Systems | Development | Analytics | API | Testing

How To Make Sense of Enterprise-Level Data With Google Cloud's Vertex AI and BigQuery

As an application developer integrating analytics into your application, your users expect a scalable, flexible solution that adapts to changing business needs. While organizations strive to capitalize on new AI tools, they’re also still wrestling with big data: massive, fast-moving datasets that traditional tools can’t handle easily.

Cloud Application Testing Guide: Key QA Strategies

Imagine your enterprise app testing runs smoothly under normal traffic, but during a flash sale, it crashes under the sudden surge of users. The root cause? The cloud application testing failed to uncover critical scalability gaps. This is happening more and more in 2025 as companies are moving to the cloud, but are underestimating the complexity of testing at scale. With cloud adoption accelerating, traditional testing can’t keep up with modern app demands.

Best Cloud-Based Automation Testing Services 2025

It's 3 AM, and during the testing process, your mobile app crashed in the middle of high traffic. Your outdated test infrastructure is unable to mirror real-life scenarios fast enough, and serious problems go undetected. On the other hand, a competitor provides a seamless user experience as they embrace Cloud-Based Testing and gain unmatched flexibility of open devices, speed of finding defects with their rapid scalability.

Bitrise is now available on Google Cloud Marketplace

Hey there, Google Cloud customers! We've got some exciting news to share with you. You can now purchase Bitrise through Google Cloud Marketplace as a private offering. That's right: the lightning-fast mobile CI/CD infrastructure and powerful automated workflows you love from Bitrise, now with all the convenience of procurement and consolidated billing through Google.

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.