Cloud Computing

In clinical informatics, every second counts. For Alcidion, a global leader in smart health solutions, the mission is simple but critical: use technology to reduce cognitive load for clinicians and present the right information at the right time to save lives. Whether it’s managing patient flow in an emergency department or ensuring a patient is […]

Written by: Chad Reams, Tufail Ahmed, Keith Knapp, Ashley Frazer, Tyler McLellan Introduction  From January through May 2026, Mandiant identified a financially motivated data theft extortion campaign executed by the threat cluster UNC3753 (also tracked as “Luna Moth,” “Chatty Spider,” and “Silent Ransom Group”) targeting dozens of organizations across professional, legal, and financial services in

At Google Cloud, our goal is to let you run large-scale analytical and data science workloads with maximum efficiency so you can process big data pipelines, machine learning, and ETL tasks.  We recently announced that the Dataproc service is now Managed Service for Apache Spark, reflecting our deep integration with the Agentic Data Cloud. To

While building AI agents locally using Google’s Agent Development Kit (ADK) is an excellent way to prototype, production-ready agents require a robust, scalable infrastructure. For developers looking to move beyond simple instances and into the world of managed container orchestration, Google Kubernetes Engine (GKE) Autopilot offers the perfect balance of flexibility and ease of use.

What do the organizations that succeed at digital transformation have in common? They align business and technical stakeholders around a shared plan before writing a single line of code. Yet research from McKinsey shows that 70 percent of transformations fail. Stakeholder misalignment and the inability to scale initiatives beyond initial pilots are patterns we see

Whether you use it for data preparation, real-time interactive queries, AI model training, or something entirely different, running Apache Spark at scale is demanding — you shouldn’t have to manage the underlying infrastructure too. Late last year, we announced the general availability (GA) of our serverless Managed Service for Apache Spark runtime version 3.0, prioritizing

Oracle databases power mission-critical enterprise applications, making their continuous availability essential for business operations. Traditional Oracle high availability (HA) solutions require complex clustering software, expensive shared storage arrays, and specialized database administration teams. These conventional approaches often introduce single points of failure while demanding significant operational overhead. Modern cloud architectures offer a transformative approach that