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Speedscale Named in Gartner Market Guide for API Testing

In the highly dynamic environment of modern engineering, an appropriate strategy for API quality is more important than ever. We are pleased to announce that Speedscale has been named in the latest “Market Guide for API and MCP Testing Tools” report from Gartner. As software development is shifting towards complex distributed architectures, integrating Model Context Protocol (MCP) for AI-based workflows, the need for realistic testing has never been higher.

#053 - The Road to Distributed AI and Kubernetes Infrastructure with Matt Butcher (Fermyon) & Ari...

They share their professional origins, highlighting how Kubernetes transitioned from a complex tool for experts to a foundational technology for global enterprises.. Part of the conversation focuses on the history of Helm, explaining its growth from a simple hackathon project into a standard package manager. Another part takes on the future of distributed computing, specifically how Akamai is integrating infrastructure as a service to support modern workloads.

Context Management for Agentic RAG | Johan Jern, Co-founder & CTO at Realm

Some queries are hard to solve with "basic" RAG. When questions require multi-step reasoning, full-document understanding (not just chunks), or aggregating many results that match specific criteria, simple retrieve-and-generate pipelines break down, we need agentic RAG. But this added capability comes at a cost: as agents plan, search, read, and iterate, they quickly use up a lot of context, which both degrades answer quality and increases costs and latency.

Why Your Data Catalog is Your AI's Brain | Stan Dmitriev, AI Product Director at Aiven

Data catalogs are no longer just for compliance - they are the essential context layer for AI. While LLMs are powerful, they fail without the "tribal knowledge" found in metadata. This session explores how to transform your catalog from a static repository into an active nervous system for AI agents.

Rovo Dev Code Review in Bitbucket and GitHub | Bitbucket Blitz | Atlassian

The demo portion of a recent webinar I did shows how to setup, configure, and use Rovo Dev code review in both Bitbucket and GitHub. Learn how to add custom coding standards to your repositories and see Rovo Dev check for the specific things you care about during code reviews. Learn how to add acceptance criteria to your Jira work items and see Rovo Dev verify them during code reviews.

How To Design AI-Native SaaS Architecture That Scales Without Killing Your Margins

AI-native SaaS products aren’t failing because the models are bad. They’re failing because the architecture can’t keep up with how AI actually behaves in production. What looks affordable in staging can erode your margins once real customers, workflows, and automation come into play. Designing AI-native SaaS architecture is now as much a margin decision as it is a technical one.

The foundations of software: open source libraries and their maintainers

Open source libraries are repositories of code that developers can use and, depending on the license, contribute to, modify, and redistribute. Open source libraries are usually developed on a platform like GitHub, and distributed using package registries like PyPI for Python and npm for JavaScript. These repositories contain pre-written, re-usable code that developers use to add elements or features within their software projects.

AI-driven caching strategies and instrumentation

The things that separate a minimum viable product (MVP) from a production-ready app are polish, final touches, and the Pareto 'last 20%' of work. Most bugs, edge cases, and performance issues won't show up until after launch, when real users start hammering your application. If you're reading this, you're probably at the 80% mark, ready to tackle the rest.

AI Is Everywhere, So Why Isn't It Delivering Business Value?

Enterprises have never had more access to artificial intelligence and less certainty about what it is delivering. Generative AI tools now sit inside everyday workflows, embedded across productivity software and operational systems employees rely on for critical work. They generate insight at scale, reveal patterns more clearly than before, and offer earlier visibility into potential risk.