Systems | Development | Analytics | API | Testing

What's new in SmartBear ReadyAPI: AI-powered test generation | ReadyAPI

SmartBear ReadyAPI's AI-powered test generation instantly builds functional test cases from a simple natural language prompt. Stop writing API tests manually and let AI do the heavy lifting. In this demo, we show how you can take an OpenAPI spec and generate tests complete with assertions, authentication headers, test data, and request chaining. Whether you test complex microservices or APIs with hundreds of endpoints, ReadyAPI helps QA teams move faster without sacrificing quality or control.

What Is Sandbox Testing? Types, Benefits, And Best Practices (2026)

Sandbox testing catches the failures that staging misses, and production makes expensive. Every team reaches a point where testing against real systems stops being practical. The payment gateway costs money per call. The third-party notification service has rate limits. One wrong database query corrupts shared test data and breaks everyone’s runs. A sandbox environment for testing gives you an isolated, controlled space where none of that matters.

Mock Testing: A Complete Guide For Developers (2026)

How much of your CI runtime is spent waiting on APIs that return the same response every time? For most teams, it’s more than they realise. Mock testing cuts that wait to zero. Instead of calling real services, teams simulate the responses they need. Faster feedback, better isolation, and test runs that don’t fail because a payment sandbox was slow. But like most testing techniques, mocking works well only when used correctly.

The API testing gap: How AI-accelerated development challenges software quality

While AI accelerates development velocity by a factor of ten, a critical consequence remains: testing hasn’t kept pace. According to SmartBear research, 70% of software professionals report that their application quality has already degraded due to AI-accelerated development. Even more concerning, 60% have experienced quality issues in the past year as development velocity outstrips testing capacity.

Building an API Gateway with Koa and AppSignal

In an API-driven setup, a gateway often sits between clients and backend services: it can validate input, aggregate upstream responses, and give you one place to observe traffic. Koa is a strong fit for that role. Its core stays small, async/await is first-class, and middleware composes in a predictable stack. In this article, you will build a compact API gateway with Koa that: You will also wire up AppSignal for the Node.js stack.

Oracle MCP Server: Connect Oracle Database to AI Agents Safely

Last updated: May 2026 An Oracle MCP server is a service that exposes Oracle Database data as tools an AI agent can call through the Model Context Protocol (MCP). Rather than handing an LLM direct credentials to a database holding ERP, financial, or healthcare records, you put an MCP server between the agent and Oracle.

Snowflake MCP Server: Conversational Analytics with AI Agents

Last updated: May 2026 A Snowflake MCP server is a service that exposes Snowflake warehouses as tools an AI agent can call through the Model Context Protocol (MCP). It sits between AI clients like Claude or ChatGPT and your Snowflake data, translating discoverable tool calls into governed SQL — with row access policies, dynamic data masking, query budgets, and audit logging applied automatically.

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