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Understanding the Three Pillars of Observability: Logs, Metrics and Traces

Many people wonder what the difference is between monitoring vs. observability. While monitoring is simply watching a system, observability means truly understanding a system's state. DevOps teams leverage observability to debug their applications, or troubleshoot the root cause of system issues. Peak visibility is achieved by analyzing the three pillars of observability: Logs, metrics and traces. Depending on who you ask, some use MELT as the four pillars of essential telemetry data (or metrics, events, logs and traces) but we'll stick with the three core pillars for this piece.

Bindplane Now Ships With a Native AI Skill - Bring Your Own Agent

Today we're rolling out the Bindplane AI Skill, a built-in capability of the Bindplane CLI (v1.98+) that teaches your favorite AI coding tool how to work with Bindplane — natively, accurately, and without the setup headaches of traditional integrations. Read Part 2 of the Bindplane AI Skill series to learn more about how we built it and how it works with real-life examples.

Moving On From MCP: How We Built the Bindplane AI Skill

If you've spent any time wiring AI coding agents into developer platforms over the last year, you've probably reached for MCP. We did too. And after enough sessions watching context windows balloon and tool calls misfire, we started looking for something different. This is the story of what we built instead — a native AI skill for the Bindplane CLI — and the engineering decisions behind it.

Your Team is Using Claude Code. Do You Know What It's Costing You?

The first two weeks of Claude Code are exciting. The third week is when you realize you don’t have visibility into what it’s doing or what it’s costing you. You would not run a production service without metrics, logs, and dashboards or deploy an API without knowing its latency, error rate, or cost per request.

Coralogix and Atlassian: Full-Stack Observability Inside the Incident Workflow

Incident response has a well-known efficiency problem. The tools teams use to detect and investigate issues are often disconnected from the tools they use to manage and resolve them. Engineers spend a significant portion of each incident switching between platforms, assembling context that should already be at hand. Even when the data is available, correlating signals across user, app, infrastructure, and security events to pinpoint a root cause remains manual and slow.

From Vibes to Signals: Observing Your AI Coding Workflow

Agentic coding tools like Claude Code and Codex have taken centre stage and inserted themselves into the critical path of software development. This shift has happened fast, and for most teams, the visibility hasn’t caught up. Until now we’ve been evaluating our vibe coding the same way – on vibes. You might say “this feels faster” or “that seems like a better approach”. That’s not going to scale.

LiveTail: Real-Time Visibility for Active Telemetry

See how Mezmo LiveTail helps teams move from passive log search to active, real-time investigation. In this demo, you'll watch live telemetry stream across services and environments, identify emerging issues as they happen, and use real-time context to troubleshoot faster before signals are delayed, buried, or lost in the noise. LiveTail is part of Mezmo's Active Telemetry platform — built for platform engineers and SREs who need immediate visibility into what's happening across their stack right now, not after the fact.

How Mezmo Uses Active Telemetry for Faster AI Root Cause Analysis

AI-powered root cause analysis only works when the data going into the model is clean, relevant, and structured. In this demo, we show how Mezmo's Active Telemetry approach helps engineers and SREs move from noisy application errors to immediate clarity. Using a restaurant ordering application running in Kubernetes, we trigger a database connection pool exhaustion issue and walk through two ways to investigate it with Mezmo.

See how Mezmo's AI Assistant instantly pinpoints root causes

This video shows how Mezmo's AI Assistant turns noisy telemetry into clear answers when errors spike. By preprocessing data and surfacing only the most relevant patterns, Mezmo quickly identifies issues like database connection failures or resource shortages and delivers actionable recommendations. Watch how AI-powered root cause analysis helps teams troubleshoot faster and with confidence. Mezmo's AI Assistant is built for platform engineers and SREs who need fast, reliable root cause analysis across high-volume telemetry pipelines — without manually sifting through noise.

Meet AURA: The Open-Source Agent Harness for Production AI : Autonomous Incident Response Demo

Watch AURA autonomously respond to a production incident in real time—from building its reasoning context and querying PagerDuty and ClickHouse, to triggering a human-in-the-loop approval with the on-call SRE, to removing the stuck pod and validating remediation. Every behavior is defined in a simple config. AURA is Mezmo's AI-powered incident response agent built for platform engineers and SREs managing high-volume telemetry pipelines.

How Kotak811 Revolutionized Digital Banking Observability with Coralogix

Kotak811, the digital-first engine of Kotak Mahindra Bank, is a banking platform serving over 23 million users across India. Since its launch in 2017, Kotak811 has transformed into the bank’s primary growth driver, now accounting for 70% of all new customer acquisitions. The platform is widely recognized for offering a paperless, mobile-first experience, providing everything from instant zero-balance accounts to seamless UPI payments and investment tools.

