Systems | Development | Analytics | API | Testing

In the burgeoning intelligence economy, AI tokens are a metered utility, but enterprise profitability now hinges on a critical distinction: output tokens can cost up to 10x more than inputs, creating a new, invisible risk for cost overruns, particularly with Agentic AI. Learn how Kong AI Gateway and Konnect Metering & Billing provide the essential financial control plane to enforce directional guardrails, protect margins, and turn token consumption into realized revenue.

Federal agencies must perform a high-stakes balancing act: Modernize legacy systems, break down data silos, and deliver real-time citizen services—all while operating under strict security and compliance requirements with constrained budgets and staff. Today, we're announcing that Confluent Cloud for Government (CCG) is now available on the FedRAMP Marketplace, with FedRAMP Moderate authorization achieved through the competitive FedRAMP 20x Pilot program.

Apache Kafka powers massive, mission-critical data streams at enterprises worldwide. But in many organizations, those streams still behave like dumb pipes: raw JSON or bytes flowing between services, limited governance, weak contracts between teams, and data that’s hard to reuse for analytics or artificial intelligence (AI).

React Native teams ship fast. App store reviews do not. Today, CodePush officially launched on Bitrise, giving React Native teams the ability to deliver JavaScript and asset updates directly to users in minutes, without waiting for App Store or Play Store approval.

Software bugs are rarely small problems; they often lead to costly disruptions for both users and development teams. When issues reach production, they can trigger support tickets, emergency fixes, and lost revenue. The real challenge in software testing isn’t that bugs exist; it’s that they’re often discovered too late. Without strong quality assurance, teams end up fixing problems after release when the cost and effort are much higher.

Your WireMock stubs are lying to you. They were accurate when someone wrote them six months ago, but the payment API added a metadata field in January, the inventory service switched from REST to gRPC in February, and nobody updated the stubs because the tests still pass. Meanwhile, production is breaking in ways your mocks will never catch. This is not a WireMock problem. It is a hand-written mock problem.

Today marks a critical step forward for enterprise Node.js. In partnership with the OpenJS Foundation, NodeSource is launching a Node.js LTS Upgrade & Modernization program to provide companies with a secure and streamlined path to migrate business-critical applications off legacy and End-of-Life (EOL) Node.js versions and onto the latest Long-Term Support (LTS) releases.

Building AI agents that work reliably in production requires solving problems that have nothing to do with AI. While teams focus on prompt engineering, model selection, and agent orchestration, a different class of challenges emerges at deployment. These have little to do with LLMs and everything to do with keeping agents and clients synchronized in realtime. Over the past few months, we've spoken with engineers at over 40 companies building AI assistants, copilots, and agentic workflows.

AI has completely reshaped the boundary between human imagination and what’s possible. Along the way, AI use in business has become mainstream, with software delivery among its top adoption areas. In 2026, leading global technology companies are now using AI to generate the majority of their code, with some development teams reporting that they haven’t written code manually in months.

Thanks to AI, software today ships faster and with more complexity than ever before, and performance teams that rely on workflows built for a slower era are at risk of falling behind. Reliance on manual steps, niche expertise, and disconnected tools create bottlenecks that add risk to every release. Tricentis NeoLoad is leading this paradigm shift with AI-powered performance capabilities that close the gap and match the pace of validation to that of modern software delivery.