platform engineering

Runtime Visibility & AI-powered Security in Cloud-Native Environments
Kubernetes and cloud-native platforms have transformed software delivery — but also redefined the attack surface. As threats shift to runtime, visibility and real-time response have become the new security frontline. AI-driven anomaly ...
Alan Shimel | | AI copilot, AI governance, AI in cybersecurity, anomaly detection, automated response, CI/CD security, cloud native security, cloud security, cloud-native defense, container security, DevSecOps, explainable AI, kubernetes, LLMs in security, observability, platform engineering, runtime protection, runtime security, runtime visibility, security automation, security telemetry, service mesh, threat detection, zero-trust

LLMs & Kubernetes Configuration: Automating Hardening, Drift Detection and Policy Enforcement
Kubernetes misconfigurations remain the top security risk. AI copilots promise automated hardening, drift detection, and policy enforcement to make clusters safer ...
Alan Shimel | | admission controllers, AI copilots, AI in Kubernetes, cloud native security, cncf, drift detection, GitOps, KubeGuard, kubernetes, Kubernetes governance, kubernetes hardening, Kubernetes misconfiguration, Kubernetes security, Kyverno, large language models, LLMs, OPA, OpenTelemetry, platform engineering, RBAC, YAML Jenga

Service Mesh Evolution: Ambient Mode, Gateways & The Return of Simpler Architectures
Service mesh is evolving beyond sidecars. Ambient mode and Gateway APIs deliver security, observability, and traffic control with less overhead. Teams benefit from leaner, more flexible architectures ...

Stateful Microservice Migration & the Live-State Challenge in Kubernetes
Alan argues that Kubernetes can’t ignore state any longer. While stateless apps fit the original vision, real-world workloads — from databases to AI pipelines — demand continuity. A new research framework, MS2M ...
Alan Shimel | | AI/ML pipelines, blue/green deployment, canary releases, cloud portability, cncf, CRIU, Data Sovereignty, day-two operations, disaster recovery, forensic container checkpointing, hybrid cloud, kubernetes, live migration, MS2M, multi-cluster, platform engineering, resilience, service mesh, Stateful Workloads, stateless vs stateful

Bridging Observability & Security in Kubernetes: Beyond Just Metrics
Kubernetes has expanded agility but also the attack surface. Alan argues that observability and security can no longer live in silos — metrics, logs, and traces already hold critical security signals, while ...
Alan Shimel | | anomaly detection, C2 traffic, cloud native security, convergence, cross-training, crypto-mining, devops, kubernetes, lateral movement, logs, metrics, observability, observability-driven security, OpenTelemetry, organizational silos, platform engineering, runtime security, security, SRE, tool sprawl, traces

Shimmy’s Early Look: Can’t-Miss Sessions at KubeCon + CloudNativeCon North America 2025
CNCF turns 10 as KubeCon + CloudNativeCon North America 2025 heads to Atlanta this November. With 300+ sessions on Kubernetes, AI, platform engineering, security, and observability, the event showcases the next decade ...
Alan Shimel | | AI workloads on Kubernetes, cloud native AI, cloud native events, CloudNativeCon 2025, CNCF community, DevOps conferences 2025, KubeCon 2025, KubeCon keynotes, Kubernetes conference Atlanta, Kubernetes security, multi-cluster orchestration, observability Kubernetes, platform engineering, supply chain security

Fitting Square Kubernetes Into the Round AI-Native Apps
Kubernetes tamed cloud-native workloads, but AI-native apps push its limits. Can it evolve for GPU-first, data-intensive AI — or is it time for new control planes? ...
Alan Shimel | | AI control plane, AI infrastructure, AI pipelines Kubernetes, AI-native applications, cloud-native vs AI-native, container orchestration AI, distributed training orchestration, GPU scheduling, inference at scale, internal developer platforms, Kubeflow, KubeRay, kubernetes, Kubernetes AI workloads, Kubernetes future, Kubernetes limitations, Kubernetes vs AI, platform engineering, Ray on Kubernetes, Volcano scheduler

From Observability to Actionability: Why Metrics Alone Aren’t Enough
Observability has plateaued. The next step is actionable observability—using AI, automation, and SLOs to turn telemetry into reliable outcomes ...
Alan Shimel | | actionable observability, AIOps, anomaly detection, auto-remediation, cloud native, continuous verification, devops, ELK stack, golden paths, internal developer platforms, metrics logs traces, observability, OpenTelemetry, platform engineering, SLO-driven operations, SRE, telemetry automation

GitOps Under Fire: Resilience Lessons from GitProtect’s Mid-Year 2025 Incident Report
GitOps may power cloud-native delivery, but rising outages and breaches across GitHub, GitLab, Jira, and Azure DevOps expose just how fragile today’s pipelines really are ...
Alan Shimel | | Azure DevOps pipelines, Bitbucket reliability, CI/CD disruption, cloud-native delivery, DevOps platform outages, GitHub incidents, GitLab breach, GitOps dependencies, GitOps resilience, GitOps security, GitProtect report 2025, internal developer platforms, Jira downtime, Kubernetes GitOps, platform engineering, resilience engineering, self-healing infrastructure, SRE practices, supply chain stability, zero-trust DevOps

Kubernetes Has Become Boring — That’s a Good Thing
Nearly 10 years on, Kubernetes has become the invisible backbone of cloud-native infrastructure—stable, trusted and still quietly evolving ...