What's popular
How VCF 9.1 Consolidates the Management Plane into a Single Unified Platform
VCF 9.1 revolutionizes VMware Cloud Foundation by consolidating four appliances into a unified VCF Management Services platform, enhancing operational simplicity and efficiency. This architectural shift demands careful upgrade planning but promises streamlined management and centralized observability, making the transition a worthwhile endeavor for VCF 9.0.x users.
AI Habits for a Sustainable Future
AI is one of the most powerful tools we have today. But like any powerful tool, it comes with responsibility. This Earth Day, WWT's Global Green Teams and Sustainable Softchoice collaborated to take an honest look at one responsibility that often goes unnoticed: the actions we users can take to reduce AI's impacts on our environment.
Cisco SR-MPLS or Cisco SRv6 uSID: Choosing the Right Path for Your Network
A deep-dive comparison of Cisco's two Segment Routing implementations — SR-MPLS, built on the proven MPLS data plane, and SRv6 uSID, built natively on IPv6 — where they diverge, where they excel and how to choose the right path forward.
AI Security: Practicing Good Model File Security
As organizations continue to incorporate AI solutions into their workflows and user toolset, the requirements for securely creating, acquiring and storing large AI model files have grown significantly. This blog post explores the risks presented by third-party AI model files and best practices to guard against those risks.
Beyond Log Reduction: AI and the Future of Security Data Strategy
The data pipeline space has evolved far beyond simple log reduction and transformation. As organizations look to AI to solve complex problems without adding cost or headcount, Security Data Pipeline Platforms are emerging as the foundation of a true data strategy. This article explores three key findings from a three-month vendor evaluation, uncovering how AI is reshaping log reduction through intelligent feedback loops, enabling autonomous pipeline health monitoring, and dramatically accelerating data onboarding, turning what once took days into a matter of minutes.
What's new
Stop Defending at the Refusal Boundary
AI safety measures hinder defenders while attackers bypass them, creating a cybersecurity imbalance. Programs like Anthropic's CVP and OpenAI's TAC aim to empower vetted defenders. The challenge is to enable defenders without restricting them, ensuring AI tools aid rather than obstruct security efforts.
The Watch Problem: Who Catches What the Autonomous SOC Misses
The autonomous SOC is coming. That's not the debate. The debate is what happens to the analysts who were supposed to catch what the AI can't, and whether anyone is building the doctrine before we find out the hard way.
The VCF 9.1 Upgrade, Step by Step: What Actually Happens
Embark on a transformative journey with the VCF 9.1 upgrade, where architectural evolution meets meticulous planning. This guide navigates the intricate steps, from upgrading VCF Operations to deploying containerized management services, helping make the transition seamless. Prepare for a leaner, unified management plane, but remember: precision in preparation is key.
Before You Upgrade to VCF 9.1: What You Need to Have Ready
VCF 9.1's upgrade is transformative, retiring the Fleet Management Appliance for a Kubernetes-based runtime. This guide details essential pre-upgrade steps, from IP planning to pre-flight checks, to help create a smooth transition. Prepare meticulously, as management visibility gaps and irreversible changes await. Part 2 will explore the execution phase.
Building an Automation Framework
Discover the transformative potential of automation with our comprehensive Automation Framework. By integrating industry-leading tools like NetBox and Ansible, we streamline operations, enhance cross-functional collaboration and drive innovation. This framework empowers organizations to achieve strategic goals, optimize AI integration and foster a culture of continuous improvement.
The Tokenomics of AI Native Engineering: Engineering the Cost Model
The patterns, model routing strategies, infrastructure options and engineering practices that bring AI native development costs under control.
The Tokenomics of AI Native Engineering: The Cost You Didn't Budget For
The productivity case for AI-Native Engineering is real. So is the API bill. How you architect your model usage, including which model handles what, when you escalate and what you cache, is becoming as important as the code itself.
Building Agent Systems on Small Local Models
Inside an enterprise network you often can't send data to a hosted model, and a local frontier model is too expensive to run. A ~30B model is the practical sweet spot, but it hallucinates, its knowledge is thin and its usable context is short. Here's how to build a real agent on top of it anyway.
Trust but Verify: Rethinking AI Risk from Pilot to Production
With generative AI, the edge no longer comes from having the best model. It comes from knowing when to trust the model's output.
Attention! Keys, Values, Caches, Offloading, WEKA, KOVE and the Research Community
In large-scale inference, transformers' KV memory demands surpass model weights, challenging GPU resources. Innovative KV management strategies, like TurboQuant and TriAttention, offer post-training solutions to optimize memory use without sacrificing accuracy. These advancements, crucial for cost-effective AI deployment, demand continuous attention from architects to maintain competitive edge.
EEI 2026 Highlights Affordability, AI Adoption, and Interconnection as Top Utility Priorities
World Wide Technology attended EEI 2026 in Las Vegas, where affordability, AI adoption, grid interconnection and workforce development dominated the conversation. Utilities are under pressure to absorb unprecedented load growth without raising customer rates. WWT has the solutions to help, from AI-powered grid planning to strategic resourcing, and left with new relationships and momentum heading into the second half of 2026.
Agentic AI in Life Sciences Manufacturing
Every life sciences application is quietly shipping AI agents inside routine upgrades; no strategy meeting required. This replays the ERP sprawl mistake, only faster and quieter, and this time touching GxP decisions regulators expect to trace. We predict that by 2027, it will be everywhere. The fix is deciding, now, who owns the architecture and who owns the agent.
Identity is Infrastructure: Why IAM Must Be Recoverable
Identity is the backbone of modern enterprises, crucial for operations and recovery. Examining incidents like Maersk, Conti and Stryker reveals identity's pivotal role in cyber resilience. Effective recovery demands treating identity as tier-0 infrastructure, ensuring trust restoration and integrating identity into all resilience strategies.
The Art of Conflict: Revisited, After the First Shock of the Iranian Conflict
Iran's cyber activities highlight the fragility of global infrastructure dependencies, emphasizing resilience over mere cybersecurity. Organizations must prioritize critical service continuity, test recovery strategies and govern resilience as a national security priority. The strategic shift from incident response to managing contested infrastructure underscores the need for robust, cross-functional resilience planning.
The Connected Enterprise - Part 4: From Visibility to Intelligence
How AI-assisted operations, GreenLake Intelligence and autonomous infrastructure are changing the future of enterprise IT. Part 4 of 4
The Connected Enterprise - Part 2: One Operational Story
How Mist, Apstra, Marvis, Flow and GreenLake Begin Connecting the Enterprise from Client to Cloud. Part 2 of 4
AI Vulnerability Discovery Is Not the Hard Part. Operationalizing It Is.
AI-driven vulnerability discovery is rapidly increasing the volume and speed of findings, but most organizations are not prepared to act on the output. This article breaks down the operational gap between AI-generated findings and what security teams can actually detect and respond to.
What AI Vulnerability Discovery Means for Detection Engineering
AI-driven vulnerability discovery changes how weaknesses are identified, but it also shifts how detection must be built. This post explores how detection engineering evolves from indicator-based logic to translating exploit paths into observable and actionable security telemetry.
Your Detections Won't Catch This
AI agents introduce a new detection failure mode: activity that passes every rule but still produces the wrong outcome. This post explores why event-based detection breaks and why the signal now exists in the sequence, not the event.
Your Security Architecture Wasn't Built for This
AI agents introduce a new failure mode: systems that pass every access check but still produce unintended outcomes. This post explores why that happens and why it's an architectural issue, not a detection or tuning problem.