# opentelemetry Published articles for opentelemetry. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## WSO2 Releases Agent Manager as Enterprises Look to Control Growing AI Agent Sprawl DevFeed: [WSO2 Releases Agent Manager as Enterprises Look to Control Growing AI Agent Sprawl]() Original publisher: [Read original article]() Author: Craig Risi Published: 2026-09-18T12:00:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [AI Agent](), [Artificial Intelligence](), [Authorization](), [Security](), [Deployment](), [Kubernetes](), [Model Context Protocol](), [OpenTelemetry]() Tags: [agent-identity](), [agentic-ai-architecture](), [ai](), [ai-agent](), [ai-agents](), [ai-development](), [ai-ml-data-engineering](), [aiops](), [authorization](), [deployment](), [devops](), [governance](), [kubernetes](), [ml-data-engineering](), [model-context-protocol](), [news](), [opentelemetry](), [ws02-agent-manager](), [ws02-stratos]() ### AI overview WSO2 has released Agent Manager, an open-source platform for governing AI agents across models, frameworks, and deployment environments. The general availability release adds agent identity and authorization, MCP governance, lifecycle controls, a Kubernetes-native sandboxed runtime, and OpenTelemetry-based tracing and evaluation. ### Source excerpt WSO2 has announced the general availability of WSO2 Agent Manager, an open-source platform designed to provide centralized governance, identity management, security controls, and operational oversight for AI agents running across different models, frameworks, and deployment environments. By Craig Risi ## Security updates for Thursday DevFeed: [Security updates for Thursday]() Original publisher: [Read original article]() Author: corbet Published: 2026-09-17T12:48:01Z Content type: news Language: en Sources: [LWN.net]() Topics: [Security]() Tags: [ansible](), [firefox](), [grafana](), [net-9](), [nginx](), [opentelemetry](), [python](), [security](), [updates]() ### AI overview A roundup of security updates issued by AlmaLinux, Debian, Fedora, Mageia, Red Hat, Slackware, SUSE, and Ubuntu. The updates cover packages and components including .NET, kernels, Firefox, nginx, Python packages, Grafana, OpenTelemetry Collector, Ansible, and valkey. ### Source excerpt Security updates have been issued by AlmaLinux (.NET 10.0, .NET 8.0, .NET 9.0, corosync, firewalld, kernel, kernel-rt, libevent, libsoup, microcode_ctl, nginx:1.26, python-lxml, rsyslog, tesseract, and unbound), Debian (firefox-esr, mkvtoolnix, thunderbird, and tor), Fedora (open62541, php-pecl-mongodb2, python-django6, python-jwcrypto, and roundcubemail), Mageia (aom, cockpit, libgd, packagekit, and python-h2), Red Hat (corosync, delve, git-lfs, grafana-pcp, gstreamer1-plugins-base, libvirt, opentelemetry-collector, and rhc-worker-playbook), Slackware (mozilla-firefox and mozilla-thunderbird), SUSE (acl, attr, alloy, ansible-core, clamav, containerized-data-importer, corosync, cups, distribution, glibc, google-cloud-sap-agent, govulncheck-vulndb, gvfs, helm, jq, kbd, kubernetes1.34-apiserver, kubernetes1.35-apiserver, lcms2, libcupsfilters, liblzmasdk26, libzypp, zypper, mistral-vibe, opensc, openvpn, pcre2, python-jwcrypto, tomcat, tomcat10, and tomcat11), and Ubuntu (guix, libheif, perl, python-cryptography, sqlite3, and valkey). ## Building an Internal Developer Platform with Artificial Intelligence DevFeed: [Building an Internal Developer Platform with Artificial Intelligence]() Original publisher: [Read original article]() Author: Ben Linders Published: 2026-09-17T11:11:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [internal developer platform](), [AI Development](), [AI search](), [agent observability](), [OpenTelemetry](), [telemetry]() Tags: [agent](), [agents](), [artificial-intelligence](), [culture-methods](), [developer-experience](), [developer-platform](), [distributed-tracing](), [guardrails](), [internal-developer-platform](), [logging](), [logs](), [metrics](), [news](), [opentelemetry](), [platform-artificial-intelligence](), [platform-engineering](), [prometheus](), [traces]() ### AI overview This news article