Last week in Paris, at KubeCon EU 2024, platform engineering was the talk of the event. The topic had a full-day co-located event and also a dedicated track during KubeCon itself. Here’s what I’ve learned from sitting in keynote rooms and then standing at the Spot and NetApp booth till my knees hurt. (Spoiler: It was well worth it.)

With applications becoming increasingly distributed and complex, gaining insights into their behavior and performance is essential for maintaining reliability and delivering exceptional user experiences. OpenTelemetry has emerged as a powerful framework for instrumenting applications to collect, process, and export telemetry data.

“We are drowning in noise all day long! Please help us!” -Every IT operations team Rich monitoring data is more important than ever for IT operations to manage the range of technology platforms and inter-connected systems the business runs on. One natural result of this is there are more signals and more noise that vie for operator attention.

Continued cloud adoption is leading to an increasing reliance on internet services, and on a complex mix of external service providers and technologies to deliver those services. For network operations teams, these moves significantly reduce visibility into the performance of the underlying infrastructure that business services depend upon. In spite of this diminishing visibility and control, these teams remain responsible for network performance.

Some issues can’t wait. When it comes to compliance or employee experience issues, time matters. Now with Nexthink Flow’s real-time event trigger, you can instantly trigger an automated workflow based off an event like an alert, employee login or application crash. When setting up a new workflow, you can select “Events” in the “Trigger” section and use a NQL query to identify the event to track.

We’ve come a long way. 25 years ago, a network engineer had an idea. The tools he used to solve IT problems weren’t as simple or effective as he needed—and they didn’t work how he wanted them to work. So, to make his team’s daily routine a little easier, he created his own.

With great power comes great… complexity? When we introduced Grafana Alerting a few years ago, it included a powerful routing feature that teams could use to send alerts to various contact points. Unfortunately, this functionality also came with a fair bit of complexity and an unfamiliar UX. This prevented many users from adopting it, but we’re still big believers in how it can help users.

There’s a common misconception about running workloads in the cloud: the cloud provider is responsible for reliability. After all, they’re hosting the infrastructure, services, and APIs. That leaves little else for their customers to manage, other than the workloads themselves…right?

Google Cloud provides a wide range of services and tools to help engineering teams reduce the complexity of migrating and deploying applications in the cloud. As engineering teams work to improve the performance, reliability, and security of their applications, they also need to be conscious of cloud costs. But engineers often don’t have access to cost data, or they only see cost data in monthly reports.

Observability goes beyond monitoring; it's about truly understanding your system. To achieve this comprehensive view, practitioners need a unified observability solution that natively combines insights from metrics, logs, traces, and crucially, continuous profiling. While metrics, logs, and traces offer valuable insights, they can't answer the all-important "why." Continuous profiling signals act as a magnifying glass, providing granular code visibility into the system's hidden complexities.