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The secret sauce that powers Agentic Development Environments (ADEs) like Kepler is a little thing called the Agent Client Protocol (ACP). In this context, Kepler is the Client and harnesses like Claude Code and the Codex CLI are the Agents. We’re going to go over some of the details about how it works, how we use it at GitKraken, and how the protocol may be changing for the better.

Twenty years ago at RMIT, I became preoccupied with a question that sounded technical but was really about corporate value: could you predict how difficult a company would be to acquire by looking at the shape of its APIs? It was 2006. I was completing Honours in a Bachelor of Applied Science in Software Engineering, and the brief for my research project was unusually open: find an impactful software research hypothesis that hasn’t been done before.

Learn how DDoS attacks work, how threats are evolving, and how modern network-integrated protection can help defend your infrastructure. Network connectivity is the frontline of revenue generation and customer trust for almost every modern enterprise. But as digital footprints expand across hybrid and multicloud environments, Distributed Denial of Service (DDoS) attacks continue to grow in volume, frequency, and sophistication.

This assessment estimates how much exposure you carry. The output is a short read on which parts of your stack would resist a change you might need to make. The score is for an internal conversation that surfaces specific decisions.

Disaster recovery (DR) is one area where organizations often assume public cloud has the answer already. Multi-region deployments, managed backup services, automated failover - the hyperscaler catalog is full of DR-flavored offerings, and the marketing suggests that resilience is a solved problem once you're on cloud infrastructure. For many workloads, this is roughly true.

For more than a decade, the prevailing wisdom in enterprise IT was simple: move everything to the public cloud. Hyperscale platforms promised unlimited scalability, lower costs, agility and freedom from the burdens of managing infrastructure. Cloud-first has been rapidly gaining momentum as the de facto path to a modern digital footprint. Until now.

Teams running containerized workloads on Google Cloud have long relied on JFrog as their single source of truth for container images. The missing piece has been getting Google Cloud’s own runtime services — like Cloud Run and Google Kubernetes Engine (GKE) — to pull directly from JFrog for every container image pull. I’m happy to say that the gap is now closed. Artifact Registry in Google Cloud has introduced a new repository mode called Connector that addresses this requirement.