Operations | Monitoring | ITSM | DevOps | Cloud

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”?

Observability data has a habit of outgrowing everything else. As telemetry volume, variety, and velocity increases, staying organized gets harder. Governance becomes messy, and the cost of digging through “everything” keeps rising. Over the past year, Coralogix’s DataPrime engine has been addressing these challenges by laying a new foundation for observability at scale.

As teams grow and telemetry scales, it becomes harder to keep track of which metrics matter. Labels pile up, cardinality increases, and costs start rising faster than anyone expected. At the same time, dashboards often stay quiet and alerts go untouched. The truth is, most teams don’t actually know how and how much of their metric data is being used, let alone which metrics are driving cost. This is exactly the problem we set out to solve.

The last few years have felt less like a product roadmap and more like a scene from science fiction. Artificial intelligence didn’t simply arrive, it erupted. In what feels like a blink, we’re building software by prompting instead of programming. Our words now generate code, compose music, translate languages, and create entire digital experiences.

At Coralogix, we’re constantly looking to evolve the measurements we take to better understand the efficiency of our infrastructure. We constantly assess and investigate sources of cost in our cloud infrastructure, to ensure we’re getting the best return on investment. This activity, often referred to as FinOps, is becoming a cornerstone of engineering teams.