Tag: cloud adoption
6 articles
Federal Agencies Drive Healthcare Transformation with Cloud Tech
Federal healthcare agencies face a daunting challenge: modernizing critical systems while millions of Americans rely on them - it's like changing a plane's engine mid-flight. Cloud technology is key to navigating this transformation, enabling agencies to deliver patient-centered care without interruption.
Defense Agencies Pursue Multi-Cloud Strategies to Bolster Operational Tempo
As defense agencies shift their focus beyond mere cloud migration metrics, they're now prioritizing a new set of goals that will give them a decisive edge in the digital landscape. They're leveraging multi-cloud strategies to drive decision advantage at scale, financial transparency, and operational tempo.
Technology Must-Have: Best Playbook for Federal IT
federal IT modernization doesnt have to be a choose‑your‑risk gamble: a compact playbook—technology, innovation, cybersecurity, and knowledge management—helps agencies prioritize investments, limit disruption, and keep mission delivery on track.
Carter Farmer Exclusive on Effortless EPA Efficiency
Carter Farmer asks a bold question: what if EPA efficiency was measured by mission outcomes — cleaner air, faster permits, and reduced hazards — instead of processes? He says an outcomes-driven approach can streamline operations, sharpen investment decisions, and make the agency’s impact unmistakably visible to communities and Congress.
SharePoint zero-day: Must-Have Fixes for Critical Risk
A critical SharePoint zero-day has surfaced that can let attackers move from a foothold to full data theft—here’s what to patch, harden, and monitor now to stop it. With simple fixes like prompt updates, stricter configs, MFA, and better logging, you can turn a risky platform back into a safe collaboration tool.
AI Zero Trust Security: Must-Have, Risky Reality
AI-powered Zero Trust promises smarter, faster defenses—adaptive risk scoring, real-time responses, and less analyst fatigue—but also introduces risks like biased models, data poisoning, and tricky governance challenges. Balancing those trade-offs with quality data, transparent policies, and human oversight is essential to make AI Zero Trust both effective and trustworthy.