Introducing the Coralogix CLI: Headless Observability for Every Agent. 
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Introducing the Coralogix CLI: Headless Observability for Every Agent
This article is a high-level overview of the Coralogix CLI. For a deeper look at...
How the Coralogix CLI Adds Production Intelligence to Any Agent for Any Use Case
The new interface into production telemetry is a tool call, made from whichever agent runtime...
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...
From Vibes to Signals: Observing Your AI Coding Workflow
Agentic coding tools like Claude Code and Codex have taken centre stage and inserted themselves...
What “AI-Ready Data” actually means for observability teams
The real AI bottleneck Many organizations deploying AI are learning similar lessons right now: the...
Code Agents Need Observability
AI coding is everywhere. But is it actually helping? For those of us using tools like Claude Code, Codex, or Gemini, we already know they’re powerful. They can...
Agent-First Observability: Dynamic Data, High Cardinality, and the Business Impact
We want to transform how companies make decisions. That is not what you expect to...
Debug frontend issues with AI: Real user monitoring meets the Coralogix MCP server
The 2 AM problem: you have data, but the workflow is fragmented It is 2...
Olly for SREs: 3 ways I actually use it in production
A practical breakdown of how I use an autonomous AI agent to investigate production incidents....
5 Essential Capabilities that Make Coralogix an Observability Powerhouse
Sometimes observability can feel like a second job. With many traditional tools, users must become...
A 4-Month Bug Fixed in <10 Minutes with Olly
In today’s highly interconnected systems, the subtle relationships between services are rarely obvious. Modern, complex architectures generate telemetry that functions less as “flashing signs” and more as faint...
The limits of MCP and how Olly surpasses them
Model Context Protocol (MCP) servers act as adapter layers between clients and AI based workloads. MCP installation into an IDE, such as Cursor, brings a wealth of information...
