Systems | Development | Analytics | API | Testing

Kubernetes is Hard. Here is the "Easy Mode" for 2026

Is Kubernetes actually hard, or are we just using the wrong tools? In 2026, the Kubernetes ecosystem has become a "dependency jungle." Between GitOps, YAML configuration, kubectl mastery, and complex CI/CD pipelines, developers are spending more time managing infrastructure than writing code. In this video, Ken breaks down the "hard parts" of K8s and introduces a more efficient workflow using Speedscale. Learn how to gain instant visibility into your cluster, pull logs without the headache, and turn real-world traffic into actionable load tests.

Kubernetes Load Testing Made Easy with Speedscale

Everybody knows working with Kubernetes is really hard. It’s highly complicated. You have to know how to work with YAMLs, there’s lots of stuff to deal with. The classic developer experience with YAML. But what if you could get complete visibility into your Kubernetes workloads and run realistic load tests without touching a single YAML file or running kubectl commands?

Why gRPC is a Debugging Nightmare #speedscale #observability #grpc #testing #devops

gRPC is fast and efficient - until it breaks at 2:00 AM. Traditional observability tools are built for HTTP/1.1 and JSON. When you switch to gRPC, you’re dealing with binary Protobuf payloads and HTTP/2 multiplexing that most logs and traces simply weren't designed to handle. Speedscale flips the switch by decoding Protobuf directly into human-readable JSON in real-time. Get the speed of gRPC with the visibility of REST.

3AM Pager: When You Know the Data but Can't Search It

Ever tried searching your entire production stack for one user? Getting paged at 3 AM is bad enough. It’s worse when you only have a single username and zero visibility into what’s actually happening across your microservices. With Speedscale, you can perform full-text searches across every API call and database interaction in real-time. Stop guessing and start debugging with total context.

What Is Baseline Testing? Meaning, Examples & Use Cases

Every software change answers one simple question: Did something break? Baseline testing exists to answer it with confidence. Teams often ship regressions simply because they lack a reliable reference to compare against. In modern software testing, a baseline provides that reference point and helps teams understand change without slowing down delivery.

10 Surprisingly Powerful Projects You Can Run on a Raspberry Pi (2025-2026)

From smart home automation to self-hosted API backends, discover what the humble Raspberry Pi can really do as we head into 2026. As we close out 2025 and look ahead to 2026, the Raspberry Pi continues to punch well above its weight class. What started as an educational tool has evolved into a legitimate platform for home servers, IoT hubs, development environments, and even production-grade API backends.

Stateful Vs Stateless: A Developer'S Real-World Guide (2026)

Why do some bugs only appear after deployment, even when tests pass locally? Early in my backend work, I kept hearing discussions around stateful vs stateless. It felt academic at first, but once I started dealing with scaling issues, flaky tests, and production bugs, I saw how much this decision actually matters. This article is based on how I’ve seen these architectures behave in real systems, not just diagrams.