Systems | Development | Analytics | API | Testing

Beyond the Pilot: How Cloudera is Scaling AI Execution

Hey, did you know Cloudera is actively hiring to build the next phase of enterprise AI? While much of the industry is focused on experimentation, Cloudera is investing in execution, scaling real-world AI with innovations like Cloudera Agent Studio and managing data at exabyte scale. As we continue to bring AI to data anywhere, we’re growing our global team to turn AI from pilot to production.

Cloudera and NVIDIA: Accelerating AI Innovation with Trusted Data at Scale #Cloudera #Short #tech

As organizations race to capitalize on AI, the foundation of success lies in trusted data and scalable infrastructure. In this video, we explore how Cloudera AI, powered by NVIDIA, delivers an end-to-end platform that enables organizations to build, test, and deploy high-performance AI solutions. From the Cloudera hybrid data lake to production-ready AI, discover how Cloudera is helping enterprises accelerate their data-driven future.

Complete guide to understanding vision AI for object recognition | TestComplete

Testing complex UI elements like CAD software, Google Maps, or Citrix environments often leads to brittle tests and false negatives. Vision AI solves these automated testing challenges by recognizing elements just like a human would, reducing manual testing efforts, and improving accuracy. Discover how vision AI strengthens automated testing for visually complex applications. This tutorial shows you how to enhance object recognition in SmartBear TestComplete and eliminate test failures caused by 3D applications, canvas-based apps, and virtualized environments.

The Claude Bill is Too Damn High #speedscale #claude #aiagents #aicoding #devops #llms

Stop overpaying for AI reasoning by trading expensive GPU cycles for efficient, deterministic testing. This video explores how tools like linters and traffic replay can complement Claude, helping you fix bugs more accurately while cutting token usage by up to 50%. Visit: speedscale.com to learn more.

MCP in Production: Governing Agentic API Consumption | DeveloperWeek

As AI agents begin interacting with APIs, traditional API governance models need to evolve. In this DeveloperWeek session, Derric Gilling (WSO2) explains how organizations can manage and secure agent-driven API consumption using the Model Context Protocol (MCP). Unlike human applications, AI agents can generate large volumes of API calls from a single prompt. Without proper controls, this can lead to unexpected costs, security risks, and limited visibility into how APIs are being used.

Velocity can't come at the cost of quality

AI-generated code is flooding your pipelines. Your test automation debt is piling up. If this sounds familiar, you're not alone. Velocity can't come at the cost of quality. As AI transforms how we build software, API testing must evolve. Join Justin Collier, Senior Director, Product Management, and Yousaf Nabi, Developer Advocate, to explore the future of API testing in an AI-driven world.