Operations | Monitoring | ITSM | DevOps | Cloud

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.

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.

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?

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.

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.

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.

If there was ever a year for AI observability, it was 2025. Vendors released assistants to cover a variety of use cases. Coralogix released the first agent (distinct from assistants!), Olly, an autonomous, multi-agent observability platform. The direction of travel is clear, but many vendors and users are about to run into some significant problems with their data layer.

As we wrap up 2025 and slowly come down from the re:Invent high, we’ve got one more reason to keep the celebration going. Coralogix has earned 192 badges in the G2 Winter 2026 reports and secured the position in the Momentum Grid Report for Observability Software. It is a strong finish to the year and a clear reflection of the steady progress the platform has been making.

Fleet management is the practice of monitoring and configuring your fleet of agents and collectors. Key functionality includes: Fleet management is the hallmark of an organisation that has realised the great importance of a healthy telemetry pipeline, and has taken steps to ensure that collectors & agents are every bit as robust as the production architecture for which they are responsible.

Tracing is one of the most transformative gifts of observability. It allows engineers to follow a single request through a distributed system and see every span and dependency along the way. However, even with that visibility, some of our most basic questions stay unanswered. Why did a specific span behave differently today than it did yesterday? Why did latency rise even when nothing “broke”?