Scaling the deployment, in order to meet demand or extend capabilities, is a known challenge in many fields, but it’s particularly pertinent when scaling microservices. This article looks at the challenges of scaling microservices and examines best practices to overcome them while maintaining app quality, dev efficiency, and a good developer experience.

eBPF, or Extended Berkeley Packet Filter, is a kernel technology available since Linux 4.4. It lets developers run programs without adding additional modules or modifying the kernel source code. Think of it as a lightweight, sandboxed virtual machine (VM) within the Linux kernel that lets you run Berkeley Packet Filter (BPF) bytecode that uses certain kernel resources. Utilizing eBPF removes the need to modify the kernel source code and improves the software’s capacity to use existing layers.

On-call shifts are part of every developer’s job – we’ve all been there. It’s 3am, suddenly you get an alert for an issue occurring in production. The microservices landscape is complicated and finding the root cause of an issue is like looking for a needle in a haystack. How can you get to the root of what’s happening in the system so you can analyze and resolve the issue quickly and effectively?

When I first met Uria Franko, the CTO of Novacy, I immediately knew we’d hit it off. He was looking for an observability solution for his team with a specific need around Celery, after they had been using logs but found they lacked the depth and granularity they needed. Luckily, our mission at Helios is to help organizations gain visibility and drill down into services through traces. So this was a perfect match.