Infrastructure
Observability
How modern observability works — OpenTelemetry, the traces/metrics/logs trio, and controlling telemetry cost at scale.
Observability is the ability to ask arbitrary questions about a running system from its outputs, without shipping new code to answer them. The classic framing is three signals — metrics (aggregate numbers over time), logs (discrete event records), and traces (the path of a single request across services) — increasingly unified by correlating IDs so you can pivot from a slow metric to the exact trace to the relevant logs.
The defining shift of the last few years is OpenTelemetry (OTel) becoming the vendor-neutral standard for generating and shipping that telemetry, ending lock-in to a single agent. Notifire tracks the OTel project's maturation, the rise of high-cardinality wide-event analysis, eBPF-based zero-instrumentation collection, and — the pressure point for most teams in 2026 — telemetry cost control through sampling, aggregation, and tiered storage.
Latest briefings on Observability
Infra
Uber Finds What Distributed Tracing Misses
Uber built an automated system to find rare failures that traditional tools miss. It analyzes production data to map how services depend on each other, helping engineers prevent outages in their massive network.
Ashish Kale ·
Infra
Grafana Tempo Makes Trace Data Safer and Smarter
Grafana Tempo 3.1 now lets teams remove sensitive data from system traces using simple queries. The update also makes performance metrics more accurate by accounting for sampled data, improving both privacy and observability.
Ashish Kale ·
Infra
How a 20-Year-Old Game Solved Modern Observability
Eve Online uses advanced sampling techniques to monitor its 20-year-old game architecture. This allows its developers to maintain high system fidelity and control telemetry costs without slowing down real-time gameplay for thousands of players.
Ashish Kale ·
Infra
Cloudflare Now Filters and Redacts Logs Natively
Cloudflare's new Transformers feature lets you filter and redact sensitive data from logs before they are exported. This removes the need for separate processing tools, simplifying data pipelines and improving security for developers and IT teams.
Ashish Kale ·
Infra
Grafana Can Now Manage Your Telemetry Fleet
Grafana Cloud has launched Fleet Management to centrally manage OpenTelemetry Collectors. This helps teams maintain consistent configurations and monitor the health of their entire telemetry pipeline, simplifying operations at scale for developers and SREs.
Ashish Kale ·
Infra
Kubernetes Monitoring Just Got More Reliable and Stable
OpenTelemetry's Kubernetes Attributes Processor is now officially stable. This gives developers and SREs a dependable way to add crucial Kubernetes context to their logs and metrics, making it much easier to debug complex applications running in containers.
Ashish Kale ·
Infra
Palo Alto's AI Finds Bugs But Still Calls You
Palo Alto Networks launched Cortex XCOR, an AI platform that automatically investigates system outages. It aims to find the root cause and suggest fixes, reducing the manual work for on-call engineers trying to debug complex systems.
Ashish Kale ·
Infra
Adobe Tool Isolates GPU Metrics for Teams
Adobe has open-sourced a new tool that lets teams safely view their own GPU performance metrics in shared Kubernetes clusters. This solves a major security challenge by preventing teams from seeing each other's sensitive operational data.
Ashish Kale ·
Infra
How Atlassian Replaced Its Core Metrics Engine Live
Atlassian replaced its core metrics system, handling data from 100,000 servers, with OpenTelemetry. The high-stakes migration was done live without disrupting critical production alerts, proving the standard's maturity.
Ashish Kale ·
Infra
AWS Built a New Tool to Debug Your AI Agents
AWS launched CloudWatch Omni, a new tool to help developers understand why their AI agents behave unpredictably. It unifies monitoring to explain agent actions, a task traditional tools like the original CloudWatch have struggled with.
Ashish Kale ·
Data
Redis Cloud Metrics Now Flow Directly to Datadog
Redis Cloud and Datadog have launched a new native integration. This allows teams to send performance metrics directly to their Datadog dashboards without setting up any additional infrastructure, simplifying the entire monitoring process.
Taranpreet Singh ·
Data
ClickHouse Now Offers a Prometheus Drop-In Replacement
ClickHouse now supports PromQL, letting it act as a drop-in replacement for Prometheus. This allows teams to store and query metrics alongside logs and traces in a single, high-performance database without rewriting queries in SQL.
Taranpreet Singh ·
Infra
How OpenTelemetry's New Status Simplifies Your Stack
OpenTelemetry has officially graduated within the Cloud Native Computing Foundation, solidifying its role as the industry standard for observability. This helps companies avoid vendor lock-in and standardize how they monitor their software and infrastructure.
Ashish Kale ·
Infra
Vercel Now Finds Bugs You Can't Reproduce
Vercel launched Always-on tracing, a new feature that continuously samples live user traffic. This helps developers debug real-world issues on production sites without needing to reproduce the bugs themselves.
Ashish Kale ·
Infra
Grafana Now Lets AI Agents Read Live System Data
Grafana has released new tools that allow AI coding agents to directly query live system data like metrics and logs. This enables developers to build and debug applications using real-time information, not just static code.
Ashish Kale ·
Infra
Your Cloudflare AI Traces May Be Incomplete
Cloudflare now offers agent tracing to help developers debug AI on its Workers platform. However, the company warns that traces are not lossless, data can be truncated, and the feature will become a paid service in 2026.