covers a KubeCon presentation about using AI agents as an internal developer platform. It discusses semantic search across sources such as Git, Slack, Jira, repositories, pull requests, and wiki pages; guardrails for controlling actions; and logs, metrics, and traces for understanding agent behavior. The speakers also describe OpenTelemetry conventions for GenAI and related observability tools. ### Source excerpt Agents are becoming the new developer platform, using semantic search with data from tools like Git, Slack, and Jira for context. Things to consider are setting guardrails to block or allow things, and using logs, metrics, and traces to understand agent behavior. By Ben Linders ## OpenTelemetry everywhere: Migrating a metrics platform at scale DevFeed: [OpenTelemetry everywhere: Migrating a metrics platform at scale]() Original publisher: [Read original article]() Author: Iris Grace Endozo, Farzad Vazirnia and Albert Kerr, Atlassian Published: 2026-09-17T11:00:00Z Content type: article Language: en Sources: [Cloud Native Computing Foundation]() Topics: [OpenTelemetry](), [migration](), [observability](), [telemetry](), [atlassian](), [Open Source]() Tags: [atlassian](), [blog](), [collector](), [metrics](), [migration](), [observability](), [opentelemetry](), [pipeline](), [scale](), [sidecar]() ### AI overview Atlassian describes replacing a large-scale gostatsd metrics pipeline with OpenTelemetry while preserving the existing StatsD interface for service teams. The migration uses purpose-built OpenTelemetry Collector distributions across collection, ingest, aggregation, and forwarding stages, with support for both StatsD and OTLP during the transition. ### Source excerpt Why we did this at all For most of the last decade our metrics pipeline ran on gostatsd, the open-source StatsD implementation we maintain. It primarily did two jobs: as sidecar on every host and the... ## Agent Anomaly Detection, now in Private Preview on the Gemini Enterprise Agent Platform DevFeed: [Agent Anomaly Detection, now in Private Preview on the Gemini Enterprise Agent Platform]() Original publisher: [Read original article]() Author: Achuth Narayan Rajagopal Published: 2026-09-17T01:25:27.608736Z Content type: release Language: en Sources: [Google Developers Blog]() Topics: [agent observability](), [OpenTelemetry](), [Security](), [Traces](), [API]() Tags: [agent](), [anomaly-detection](), [api](), [autonomous-agents](), [gemini](), [opentelemetry](), [security]() ### AI overview Google announces Agent Anomaly Detection in private preview on the Gemini Enterprise Agent Platform. The feature analyzes agents' reasoning traces, tool calls, logs, and execution flows to identify behavioral anomalies, suspicious intent, and policy violations. ### Source excerpt Agent Anomaly Detection is a new, out-of-band oversight layer for the Gemini Enterprise Agent Platform that analyzes OpenTelemetry traces and tool calls to catch behavioral risks without adding runtime latency to live requests. It utilizes a multi-tiered detection pipeline--combining lightweight statistical scanning with deep LLM-based reasoning--to identify logical anomalies and policy violations grounded in the OWASP Agentic Top 10. Developers can triage these automated findings within Security Command Center or leverage the exposed API to programmatically block subsequent tool calls when an agent breaches defined risk thresholds. ## Behind the Scenes: How the OpenTelemetry Plugin Maps Your Microservices in Real-Time DevFeed: [Behind the Scenes: How the OpenTelemetry Plugin Maps Your Microservices in Real-Time]() Original publisher: [Read original article]() Author: Egor Klimov Published: 2026-09-16T12:34:47Z Content type: article Language: en Sources: [The JetBrains Blog]() Topics: [OpenTelemetry](), [Microservices](), [observability](), [telemetry](), [Traces](), [ide]() Tags: [all-things-web](), [backstage](), [environment-variables](), [goland](), [ide](), [idea](), [intellij-idea](), [intellij-platform](), [jetbrains](), [microservices](), [observability](), [opentelemetry](), [performance-optimization](), [plugin-development](), [plugin-highlights](), [plugins](), [pycharm](), [research](), [rider](), [telemetry](), [traces](), [webstorm]() ### AI