Systems | Development | Analytics | API | Testing

Before you start, paste this into Claude Code, Cursor, Codex, Gemini CLI, Kiro, or any assistant that can read a URL and run commands: The install-speedscale skill installs proxymock for your operating system and walks you through proxymock init. It stops when you need to complete browser sign-in, keeps your recordings on your machine, and connects the proxymock MCP server so your assistant can run the prompts later in this article.

Today we're announcing Kong Operator 2.3. Building on 2.2's expansion into supporting Event Gateway and Dev Portal, this release significantly broadens our feature set. While 2.2 introduced foundational event-driven capabilities, 2.3 brings Kong **AI Gateway** fully into the Kubernetes-native fold, enabling teams to manage LLM routing and policies through familiar GitOps workflows. This update also rounds out Gateway API coverage with `TCPRoute`, `UDPRoute`, and `GRPCRoute`.

The first number from my local PostgreSQL 16 test was roughly 1,600 statements per second. It looked impressive. It was also the least useful result in the run. The useful part was the workload. It came from queries the demo app had actually sent: the same prepared statements, parameters, reads and writes. A synthetic benchmark tells you how PostgreSQL handles a synthetic workload. It does not tell you whether your migration just broke the UPDATE your app depends on.

Remember when “going shopping” meant getting in the car? This fall, filling the tank feels like applying for a small loan. U.S. regular gasoline averaged about $4.48 a gallon for the week of September 21, 2026. A round trip to the store starts competing with free shipping. And free shipping never needs a parking spot. That doesn’t tell us how many shoppers will move online this holiday season.

Test libraries that once felt instant can become harder to manage as they grow: test cases take longer to open, reports take longer to build, and every sprint adds more data to an already bloated Jira environment. That’s usually the moment when a testing leader starts evaluating whether the test management tool installed years ago still fits the way the organization tests today. Your team has already decided to run testing inside Jira.

AI agents review code, triage incidents, summarize tickets, and draft documentation, and the industry has largely decided the help is worth having. Leadership is often pushing teams for AI productivity gains and many teams accept the mandate. The obstacle is what happens next: the agent works on the wrong thing, the time and money spent on it return nothing, and the team ends up less efficient than before it started by creating more work.

At Insomnia, we believe your tools should support you (and your agents!), not force you into certain ways of working. Over the last few months, we’ve been hard at work streamlining our interface so that it’s easier than ever for you to get started, stay organized, and work however you want with your APIs. There are two key concepts when a developer works with an API.

*Enterprise AI governance requires a composed stack connecting high-level risk and compliance oversight with real-time runtime enforcement. While oversight tools manage inventories, approvals, and evidence, AI gateways apply policy controls directly to live model, API, MCP, and agent traffic. Implementing both runtime controls and structured governance frameworks ensures comprehensive security, observability, and cost management across your entire AI estate.*