internal developer platforms

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