overview This article explains how the JetBrains OpenTelemetry Plugin generates a service map from runtime telemetry. It describes using logs, metrics, and especially standardized trace spans to visualize how microservices communicate, along with the plugin's lightweight local OpenTelemetry backend. ### Source excerpt We've all been there: you join a new project, and the first thing you ask for is the architecture diagram. You're handed a diagram that looks great, but after a week of debugging, you realize it's six months out of date. Service A hasn't talked to Service B since the spring, and there's a new [...] ## Kubernetes attributes processor reaches v1.0.0 milestone DevFeed: [Kubernetes attributes processor reaches v1.0.0 milestone]() Original publisher: [Read original article]() Author: OpenTelemetry Authors; Docs CC BY Published: 2026-09-16T04:59:27Z Content type: release Language: en Sources: [Blog on OpenTelemetry]() Topics: [OpenTelemetry](), [telemetry](), [releases](), [Kubernetes](), [Go Language]() Tags: [api](), [go](), [kubernetes](), [opentelemetry](), [releases](), [stable](), [telemetry]() ### AI overview The Kubernetes attributes processor has reached version 1.0.0 and fulfills OpenTelemetry's stability criteria for testing, benchmarking, documentation, and telemetry. The release also supports redistribution as a Go library or in binaries without API breakage. ### Source excerpt The Kubernetes attributes processor, which enriches your telemetry with Kubernetes metadata, has officially moved to v1.0.0! You can try it out on your custom distro, and it is also available as part of the latest opentelemetry-collector-contrib and opentelemetry-collector-k8s distro releases. Being v1.0.0 means the component is now verified to fulfill the 'stable' stability criteria including requirements around testing, benchmarking, documentation and telemetry stability. It also ensures you can redistribute it as a Go library or as part of your binaries without API breakage. ## Running Agent Harnesses with Local Models DevFeed: [Running Agent Harnesses with Local Models]() Original publisher: [Read original article]() Author: Avi Chawla Published: 2026-09-15T21:59:31Z Content type: tutorial Language: en Sources: [Daily Dose of Data Science]() Topics: [Large Language Model](), [coding](), [Hardware](), [Open Source](), [Claude Code](), [codex]() Tags: [agent](), [coding](), [hardware](), [local](), [models](), [open-source](), [opentelemetry](), [profiling](), [recommendations](), [run-agent](), [video]() ### AI overview A video walkthrough explains how Magnitude profiles computer hardware, benchmarks local models, recommends practical candidates, and connects a selected model to coding agent harnesses such as Claude Code, Codex, OpenCode, and Pi. The article also presents a Dynatrace reference application for tracing LLM pipelines with OpenTelemetry. ### Source excerpt ...explained with a full video walkthrough. ## 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 ## Grab's LLM-Kit Framework Standardizes More Than 500 Internal Agent Services DevFeed: [Grab's LLM-Kit Framework Standardizes More Than 500 Internal Agent Services]() Original publisher: [Read original article]() Author: Hien Luu Published: 2026-09-15T09:00:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [Framework](), [AI Agent](), [Deployment](), [Model Context Protocol](), [agent observability](), [FastAPI](), [OpenTelemetry](), [GitLab]() Tags: [agent](), [agents](), [ai](), [ai-agent](), [ai-ml-data-engineering](), [deployment](), [fastapi](), [framework](), [gitlab](), [grab-agent-platform](), [ml-data-engineering](), [model-context-protocol](), [news](), [opentelemetry](), [vault]() ### AI overview Grab's internal LLM-Kit framework standardizes more than 500 agent services by providing shared scaffolding for evaluation, tracing, secret handling, service discovery, and tool-server connections. The article reports that deploying a new agent service now takes about one