/env so environment helpers live in a dedicated subpath (2.70.0, Docs, #16378) SvelteKit 3 preview The next major version has landed in @next. Here are the highlights from 3.0.0-next.5 through 3.0.0-next.13 that you'll actually want to try out: Shallow routing is now built into goto via a new state option (with persistState: true to keep state across reloads), replacing pushState and replaceState (3.0.0-next.13, #16449) goto's noScroll and keepFocus options (and their matching data-sveltekit-* attributes) collapse into a single reset option (3.0.0-next.13, #16558) error(status, {...}) is deprecated in favor of error(status, message, {...}) so error messages are always required (3.0.0-next.13, #16540) refreshAll replaces invalidateAll, which is now deprecated (3.0.0-next.8, #16289) A new $app/manifest module exposes immutable, assets, prerendered and routes so you can introspect the build output at runtime (3.0.0-next. ## ClickHouse joins the Open Secure AI Alliance DevFeed: [ClickHouse joins the Open Secure AI Alliance]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-07-30T19:44:40Z Content type: news Language: en Sources: [ClickHouse Blog]() Topics: [ai security](), [AI Agent](), [Securing AI](), [agent observability](), [clickhouse](), [Open Source](), [tracing](), [observability](), [Instrumentation](), [hugging face](), [Nvidia]() Tags: [agents](), [ai](), [ai-agent](), [ai-agents](), [ai-security](), [clickhouse](), [hugging-face](), [instrumentation](), [nvidia](), [observability](), [open-source](), [security](), [tracing]() ### AI overview ClickHouse joins the Open Secure AI Alliance with NVIDIA and other industry leaders to develop open tools for securing AI agents. The article highlights Langfuse for agent tracing, evaluations, guardrail monitoring, and open audit trails, including air-gapped deployments that store traces in ClickHouse. ### Source excerpt ClickHouse is joining the Open Secure AI Alliance alongside NVIDIA and other industry leaders to help build open tools that keep AI agents secure. ## Detection primitives for eBPF rootkits DevFeed: [Detection primitives for eBPF rootkits]() Original publisher: [Read original article]() Author: Lorenzo Susini, Matt Muir Published: 2026-07-27T00:00:00Z Content type: article Language: en Sources: [Datadog Security Labs]() Topics: [eBPF](), [Malware](), [Linux](), [tracing](), [Network](), [Protocol (disambiguation)](), [debug](), [Processes]() Tags: [debug](), [ebpf](), [kernel](), [linux](), [malware](), [payload](), [processes](), [tracing]() ### AI overview The article analyzes how Linux malware families use eBPF rootkits and helpers to evade defenses, focusing on detection primitives and VoidLink's method for hiding active connections. It explains how VoidLink manipulates user-space memory and processes socket statistics obtained through Netlink. ### Source excerpt We analyze how VoidLink, LinkPro, and Atomic Arch abuse eBPF helpers to hide from defenders, and show how to detect them at load time, before they can act. ## Sentry Unreal Engine SDK Adds Session Replay to Crash Reports DevFeed: [Sentry Unreal Engine SDK Adds Session Replay to Crash Reports]() Original publisher: [Read original article]() Author: Ivan Tustanivskyi Published: 2026-07-24T09:00:00Z Content type: release Language: en Sources: [Sentry Blog]() Topics: [session replay](), [Unreal Engine](), [SDK](), [debugging](), [tracing]() Tags: [crash](), [debugging](), [sdk](), [sentry](), [session-replay](), [trace](), [unreal]() ### AI overview Sentry's Unreal Engine SDK adds Session Replay, recording the last several seconds of gameplay and attaching the footage to crash reports. Developers can review rendered frames alongside context, breadcrumbs, logs, and traces to investigate what led to a crash. ### Source excerpt The Sentry Unreal Engine SDK now records the last seconds of gameplay and attaches the footage to crash reports, so you can watch what led to the crash. ## Harness AgentTrace: An Observability and Guardrail