Contributed Content
Why Your Kubernetes Readiness Probes Are Lying During Rolling Updates
Kubernetes readiness probes can pass while applications are still unable to serve real traffic. Protocol-aware checks help close the gap between “running” and truly “ready.” ...
Why CPU-Based Autoscaling Fails for Rails — and What We Used Instead
Kubernetes autoscaling works best when teams match the metric to the workload: queue latency for synchronous web traffic, queue depth for background jobs ...
Write Access Is the Easy Part: The Verification Gap in Agentic Kubernetes Remediation
Giving an AI agent the power to change a cluster is now straightforward. Confirming the change landed, did not produce unintended duplicate effects and achieved the outcome the operator actually wanted is ...
Production-Safe Security Testing: A Missing Layer in Cloud-Native Application Security
Cloud-native applications keep changing after deployment, making production-safe security testing essential for validating real vulnerabilities, misconfigurations and access-control gaps without disrupting live systems ...
K8sGPT and the Guardrails for AI-Assisted Kubernetes Troubleshooting
A practical way for platform teams to use AI for faster Kubernetes triage without giving agents unsafe control of the cluster. The first time an AI tool gets real cluster context, the ...
From Controls to Continuous Assurance: Rethinking GRC for Cloud-Native Environments
The standard process of building governance, risk, and compliance (GRC) programs has been straightforward: define a control, document a control, test the control on a regular basis, and generate a report for ...
Securing North-South Traffic in AKS Using Application Gateway, WAF and AGIC
Secure AKS north-south traffic with Application Gateway, WAF and AGIC, combining Layer 7 protection, end-to-end TLS, private back ends and strong ingress visibility ...
Prompt Injection in Cloud-Native AI Is Now an Access Control Problem
For a long time, prompt injection was treated like other model behavior problems, such as jailbreaks or strange responses. The usual fix was to improve the system prompt, add stronger filters, or ...
Autoscaling AI Workloads on Kubernetes With KEDA and What it Means for Agentic Systems
KEDA can scale Kubernetes AI workloads on real demand signals such as queue depth, helping model-serving and agent workloads respond faster while reducing idle compute costs ...
Rearchitecting Legacy Systems for Real-Time AI: Practical Patterns for Cloud-Native Migration
Artificial intelligence is changing what enterprises expect from software platforms. Systems that once processed transactions in batches are increasingly expected to evaluate events, apply intelligence and respond in near real time. The ...