hour instead of two weeks or more. ### Source excerpt Grab has implemented LLM-Kit, a framework that standardizes over 500 internal agent services. This system enhances service integration, evaluation, and secret handling, reducing the time to deploy new AI agents from two weeks to one hour. It centralizes infrastructure management, allowing runtime tool discovery and flexible model integration, while maintaining operational control. By Hien Luu ## Inside the LLM Call: GenAI Observability with OpenTelemetry DevFeed: [Inside the LLM Call: GenAI Observability with OpenTelemetry]() Original publisher: [Read original article]() Author: OpenTelemetry Authors; Docs CC BY Published: 2026-09-14T16:56:42Z Content type: tutorial Language: en Sources: [Blog on OpenTelemetry]() Topics: [OpenTelemetry](), [agent observability](), [telemetry](), [AI Agent](), [Large Language Model]() Tags: [agent](), [ai-agent](), [claude-code](), [codex](), [observability](), [opentelemetry](), [token](), [tool](), [visibility]() ### AI overview This tutorial explains how OpenTelemetry Semantic Conventions for Generative AI record LLM calls, tool invocations, token counts, and related events. It demonstrates exporting telemetry from an LLM-powered application, viewing it with Aspire Dashboard, and considering sensitive-data implications of optional content capture. ### Source excerpt Your AI agent just took 45 seconds to answer a simple question. Was it the model? A slow tool call? A retry loop? Every time an application calls an LLM, a chain of model calls, tool invocations, and token exchanges happens behind the scenes -- and without observability, you are guessing. The OpenTelemetry Semantic Conventions for Generative AI give you that visibility. They standardize how GenAI operations are recorded -- the model being called, input and output token counts, and when opted in, the full content of prompts, completions, tool calls, and tool results. ## Datadog named the Company to Beat for observability platforms in 2026 Gartner® AI Vendor Race report DevFeed: [Datadog named the Company to Beat for observability platforms in 2026 Gartner® AI Vendor Race report]() Original publisher: [Read original article]() Author: Yanbing Li Published: 2026-09-14T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [observability](), [agent observability](), [observability ai agents](), [incident](), [MCP Server](), [observability pipelines](), [OpenTelemetry](), [Security](), [Artificial Intelligence]() Tags: [agent-observability](), [ai-agents](), [datadog](), [incident-response](), [mcp-server](), [observability](), [observability-pipelines](), [opentelemetry]() ### AI overview Datadog says it was named the Company to Beat for observability platforms in Gartner's August 2026 AI Vendor Race research and a Leader in the 2026 Gartner Magic Quadrant for Observability Platforms. The article presents Datadog's unified observability and security platform, including autonomous incident investigation, AI agent and LLM application observability, an MCP Server for querying telemetry, and Observability Pipelines with OpenTelemetry support. ### Source excerpt Datadog has been recognized as the Company to Beat for observability platforms in the August 2026 Gartner® AI Vendor Race research. ## How to scale Alloy as a central telemetry gateway: capacity planning, load testing, and production lessons DevFeed: [How to scale Alloy as a central telemetry gateway: capacity planning, load testing, and production lessons]() Original publisher: [Read original article]() Author: Fatjon Nebiu Published: 2026-09-12T11:22:06.456390Z Content type: tutorial Language: en Sources: [Grafana Labs blog on Grafana Labs]() Topics: [Grafana]() Tags: [analytics](), [auth](), [best-practices](), [cloud](), [cost](), [data](), [deployment](), [enterprise](), [grafana](), [grafana-alloy](), [grafana-cloud](), [how-to](), [kubernetes](), [logs](), [metrics](), [monitoring](), [observability](), [opentelemetry](), [platform](), [production](), [prometheus](), [scale](), [telemetry](), [testing](), [traces]() ### AI overview A practical guide to scaling Grafana