Credential Management: The Hidden Production Bottleneck for Agentic AI on Kubernetes

Agentic AI has moved from experimental curiosity to a production imperative. Organizations are deploying AI agents that don’t just answer questions but take actions: querying databases, updating records, orchestrating workflows, and provisioning infrastructure. These systems are no longer confined to innovation labs and are increasingly embedded in core business operations. The question is no longer …

Coro Launches MCP Integration to Bring Security Operations Directly into AI Tools

Coro, the cybersecurity platform for organizations protected by lean IT teams, today announced new Model Context Protocol (MCP) capabilities that extend its AI-driven security platform beyond the Coro interface, allowing users to access, analyze, and take action on security data directly from tools like ChatGPT, Claude, and other AI environments. Coro enables teams to interact …

Observability Without Code Changes: The Promise of eBPF‑Native Architectures

There’s a problem with modern observability that almost nobody talks about openly: your monitoring stack might be hurting the systems it’s supposed to protect. I don’t mean in a theoretical sense. I mean that the agents and SDKs most teams rely on for visibility impose real overhead on the applications they instrument. CPU, memory, throughput. …

Standardizing AI at Scale: llm-d Joins the CNCF

In a significant move toward solidifying the infrastructure for production-grade AI, the llm-d project is being contributed to the Cloud Native Computing Foundation (CNCF) as a Sandbox initiative. This commitment, spearheaded by a multi-vendor coalition including CoreWeave, IBM Red Hat, Google, and NVIDIA, aims to establish an open standard for distributed inference. By integrating llm-d into the cloud …

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RSA Conference Roundup: — DeepTempo open-source AI SOC; ArmorCode study, Black Duck Signal, Cribl background detection

Vigil: An Open-Source AI SOC Built with a LLM-native Architecture A new open source project, Vigil, launched at RSA today, enhances the transformative intelligence of rapidly advancing reasoning models, including Anthropic’s Claude. Available under an Apache 2.0 license, Vigil — created by DeepTempo — ships with13 specialized AI agents, 30+ integrations, and 7,200+ detection rules spanning …

Three ways to automate Kubernetes incident management

Kubernetes has become the standard for container orchestration. It’s also notoriously challenging to manage when incidents arise. These incidents can come in many shapes and sizes, with their complexity forcing responders into firefighting mode. As a result, teams frequently end up chasing symptoms rather than finding and fixing the underlying cause. While Kubernetes incidents may …

Linux Foundation to Use $12.5M in Grant Funding to Advance Open Source Security

The Linux Foundation has announced it will use $12.5 million in grants to develop long-term, sustainable security solutions that support open source communities worldwide. This is necessary, the foundation said in its announcement, because rapid advances in AI have created a more complex security landscape with vulnerabilities being found in much greater numbers, leaving security teams …

Why Gateway API Is the Front Door for AI Workloads

The AI boom is reshaping application architectures. Large Language Model (LLM) inference has fundamentally altered the requirements of the Kubernetes networking stack. Kubernetes is now the default environment for scheduling GPU-accelerated workloads, but the last mile of delivery — connecting a user request to the optimal model instance — is increasingly a bottleneck. Traditional ingress …

Identity Debt: The New Source of Privilege Sprawl Overlooked by Security Teams

Let’s talk about debt. For years, enterprises have made decisions that help them move faster in the moment – taking shortcuts, postponing cleanup, or accepting imperfect visibility – knowing it will create technical debt they’ll eventually have to unwind. Many leaders accept this trade-off. While they know it will be a pain to deal with …

The Most Critical Element Of Your AI Strategy Is The One You Find Most Boring

I know the pressure you are under right now. In every meeting I attend with technology leaders, the conversation inevitably drifts toward the same mandate: “What is our AI story?” You are expected to explain how AI will predict the next outage, optimize traffic flows, and finally deliver the self-healing infrastructure that has been promised …

Zero-Trust Architecture for AI Pipelines: Why Your Security Model Needs to Evolve

Security teams have spent decades building defenses around network perimeters. AI pipelines make those perimeters meaningless. Data moves constantly between training environments, model registries, inference endpoints, and third-party services.  A fraud detection system I worked on in a large healthcare setting illustrates why: the workflow relied on governed clinical and claims data, real-time event signals, …

The Next Evolution of Observability: Why Your Telemetry Needs to be AI-First

The DevOps and Platform Engineering landscape is undergoing a massive shift. As AI-driven automation accelerates, the volume of machine-generated telemetry data is growing exponentially. Consequently, traditional observability platforms are struggling to provide the context and speed necessary for AI-scale operations. Existing tools, built for humans reading logs, are failing to keep up with intelligent agents …

Blind Spots in Hybrid IT: SolarWinds Report Finds 77% of IT

A critical misalignment between modern IT architecture and the monitoring and observability tools needed for full-stack visibility has led to those tools not being able to keep pace, according to the 2026 SolarWinds State of Monitoring & Observability report. The report found that: 77% of respondents cite limited visibility across on-prem and cloud environments 75% …

From Monoliths to Microservices to AI-Native: The Next Evolution of Distributed Systems

The architectural patterns that powered the microservices revolution are showing their age. When my peers and I began designing distributed systems for companies like Cisco, Amazon, and Palo Alto Networks, we optimized for stateless, horizontally scalable services with predictable resource consumption.  AI workloads follow a different set of rules. Transformer architectures demand frequent synchronization of …

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