Systems | Development | Analytics | API | Testing

Did you know more than half of users will bail if your app doesn’t load in under three seconds? That’s not a fun stat. But it’s real, and it shows up fast, especially in high-traffic moments. Take an e-commerce app during a big sale. One delay during checkout, one stutter when loading the cart, and users are gone. That team watched retention nosedive because mobile app performance didn’t hold up under pressure. The problem wasn’t the features. It was the lag.

Agentic AI is transforming how businesses operate by enabling systems to handle complex tasks autonomously. Instead of relying on constant human input, these AI systems break down high-level goals into smaller tasks, make decisions independently, and improve continuously through feedback. Here's what you need to know: Key Features: Autonomously manage workflows and processes. Handle multi-step decision-making and problem-solving. Learn and adapt based on performance data.

Ever feel like you're fighting an uphill battle with your API strategy? You're building APIs faster than ever, but somehow everything feels harder. Wasn’t API-first supposed to make all this easier? Well, you're not alone. And now industry analysts are noting it as well. New Gartner research on successful API-first integration just came out, and it validates something we've been saying for a while: many organizations are fundamentally misunderstanding what API-first actually means. The result?

The rise of Model Context Protocol (MCP) has given AI agents and large language models (LLMs) a standardized way to talk to external tools, APIs, and data sources. In theory, it solves the messy integrations and custom connectors that have slowed down real-world agent adoption. A clean protocol should mean smooth interoperability. However, we’re observing certain patterns of fragmentation. Each MCP server runs in isolation. Agents have to handle multiple connections.

Today, we’re announcing that Kong has acquired OpenMeter, the open source and SaaS leader for real-time usage metering and billing. OpenMeter’s capabilities will be integrated into Kong Konnect, enabling usage-based pricing, entitlements, and invoicing for APIs, events, and AI workloads. This is a huge milestone for Kong, and we’re excited about what this means for our customers and the future of how you build and scale revenue-generating digital products for the agentic AI era.

The healthcare industry is buzzing about FHIR (Fast Healthcare Interoperability Resources). Pronounced “fire,” this widely adopted data standard has been revolutionizing how healthcare information is exchanged. But building a truly modern, secure, and scalable digital health platform takes more than just a data standard. Here comes SMART on FHIR, a framework that builds on FHIR to create a universal, secure, and user-friendly way for applications to access electronic health records(EHRs).

Integrating AI into enterprise systems is a high-wire act: you must deliver value quickly—without breaking security, compliance, or scalability. This guide distills security-first patterns CISOs can operationalize immediately: zero-trust for every AI interaction, least-privilege RBAC, end-to-end encryption and secret management, auditable-by-default pipelines, and a platform approach that minimizes custom code and speeds delivery. Bottom line: Treat AI like any external, untrusted client.

APIs have become the backbone of modern software architecture—but building and securing them is often harder than it should be. Developers today are expected to expose dozens of data sources as clean, secure, and compliant APIs—fast. From managing authentication to documenting endpoints and enforcing governance, the traditional approach to API integration comes with friction, delay, and technical debt.

Continuous integration and continuous delivery/deployment (CI/CD) in API management refers to the automation of building, testing, publishing, and promoting APIs across environments (development, staging, and production) using CI/CD practices. It brings DevOps principles to the API lifecycle, enabling faster and more reliable API releases.