Alloy as a centralized telemetry gateway. It covers capacity planning, load testing, and production considerations for collecting metrics, logs, and traces and forwarding them to Grafana Cloud. ### Source excerpt Running Alloy as a single-instance sidecar is simple. Running it as a centralized gateway that absorbs the full telemetry stream of an enterprise platform--tens of millions of active series, terabytes of logs per day, and tens of thousands of trace spans per second--is a different challenge altogether. To get it right, you need deliberate capacity planning, honest load testing, and a monitoring setup that doesn't rely on the very thing you're testing. As part of the Professional Services team here at Grafana Labs, we've seen this firsthand working with customers. In this post, we'll walk you through the best practices we follow to help them find success, and we'll do so using real, anonymized data from a recent engagement. We'll cover how we sized and load tested a production Alloy central collector deployment on Kubernetes, what the numbers looked like under real stress, and how the cluster behaves today handling the full production telemetry workload for a large enterprise platform. By the end, you should have a better sense for how you can create your own central gateway for collecting telemetry in Grafana Cloud. Why a central gateway? Before diving into numbers, it's worth explaining the pattern. In a central gateway setup, all telemetry from application teams--metrics, logs, and traces--flows to a shared Alloy fleet via OTLP or native Prometheus/Loki write protocols. Alloy buffers, processes, batches, and forwards everything to Grafana Cloud. This gives you several things that per-team sidecar deployments struggle to provide: A single control plane: Auth, rate limiting, and routing in one place so application teams don't need to manage Grafana Cloud credentials Centralized buffering: Ensure a transient Grafana Cloud slowdown doesn't immediately cause data loss at the source Cost visibility: Configure the gateway to only accept telemetry data containing the label or attribute that is mandatory for cost-attribution Protocol normalization: Send OTLP, Prometheus Remote ## 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. ## Session Traces and Cost Controls Help Diagnose AI Agent Failures DevFeed: [Session Traces and Cost Controls Help Diagnose AI Agent Failures]() Original publisher: [Read original article]() Author: Mark Silvester Published: 2026-09-11T08:14:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [ai observability](), [AI Bots](), [debugging]() Tags: [agents](), [ai](), [ai-agent](), [ai-ml-data-engineering](), [artificial-intelligence](), [cost](), [debugging](), [devops](), [llm](), [loops](), [ml-data-engineering](), [monitoring](), [news](), [observability](), [observability-ai-agents](), [opentelemetry](), [traces]() ### AI overview The article describes using nested session traces, execution metrics, and cost limits to investigate and contain AI agent failures such as repeated tool calls and runaway spending. ### Source excerpt Session traces and cost controls are emerging as key observability techniques for diagnosing AI agent failures, helping teams spot tool-call loops and runaway spend while preserving enough execution context for post-incident debugging. By Mark Silvester ## Security updates for Thursday DevFeed: [Security updates for Thursday]() Original publisher: [Read original article]() Author: jzb Published: 2026-09-10T13:14:35Z Content type: news Language: en Sources: [LWN.net]() Topics: [Security, Privacy and Abuse Prevention](), [.NET](), [Boot Process, passwd, systemd](), [Grafana]() Tags: [ansible](), [grafana](), [kernel](), [linux](), [net](), [opentelemetry](), [oracle](), [prometheus](), [python](), [redis](), [rust](), [security](), [systemd](), [ubuntu](), [updates]() ### AI overview A roundup of security updates issued by several Linux distributions for a range of packages. ### Source excerpt Security updates have been issued by AlmaLinux (389-ds-base, ansible-core, buildah, expat, glib2, gpsd, gpsd-minimal, gzip, kernel, kernel-rt, opentelemetry-collector, osbuild-composer, perl-DBI, python-lxml, python3.12-lxml, qt5-qtbase, thunderbird, valkey, vim, and xz), Debian (pyasn1), Fedora (darktable, freeipa, freerdp2, gdk-pixbuf2, GitPython, libsoup3, openssl, perl-Net-DNS, rust-ppmd-rust, samba, and valkey), Mageia (ceph, firefox, nss, perl-DBI, thunderbird, and wget), Oracle (389-ds-base, buildah, expat, git-lfs, glib2, glibc, gpsd, gpsd-minimal, grafana-pcp, kernel, libssh, nginx, perl-GD, python3.14-cryptography, redis:7, skopeo, thunderbird, valkey, xmlrpc-c, and xz), Slackware (xz), SUSE (bzip2, cpio, curl, dracut, fuse-overlayfs, golang-github-vpenso-prometheus_slurm_exporter, helm, java-1_8_0-ibm, kbfs, kernel, kernel-devel, libopenslide-devel, libsoup, libssh2_org, libusb-1_0, libvirt, libzypp, zypper, mcphost, multipath-tools, NetworkManager, opensc, openssl-3, perl-Net-DNS, python-aiohttp, python-Authlib, python-pip, python-sqlparse, python313-dnspython, python313-idna, rpcbind, sssd, strongswan, systemd, tomcat11, ucode-intel, and wget), and Ubuntu (dotnet8, dotnet10, ffmpeg, flatpak, netty, and perl). ## Security updates for Wednesday DevFeed: [Security updates for Wednesday]() Original publisher: [Read original article]() Author: jzb Published: 2026-09-09T13:04:46Z Content type: news Language: en Sources: [LWN.net]() Topics: [Debian](), [cURL](), [Chromium](), [systemd](), [Terraform](), [.NET]() Tags: [chromium](), [cli](), [debian](), [google](), [intel](), [java](), [kernel](), [opentelemetry](), [python](), [redis](), [security](), [systemd](), [terraform](), [updates]() ### AI overview Security updates have been issued across AlmaLinux, Debian, Fedora, Mageia, Red Hat, SUSE, and Ubuntu for a broad set of packages, including kernels, systemd, Chromium, curl, Python, Java, Terraform provider components, and other system and developer tools. ### Source excerpt Security updates have been issued by AlmaLinux (expat, glib2, microcode_ctl, mrtg, pam, redis, thunderbird, and valkey), Debian (fort-validator, gst-plugins-base1.0, kernel, and slurm-wlm), Fedora (complyctl, libevent, openvpn, and tar), Mageia (dovecot and spice-vdagent), Red Hat (ignition, opentelemetry-collector, and osbuild-composer), SUSE (amazon-ssm-agent, aws-nitro-enclaves-cli, bzip2, cadvisor, chromium, curl, distribution-registry, emacs, freeciv, fuse-overlayfs, gh, google-guest-agent, GraphicsMagick, hauler, insighttoolkit-devel, java-17-openjdk, libidn, libusb-1_0, libvirt, libvncserver, libzypp, zypper, lkl, lxd, multipath-tools, NetworkManager, perl-Net-DNS, perl-URI, python, python-authlib, python-sqlparse, python-tornado, python3, rpcbind, supergfxctl, systemd, terraform-provider-null, ucode-intel, wget, wireshark, and xen), and Ubuntu (curl, ffmpeg, glibc, hsqldb1.8.0, imagemagick, perl, and vim). ## Distributed tracing for CI pipelines without touching a single workflow file DevFeed: [Distributed tracing for CI pipelines without touching a single workflow file]() Original publisher: [Read original article]() Author: George Sims, downtherabbithole.dev Published: 2026-09-08T11:00:00Z Content type: article Language: en Sources: [Cloud Native Computing Foundation]() Topics: [ci]() Tags: [blog](), [ci](), [github](), [github-actions](), [instrumentation](), [jobs](), [opentelemetry](), [tracing](), [workflow](), [workflows]() ### AI overview The article describes collecting GitHub Actions events at the organization level and converting them into OpenTelemetry spans to trace CI workflows without editing individual workflow files. ### Source excerpt You've probably felt this one: GitHub Actions usage creeps up across your org, and your actual visibility into it doesn't keep pace. Which workflows are slow? Which are flaky? How long are jobs sitting queued for... ## MCP Logging in Spring AI DevFeed: [MCP Logging in Spring AI]() Original publisher: [Read original article]() Author: Burak Gökmen Published: 2026-09-06T23:19:21Z Content type: tutorial Language: en Sources: [Baeldung]() Topics: [Model Context Protocol](), [log management](), [AI Development](), [Remote Procedure Call (RPC)](), [telemetry]() Tags: [logging](), [mcp](), [mcp-server](), [opentelemetry](), [popular](), [rpc](), [spring](), [spring-ai](), [spring-ai-mcp-popular](), [spring-boot](), [tutorial]() ### AI overview A tutorial on MCP logging in Spring AI, covering server-to-client log notifications, client-controlled severity levels, and migration guidance following the feature's deprecation. ### Source excerpt Learn about MCP logging in Spring AI, both in an MCP server and a client. The post MCP Logging in Spring AI first appeared on Baeldung. ## Open by design: How Elastic supports MOSA, the DoD's Modular Open Systems Approach DevFeed: [Open by design: How Elastic supports MOSA, the DoD's Modular Open Systems Approach]() Original publisher: [Read original article]() Author: Woody Walton Published: 2026-09-04T00:00:00Z Content type: article Language: en Sources: [Elastic Blog - Elasticsearch, Kibana, and ELK Stack]() Topics: [Architecture & Design](), [data](), [Instrumentation](), [telemetry]() Tags: [acquisition](), [analytics](), [data](), [defense-government-open-source-standards](), [design](), [elasticsearch-platform](), [government-public-sector](), [instrumentation](), [integration](), [open](), [opentelemetry](), [scalability](), [systems]() ### AI overview Elastic explains how its data and analytics platform can support the US Department of Defense Modular Open Systems Approach through modularity, open standards, and component removability. ### Source excerpt Major US defense acquisition programs are required to be designed around a Modular Open Systems Approach (MOSA). Here's what program offices need to know about how Elastic can support MOSA at the data and analytics layer. ## How Uken Games reduces observability costs by 87% with ClickHouse DevFeed: [How Uken Games reduces observability costs by 87% with ClickHouse]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-09-01T15:28:24Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [telemetry](), [Traces](), [Grafana]() Tags: [clickhouse](), [cost](), [observability](), [opentelemetry](), [traces]() ### AI overview Uken Games replaced Datadog with an open-source observability stack centered on ClickHouse, cutting observability costs by 87%. The stack stores traces in ClickHouse and uses OpenTelemetry collectors with SigNoz, Prometheus, and Grafana. ### Source excerpt Uken Games replaced Datadog with an open-source observability stack built on ClickHouse, cutting costs by 87% while storing every trace on a single node. ## 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. ## OpenTelemetry Go Logs API and SDK reach release candidate status DevFeed: [OpenTelemetry Go Logs API and SDK reach release candidate status]() Original publisher: [Read original article]() Author: OpenTelemetry Authors; Docs CC BY Published: 2026-08-31T15:40:58Z Content type: release Language: en Sources: [Blog on OpenTelemetry]() Topics: [OpenTelemetry](), [Go Language](), [releases](), [SDKs](), [Logging]() Tags: [api](), [beta](), [experimental](), [go](), [opentelemetry](), [release](), [sdk](), [version]() ### AI overview OpenTelemetry Go v1.47.0-rc.1 promotes the Logs API and SDK to release candidate status. The release moves these modules from beta stability toward stable v1 compatibility guarantees, while log exporters and logtest remain experimental and outside the RC scope. ### Source excerpt OpenTelemetry Go v1.47.0-rc.1 is here. This release promotes the Logs API and SDK to release candidate (RC), the final stage before we provide stable v1 compatibility guarantees. We believe the design is ready, and now we need the community to test it in real applications and integrations before those guarantees take effect. What is included in the release candidate? The RC covers these two modules: go.opentelemetry.io/otel/log go.opentelemetry.io/otel/sdk/log These modules move from v0.22.0, with beta stability, to v1.47.0-rc.1. The version aligns them with the other stable OpenTelemetry Go modules, which share a coordinated version number. The log exporters and logtest modules remain experimental and are not covered by this RC's stability scope. [Next page]()