Framework DevFeed: [Harness AgentTrace: An Observability and Guardrail Framework]() Original publisher: [Read original article]() Author: Sunil Gattupalle Sanjay Nagaraj Published: 2026-07-21T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [agent observability](), [ai observability](), [Framework](), [Testing](), [tracing]() Tags: [agents](), [ai](), [ai-observability](), [apache](), [ci](), [evaluation](), [observability](), [testing](), [tracing]() ### AI overview Harness describes AgentTrace, an internal framework for observing, evaluating, and governing AI agents in production. It connects production monitoring with evaluation, allows failures to become regression test cases, and includes open-source harness-sdk and harness-evals layers under Apache 2.0 that work with any OpenTelemetry backend. ### Source excerpt Harness AgentTrace unifies AI observability, evaluation, and guardrails to detect failures, improve quality, and secure AI agents in production. | Blog ## MongoDB Query Tracing in .NET with Sentry + OTLP DevFeed: [MongoDB Query Tracing in .NET with Sentry + OTLP]() Original publisher: [Read original article]() Author: James Crosswell Published: 2026-07-20T09:00:00Z Content type: tutorial Language: en Sources: [Sentry Blog]() Topics: [MongoDB](), [OpenTelemetry](), [tracing](), [.NET](), [telemetry](), [SDK]() Tags: [instrumentation](), [integration](), [mongodb](), [net](), [opentelemetry](), [sdk](), [telemetry](), [traces](), [tracing]() ### AI overview This tutorial demonstrates how to trace MongoDB queries in a .NET application by combining MongoDB's built-in OpenTelemetry instrumentation with Sentry's OTLP ingestion support in the .NET SDK. It explains how MongoDB spans and query data can flow into Sentry for performance analysis and correlation with errors and replays. ### Source excerpt Trace MongoDB queries in .NET using OpenTelemetry and Sentry's OTLP ingestion. See spans, query data, and error correlation in Sentry. ## How Sherlocks AI uses Temporal to orchestrate AI agents for incident resolution DevFeed: [How Sherlocks AI uses Temporal to orchestrate AI agents for incident resolution]() Original publisher: [Read original article]() Author: Akshat Sandhaliya Published: 2026-07-07T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [AI Agent](), [incident](), [SRE](), [observability](), [Cloud](), [tracing](), [Graphs](), [Databases](), [Kubernetes]() Tags: [ai-agent](), [ai-agents](), [apm](), [community](), [dashboards](), [databases](), [incident](), [kubernetes](), [logs](), [monitoring](), [observability](), [sre](), [temporal]() ### AI overview Sherlocks AI describes using Temporal Cloud to run durable AI-agent investigations for production incidents. The platform also uses workflows for knowledge-graph updates, infrastructure scans, and event ingestion, with retries, checkpointing, and parallel execution to improve reliability. ### Source excerpt Sherlocks AI on how Temporal Cloud runs durable AI agent investigations, infra scans, Knowledge Graph updates, and event ingestion for SRE teams. ## Next.js already traces your requests. Here's how to export them with OpenTelemetry. DevFeed: [Next.js already traces your requests. Here's how to export them with OpenTelemetry.]() Original publisher: [Read original article]() Author: Kyle Tryon Published: 2026-06-29T09:00:00Z Content type: tutorial Language: en Sources: [Sentry Blog]() Topics: [Next.js](), [OpenTelemetry](), [tracing](), [telemetry]() Tags: [next-js](), [opentelemetry](), [telemetry](), [traces](), [tracing](), [vercel]() ### AI overview This tutorial explains how to export the traces that Next.js generates automatically using OpenTelemetry and @vercel/otel. It covers sending traces to Sentry or other OTLP-compatible backends, understanding trace spans, and differences between Node and Edge runtimes. ### Source excerpt Next.js creates OpenTelemetry traces automatically. Learn how to export them to Sentry or any OTLP backend with @vercel/otel. [Next page]()