Ashish Kale ·
Infra
How Netflix Built a Map That Never Loses Data
Netflix redesigned its real-time service map to handle massive scale without losing data. The new system uses a multi-stage pipeline and clever backpressure techniques to ensure every event is processed, even under extreme load.
Ashish Kale ·
Infra
Is Your Observability Stack Counting Everything Twice?
Using a service mesh with other observability tools can accidentally double-count your traffic metrics. A new guide from CNCF shows developers how to fix this common issue, ensuring accurate data for monitoring and incident response.
Ashish Kale ·
Data
Making the Perfect Espresso with a Modern Data Stack
A developer treated an espresso machine like a distributed system, using OpenTelemetry and ClickHouse to analyze every shot. The project is a creative case study on applying observability principles to real-world, unconventional systems.
Taranpreet Singh ·
Infra
Talk to Your Data With Grafana's Upgraded AI
Grafana's AI assistant can now query and correlate data from over 30 sources using plain English. This helps developers and IT teams find insights faster without writing complex queries, boosting productivity and simplifying observability.
Ashish Kale ·
Infra
Dynatrace AIOps Moves from Guessing to Knowing
Dynatrace is upgrading its AIOps platform to move beyond predictions. The new system uses deterministic analysis to pinpoint root causes and automatically resolve infrastructure issues, aiming for truly autonomous IT operations for SRE teams.
Ashish Kale ·
Infra
Get a Clearer View of Your Kubernetes AI Jobs
A new plugin for the Headlamp Kubernetes UI now supports Volcano, a popular batch scheduler for AI and high-performance computing. This gives developers a simple web interface to inspect and manage complex batch jobs directly within Kubernetes.
Ashish Kale ·
Infra
Find and Fix Workflow Bugs Faster on Vercel
Vercel has launched a redesigned trace viewer for its Workflows tool. The update helps developers debug complex processes more quickly by making it easier to search, zoom, and inspect each step of a workflow run.
Ashish Kale ·
Infra
eBPF Lets You Safely Extend the Linux Kernel
The technology eBPF allows developers to safely run custom programs inside the Linux kernel. This provides deep system visibility for performance and security monitoring without the risks or slow update cycles of traditional methods.
Ashish Kale ·
Data
Build Elastic Integrations Faster, With or Without Code
Elastic 9.4 now offers two ways to build custom integrations. A new no-code tool makes it faster for anyone, while a developer toolkit provides full control for complex needs, simplifying data ingestion from any source.
Taranpreet Singh ·
Infra
Your AI Incident Tools Are Missing a Key Layer
PagerDuty's Chief AI Officer warns that while AI accelerates code delivery, it also increases incidents. Most current AI tools for incident response lack a critical layer of operational context, making them less effective.
Ashish Kale ·
Infra
The Limits of OpenTelemetry Neutrality
OpenTelemetry (OTel) offers a standard for telemetry data, promising vendor neutrality. However, a recent analysis highlights the complexities behind this promise. While OTel provides a common format, true neutrality is challenging as vendor-specific features can still lead to forms of lock-in.
Ashish Kale ·
Infra
Unifying Tech and Business Goals
Customer expectations are now set by digital giants like Google and Netflix. To meet these standards, companies need a unified view across tech, service, and business. Collaborative observability connects system performance directly to customer experience and business outcomes, enabling better, more aligned decision-making across teams.
Ashish Kale ·
AI
Experts Warn Against Ungoverned AI
AI experts are warning CIOs against deploying AI agents without proper governance and observability tools. Rushing into adoption without visibility into the agents' decision-making processes creates a "time bomb" with the potential for severe negative consequences, turning a potential productivity boost into a significant business risk.
Neeraj Dhiman ·
Infra
Expert advice for running production AI
CoreWeave's CTO, Peter Salanki, discussed the challenges of running AI in production. He highlighted the growing importance of observability, resource utilization, and scheduling for efficient operations. Salanki also advised teams to avoid the common mistake of over-architecting their systems too early.
Ashish Kale ·
Frequently asked questions
What's the difference between monitoring and observability?
Monitoring tracks known failure modes — dashboards and alerts for metrics you decided in advance to watch. Observability lets you investigate unknown problems after the fact by querying rich telemetry, including questions you never anticipated. Monitoring tells you that something is wrong; observability helps you figure out why, especially for novel failures in distributed systems.
What are the three pillars of observability?
Metrics (numeric measurements aggregated over time, e.g. request rate or p99 latency), logs (timestamped records of discrete events), and traces (the end-to-end path of a single request as it flows through multiple services). Many teams now treat them less as separate pillars and more as correlated views, linked by trace and span IDs so you can jump between them during an investigation.
What is OpenTelemetry and why does it matter?
OpenTelemetry (OTel) is a CNCF project providing vendor-neutral APIs, SDKs, and a collector for generating and exporting traces, metrics, and logs. Instrumenting with OTel means your telemetry isn't tied to one vendor's agent — you can switch or mix backends (Datadog, Grafana, Honeycomb, Prometheus) without re-instrumenting. It has become the de facto standard for application telemetry.
How do teams control observability costs?
The main levers are sampling (keep a representative or error-biased subset of traces rather than all of them), aggregation and metric cardinality limits, dropping low-value logs at the collector, and tiered storage that keeps recent data hot and archives older data cheaply. With telemetry volume often growing faster than the systems it observes, cost governance at the OTel collector has become a first-class engineering concern.