Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on Log Management, Log Analytics and related technologies.

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.

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.

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.

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.