State of Observability in Financial Services 2026: From implementation to business impact

The demands on financial services companies are intensifying rapidly. They must not only deliver seamless system performance but also control costs, secure sensitive data, and maximize the value of their observability investments. To navigate these converging pressures, leaders are evolving their approach to system monitoring and telemetry. The 2026 State of Observability in Financial Services research report reveals a fundamental shift in how organizations manage their digital infrastructure.

The New Kubernetes Monitoring Experience in Splunk Observability Cloud

In this video, I walk through the three main pieces of the new Kubernetes monitoring experience in Splunk Observability Cloud: the Kubernetes overview page for monitoring the status and top issues across your environment, the Kubernetes Entities page for troubleshooting individual instances with correlated metrics, logs, events, and configuration, and the Workload Optimization view for getting actionable recommendations on your CPU and memory resource allocation.

What "AI-Ready Data" actually means for observability teams

Many organizations deploying AI are learning similar lessons right now: the challenge isn’t this or that AI model, it’s the data. According to Gartner, 60% of AI projects will be abandoned by organizations because of failures to support these projects with AI-ready data. Also, 63% of organizations either lack or aren’t sure they have the right data management practices to get there.

Code Agents Need Observability

For those of us using tools like Claude Code, Codex, or Gemini, we already know they’re powerful. They can write code, refactor functions, open PRs, even run commands. For a lot of developers, they’re already part of the daily workflow. But once you zoom out beyond the individual developer, the biggest problem isn’t productivity. It’s control. AI coding tools are powerful, but they introduce a new, unpredictable cost layer that most teams don’t fully understand.

AI agents are only as smart as the data you feed it

AI is only as useful as the context you give it. An autonomous observability agent can unlock serious value from your telemetry, but only when the foundation is right: good telemetry, a strong data layer, and efficient access to the data. Annie Freeman and Lewis Isaac had a lot to say about this at AWS Summit London this week! hashtag#Observability hashtag#AI hashtag#AWSSummitLondon hashtag#DevOps hashtag#OpenTelemetry.

Join operator and Query Agent for smarter log analysis

Sumo Logic’s log analytics capabilities have always provided the greatest insights to help you secure, monitor and troubleshoot your environment. Now, with our Query Agent, as part of Dojo AI, creating optimized log searches with natural language is even easier. Query Agent works with a wide variety of operators, including the join operator, for parsing, aggregation, data transformation, filtering, advanced analysis and lookup.

DataPrime at Ingest: Fine-Grained TCO Routing with DPXL

The real economic decision for observability happens at ingest, before storage, billing, and retention choices are locked-in. Until now, the logic governing that decision could only see three broad fields: application, subsystem, and severity. That just changed. TCO routing now matches on any field in the event payload, including nested keys, custom fields, and event body content, using DPXL, the DataPrime Expression Language.

What is Network Monitoring? Why Every IT Team Needs It (2026)

Learn what network monitoring is and why it’s critical for IT teams in 2026. Discover how it works, key metrics to track, and how to prevent downtime before users are impacted. Modern IT environments are complex—network monitoring helps you detect issues early, reduce downtime, and keep your infrastructure running smoothly. Watch now and monitor your network with confidence. Don’t forget to like, share, and subscribe for more IT insights.

Observability is a design problem: Live Laugh Logs ep. 1 - KubeCon Amsterdam 2026

What happens when 20,000 engineers descend on Amsterdam to talk about Kubernetes and AI? Welcome to Episode 1 of Live Laugh Logs, the podcast from Annie, Lewis and Andre from the Coralogix Developer Relations team where we will get together and recap everything going on in our worlds! We had an amazing time at KubeCon in Amsterdam and had loads of insights from the talks we went to around designing observability systems, all the AI tools being created and how to observe them, and using agent-generated code.

Building Audit-Ready Observability for Digital Banking

Most observability platforms are built to answer one question: what’s broken right now. Regulators are asking a different one: what happened, exactly, and can you prove it? Digital banking operates under constant regulatory scrutiny, where frameworks like DORA, PCI-DSS, and GDPR require every incident to be fully reconstructed across systems, timelines, and access. Systems can recover quickly, but the ability to explain what happened often remains fragmented across tools and teams.

Debug frontend issues with AI: Real user monitoring meets the Coralogix MCP server

It is 2 AM. Someone on-call gets paged. Conversion rates on the checkout page dropped 30 percent in the last hour. The immediate questions are familiar. Is this a JavaScript error? A slow API call? A broken third-party script? A performance regression that never throws an exception but quietly drives users away? In most teams, answering those questions is not hard because the data is missing. It is hard because the investigation is split across too many places.

