Operations | Monitoring | ITSM | DevOps | Cloud

Beyond a Billion Spans: Using Highlights for High-Speed Root Cause Analysis at Scale

In late 2025, we introduced Trace Highlight Comparison. This capability was designed to solve the problem of having too many spans. This causes technical and financial challenges when identifying performance patterns within high-volume telemetry streams. The goal is to avoid massive indexing costs and eliminate the ingestion latency associated with indexing every record. However, knowing these trends is only half the battle.

How does Coralogix go beyond basic migration?

When a team, division or organization is assessing a new vendor, there are some basic questions that must be answered. At Coralogix, we look at migrations in a different way. It isn’t about transporting the current state of play into a new vendor, often called a “lift and shift”. These are the basics. There is a whole new level of onboarding and support that doesn’t just replicate value across platforms – it expands it.

Introducing System Datasets: Observing the Observability Platform

Modern observability platforms are great at explaining what’s happening in your apps and your infrastructure. However, all too often the observability platform itself remains a black box. As observability data and usage grow, governance almost always lags behind, and teams struggle to answer basic operational questions like: This valuable data is typically fragmented across admin UIs, billing pages, support tickets, and tribal knowledge.

Fleet Management: Manage your telemetry collectors at scale

In this video, we introduce Fleet Management and how it helps teams control their telemetry estate as it scales. See how you can centrally manage collectors and agents, standardize configurations across environments, and roll out updates confidently, reducing operational effort and risk.

Fair usage limits: a safer way to scale observability

For the past several years, Coralogix customers have used the platform to ingest, process, and analyze large volumes of observability data without the presence of artificial barriers or unexpected constraints. This flexibility has enabled teams to experiment freely, evolve their architectures, and scale smoothly alongside their systems.

Observability for Feature Flags

Some of your users are having a party; dancing away, having a great time. But a couple of users are stuck outside in the rain, knocking on the door, trying to get in. Unfortunately, you can’t hear them because of all the noise happening inside. That’s what it feels like when you gradually roll out new features across your user base without the right monitoring.

Sampled analysis of 10 billion spans with Coralogix highlight comparison

The CNCF reported that between 39% and 56% of organizations surveyed are now ingesting traces as part of their observability strategy. Tracing has become a cornerstone of any modern observability operation. Customers are regularly handling 10s of billions of spans every day, but with billions of spans, how can teams quickly figure out what is changing, what’s breaking, or what’s slowing down?

Confessions of a software engineer who enjoyed being paged at 5am

It’s 5:14am, and I wake up to the squawking geese sound of my PagerDuty alert (anyone else have this sound? No?). I’m four months into working for my new team as a junior software engineer, and this is my first time being paged in the middle of the night. Most software engineers probably dread this moment, but I kind of love it. Agile ceremonies and Jira tickets suddenly don’t matter, and you’re fully focussed on stopping a customer-impacting fire.

Building visibility and resilience across Kubernetes

Kubernetes has transformed how modern applications are deployed and scaled. Its flexibility and automation power innovation but also expand the attack surface. From control plane access to runtime drift, Kubernetes introduces layers of complexity that can obscure visibility if not properly monitored. For security leaders, Kubernetes is both an opportunity and a risk. While it enables agility, it also decentralizes security responsibility across teams, tools, and cloud layers.

Save the logs, save the planet: How to make your observability stack greener

If data centres were a country, they’d rank fifth in electricity consumption by 2026. Over the past few years, the resulting carbon footprint of the technology industry has sparked the fast-growing green software movement, led by the Green Software Foundation. How can we continue to innovate software in a way that also minimises its impact on the environment? This has been a fascinating problem I’ve been exploring for a few years now.