Operations | Monitoring | ITSM | DevOps | Cloud

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.

Coralogix has spent years building metrics infrastructure that handles high cardinality and high dimensionality without flinching, with governance, usage visibility, and cost optimization built into the platform, and recognized industry delivery to show for it. Today that infrastructure takes its biggest step yet. We have rebuilt the metrics engine from the ground up, with a new pricing model, a set of new capabilities, and a tripled fair usage allowance to enjoy them in.

We are absolutely thrilled to share with you all that Coralogix has been recognized as a Leader in the Gartner Magic Quadrant for Observability Platforms. When we architected Coralogix around in-stream processing, open-format storage, and index-free query, we weren’t optimizing for where observability stood at the time. We were building for the world it was heading toward.

Coralogix and Sumo Logic are two different answers to the same observability platform decision. Where Coralogix processes telemetry in flight, stores it in your own Amazon Simple Storage Service (S3) bucket, and prices on data ingested, Sumo Logic keeps data in vendor-managed storage and, under its Flex model, bills for data scanned at query time. Both platforms have introduced pricing and artificial intelligence (AI) changes in the past year, and those changes have widened the difference between them.

Coralogix and New Relic both cover the full observability surface, but they charge for it and store it in different ways. One prices purely on data ingested and writes telemetry to a bucket you own, while the other combines ingest pricing with per-user licensing and retains data in its own backend. This guide covers how the two platforms compare on core features, pricing structure, AI observability, archiving and retention, security coverage, and support, then shows when each one is the stronger choice.