Systems | Development | Analytics | API | Testing

Building a Secure, Scalable AI Infrastructure with Kong and Akamai: A Technical Introduction

As organizations transition from experimental AI to production-grade systems, they often face a fragmented landscape of unmanaged LLM providers, complex tool integrations, and escalating security risks. This infrastructure gap leaves AI applications vulnerable to sophisticated threats like prompt injection and data exfiltration, necessitating a unified stack that secures the edge while streamlining the data plane..

From Kafka Chaos to Control: A Practical Guide to Governing Real-Time Data

Most engineering teams adopt Apache Kafka for one simple reason: it works. It scales effortlessly, it is incredibly reliable, and it powers real-time systems across almost every industry. But as your Kafka usage expands across different teams, regions, and external consumers, success creates a brand new problem. Kafka is a massive data firehose, and without the right nozzle, it quickly becomes unmanageable.

What Is an API? A Complete Guide to Application Programming Interfaces

Last updated: May 2026 An API (Application Programming Interface) is a set of rules and definitions that lets one software system request data or services from another. APIs are the connective tissue of modern software — every time a mobile app shows live data, a website logs you in with Google, or a SaaS tool talks to your CRM, an API is doing the work in the background.

Replay Real Customer API Sessions as Datadog Synthetics Tests

A customer pings support: “I tried to check out twice this morning and got a 500 each time, but it works fine for everyone else.” The session ID is in the email. You have full request/response capture in your environment, you have Datadog Synthetics already running browser checks against the same flow, and you still spend the next two hours grepping logs because none of those tools let you say “show me just this user’s requests, in order, and re-run them.”

Application integrity in the AI era | From the Bear Cave Ep. 3

The tsunami of AI-generated code creates downstream bottlenecks for QA teams, and shift-left or traditional test automation aren't enough in the AI era. In this From the Bear Cave session, SmartBear CEO Dan Faulkner and CMO Kelly Wenzel unpack how AI code generation impacts software quality and why traditional testing struggles to keep up.