Operations | Monitoring | ITSM | DevOps | Cloud

The Coralogix migrations team has published what it measured. Since 2023 the team has moved more than 75,000 assets across 300+ migrations and onboardings, including a single migration of about 41,000 alerts. The new Migration Benchmarks page holds the figures by source, a calculator for your own migration and the causes of delay that post-migration reviews name most.

Your coding agent can debug production issues now. Yes… Not just “help you debug.” Actually run the investigation… FOR YOU! In this new era of agentic development, speed matters. And in the old days (you know… last week or so) we used to investigate production bugs ourselves. Manually. Like humans. But for a lot of incidents, we don’t need to do all of that anymore.

With GitOps, you can roll back your cluster with git revert and explain each approved change through a commit log. Routing normal changes through Git and running an in-cluster agent that detects drift from the repository gives infrastructure changes the same review and rollback discipline as application code, and Git preserves their history. This guide covers the four GitOps principles, the pull-based reconciliation workflow, and the tools and practices you need to get started.

Coralogix APM has told you which service is behind the latency. From today, the new APM experience tells you what is behind the service: the release, the environment, or the query one layer down. It watches every service you run from the moment it appears, without anyone writing an alert. And everything you see on the screen, your AI agent can use too: in Olly, from the Coralogix CLI, or through MCP in your IDE. A latency chart shows that something got slow.

Every page view, click, and session your RUM SDK captures lands in Coralogix as a log event under the cx_rum subsystem — the raw data behind how people actually use your product. You can turn it into a shareable report without writing a single query. Just ask your coding agent. Your agent queries that data through the CX CLI and writes the report for you: describe what you want in plain English, get a formatted report back — without leaving the terminal.

Tuning guardrails can take time. To accelerate this, we combined the power of Claude Code, Coralogix Telemetry and the CX CLI, to build a loop that iterates on guardrails. To test our loop, we built a fictional chat interface for an iGaming operator, that took bets, gave odds on markets and more, but with a catch: this agent was not permitted to make predictions about where the market was going. With our goal in place, we got to work designing our loop.

The OpenTelemetry Operator changed how teams approach telemetry collection in Kubernetes. The core appeal of zero-code instrumentation is that you can bring up telemetry inside application containers to collect traces, metrics, and logs without touching your source code or rebuilding your container images. However, if you follow the default OpenTelemetry Operator documentation, you quickly run into a heavy operational prerequisite: the Instrumentation CRD.

An agent that only speaks when spoken to is a tool you have to remember to use. Olly has run on a schedule for a while now, working a saved prompt hourly, daily, weekly, or monthly and writing its findings into a chat with its own run history. Those scheduled tasks are now wired into the Coralogix Notification Center, so Olly delivers that output itself, allowing Olly to reach out to Slack or email, out of the box.

Coralogix Real User Monitoring has spent years collecting full-fidelity user sessions: every session and event processed in stream, without sampling and without prior indexing, at rest in cloud object storage you own. Today that data does a second job. Product Analytics brings heatmaps, funnels, and pathways to the RUM sessions you already send, with no second SDK to install. One dataset now answers what your users did and why it happened.

FinOps spent a decade making cloud spend predictable, and teams now point the same discipline at a workload that behaves nothing like a virtual machine. In the FinOps Foundation’s State of FinOps 2026 survey, drawn from 1,192 practitioners representing more than $83 billion in annual cloud spend, 98% now manage AI spend, up from 31% two years earlier. The main driver for this was agents.