Systems | Development | Analytics | API | Testing

Data Streaming: The Key to Tackling Data Challenges for AI Success

As artificial intelligence (AI) matures from experimentation into production use cases, the symbiotic relationship between data and AI becomes increasingly clear. To deliver real business impact—smarter automation, better customer experiences, and massive cost takeout—AI use cases are only as powerful as the data they’re running on.

Troubleshooting Microservices with AI

Ever found yourself saying, "But it works on my machine!" when a bug pops up in a microservices environment? It's a common and frustrating problem. Unlike a monolithic application, microservices are a collection of independently deployed services that communicate with each other. This complexity makes it difficult to reproduce real-world issues on your local machine, as you may not have all the necessary services and dependencies running. But what if you could take a snapshot of a running application's behavior and bring it home for debugging?

How to introduce AI Tools into your QA process successfully

Every QA engineer has felt the crunch: tighter deadlines, growing complexity, and the same old expectation that everything must work perfectly by release day. It’s not an easy balance. That’s why AI in software testing has become such a hot topic. It promises faster test case generation, smarter insights, and support with tasks that usually eat up hours of time. But let’s be clear: AI isn’t here to replace testers.

Celebrating IT Professionals Day: Turning AI Wishes Into Trusted Outcomes

IT Professionals Day is our opportunity to celebrate the people who keep the digital world running - the ones who make sure data is secure, reliable, and ready to power innovation. At Qlik, we know IT professionals aren’t just solving problems, they’re enabling possibilities.

Multi-Cloud API and AI Infra Gets Smarter: Managed Redis for Kong DCGW

Modern enterprises are embracing multi-cloud strategies to avoid vendor lock-in, optimize costs, and ensure resilience. Yet managing API infrastructure (which also happens to be AI infrastructure) across multiple cloud providers while maintaining performance and simplicity remains a significant challenge.