The End of Manual Instrumentation: Scaling Observability with OTel OBI & Coralogix

Traditionally, achieving deep visibility into distributed systems required significant trade-offs in engineering time. Collecting meaningful application metrics and traces required teams to embed language-specific agents, modify source code, or manage complex library dependencies across every service.

OpenTelemetry Project Updates from KubeCon EU '26 in 10 Minutes | The Road to Graduation

OpenTelemetry Project Updates | Observability Day Europe Catch up on the latest OpenTelemetry project updates from Observability Day Europe. This session covers recent stability milestones, new tooling, and what's in progress across the OTel ecosystem.

JSON Jiu Jitsu: Has JSON Parsing Got You in a Chokehold?

From malformed fields to endlessly nested objects, JSON logs can feel like they’re trying to submit your SIEM. In this technical session, we’ll demonstrate how to turn that chokehold into a clean takedown using Graylog’s parsing, normalization, and enrichment capabilities. You’ll learn how to: Whether you’re a SOC analyst tired of regex wrestling or an admin looking to streamline onboarding, you’ll leave with practical techniques to make messy JSON your sparring partner—not your opponent.

The Runbook Problem: How AURA Documents What Teams Don't Have Time to Write

Runbooks are rarely missing because teams don't value them. They're usually missing because incident response, follow-up, and platform work compete for the same limited time. By the time an issue is resolved, the knowledge is fresh, but the window to document it is already closing. That gap creates familiar failure modes: over-reliance on senior engineers, slower handoffs, and less confidence for whoever is on call next.

Tech Talk | AI Agents in O11y Cloud

Transform reactive incident response with Splunk’s troubleshooting agents, designed to drastically reduce mean time to identify and resolve issues. This session demonstrates how a multi-agent approach empowers teams of all skill levels to pinpoint root causes, prioritize issues by business impact, and prevent future outages. Tech Talk sessions offer insightful and valuable deep-dives for any technical practitioner.

Spending More, Seeing Less: How Indexing Limits Capital Markets Visibility

Capital markets systems don’t scale linearly. A macro event, an earnings release, a sudden liquidity shift, and telemetry volume doubles in seconds. In most observability platforms today, that spike means one thing: every byte gets written to a high-cost index before a single query can touch it. There’s no middle ground. You pay full indexing cost for the compliance log that no one queries for six months, the same way you pay for the execution trace you need right now.

Introducing OrionIQ: The End of Manual Observability

OrionIQ is Logz.io’s new agentic observability platform designed to move teams from detecting issues to resolving them automatically. As AI accelerates software development, operations remain manual: engineers still wake up at 2 a.m. to investigate alerts and rebuild context. OrionIQ uses AI agents to analyze real-time telemetry, investigate incidents, identify root causes, and take action across systems.

Ep 37: Robbing banks is now a work from home job

In this episode of Masters of Data, we explore how banks and fintech companies have traded friendly neighborhood tellers for data-driven, always-on digital fortresses. We unpack everything from sophisticated phishing schemes and viral TikTok check fraud trends to the AI-powered tools that now handle the fraud detection Shirley the bank teller used to manage through sheer familiarity. We make the case that financial institutions today face more pressure than ever to be trustworthy, secure, and seamless all at once, whether their customers are logging into a sleek app or calling a landline to pay two bills a month.

Paris | Observability Unleashed - Boostez vos opérations IT, DevOps & SRE

La complexité des environnements IT ne cesse de croître. La visibilité en temps réel n'est plus une option. Le 14 avril 2026, Stéphane Estevez , EMEA Observability Market Advisor chez Splunk, vous invite chez Cisco à Paris pour un événement dédié à l'observabilité, avec les équipes Splunk & Cisco. Au programme : Observabilité assistée par l'IA Stratégies de données intégrées OpenTelemetry simplifié De la donnée à l'action, avec des cas concrets et démos live Observabilité pour l'IA et par l'IA.

KubeCon Europe 2026: OpenTelemetry Recap from Amsterdam

The reason why I like writing recap articles is because AIs don’t have enough context to write them for us. You have to be there, in person, listen to sessions, interact in the hallways with the community, and absorb as much new knowledge as possible. That’s what I did last week in Amsterdam at KubeCon + CloudNativeCon Europe ‘26. Well, at least I tried to. Let me break down what I consider the most interesting topics were last week.

Unified Logging for a Single Source of Truth

In Star Trek, the Borg are a cybernetic alien organism that forcibly assimilates other beings and technologies into its hivemind called “The Collective.” Each assimilated being or technology becomes part of the unified consciousness, with the villainous Borg Queen as the leaders. As the only independent thinker, the Borg Queen leads this rapidly adapting Collective.