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"Too much information running through my brain." When The Police sang this opening line on their 1981 album Ghost in the Machine, they weren't thinking about artificial intelligence, but the sentiment perfectly captures the state of modern AI. The song warns of an overload of data that parallels how modern AI agents process extensive collections of messages and data.

Apache Kafka powers real-time data at companies processing substantial event volumes daily. The new KRaft architecture makes getting started easier than ever. The platform handles massive data flows for more than 80% of Fortune 100 companies (Apache Kafka), according to the Apache Software Foundation. Event streaming represents a fundamental shift in data processing. Traditional databases save snapshots. Event streaming captures data in motion. It's the difference between a photo and live video.

The EU AI Act is here, and for many enterprises, it represents a massive coordination challenge. As the world’s first comprehensive AI law, it mandates strict governance on transparency, risk management, and data quality. For platform engineers and architects, the immediate question is operational: How do we comply with these new regulations without forcing every developer to rewrite their applications?

The integration of next-generation AI workloads — from large language models (LLMs) to speech-to-text and text-to-speech — demands a powerful, secure, and scalable infrastructure. This is especially true for building advanced AI voice agents, which rely on seamless, natural, and highly efficient user interaction.

The Kubernetes networking landscape is evolving, and recent announcements confirm a significant community shift. The Kubernetes community recently announced the upcoming retirement of one of its most widely used components: Ingress NGINX "To prioritize the safety and security of the ecosystem, Kubernetes SIG Network and the Security Response Committee are announcing the upcoming retirement of Ingress NGINX. Best-effort maintenance will continue until March 2026.

A burgeoning cutting-edge technology has been fundamentally transforming how we build automation inside disruptive businesses: agentic AI. The impact of agentic AI is already shaping up to be massive. And agentic adoption is soaring: Kong's Agentic AI in the Enterprise report found that, of those with visibility into their organization’s plans, 90% say their companies are actively adopting AI agents.

We’re excited to announce the general availability of Kong Insomnia 12!

Traditional API Gateways: Excellent for routing, auth, and microservice traffic; poor at AI workloads. Limitations: Can't track tokens, manage streaming responses, enforce content-level security, or use semantic caching. AI Gateways Purpose-built for LLMs with: Architecture Recommendation: Layered approach: Benefits: Lower costs (20--40%), better performance, centralized governance, future-proof AI infrastructure. Market Context.

Everyone's telling you to innovate faster with AI. Move quicker. Ship more features. Deploy more agents. But before we sprint headlong into the AI revolution, we need to have a proper dollars-and-cents conversation that most companies are avoiding. Disclaimer: Statistics cited in this post were reported in the 2025 State of AI Cost Governance Report by Mavvrik. The data is stark: 84% of companies report more than a 6% hit to gross margin from AI costs.

In January 2025, the OAuth 2.0 Security Best Current Practice became RFC 9700 (RFC 9700 - Best Current Practice for OAuth 2.0 Security). This technical milestone symbolizes a broader transformation. APIs are no longer just developer tools---they're regulated infrastructure powering everything from AI agents to telecom networks. The numbers tell a compelling story.