DevNfra Engineering Blog

Every published tutorial on Kubernetes, cloud infrastructure, MLOps pipelines, CI/CD, and site reliability — sorted by recency.

All articles (19)

Building an Organizational Failure Memory for CI/CD — Automation — An idea I've been turning over for a while, framed honestly: I don't have a finished product here. What I have is a recurring frustration from year...
Kubernetes Cost Optimization: Lessons from Real Production Incidents — DevOps — Most Kubernetes cost-optimization advice reads like a checklist someone wrote without ever being paged. "Right-size your requests. Use HPA. Enable ...
Why Most "AI for DevOps" Tools Fail in Production — MLOps — I've evaluated, piloted, or quietly removed more "AI-powered DevOps" tools than I can count — at a large financial services environment and again a...
The Hidden Cost of Observability Tool Sprawl in Enterprise DevOps — DevOps — I've worked across enterprise environments — financial services, large-scale manufacturing — where the observability stack wasn't designed...
What I Learned Building an ML Model to Predict CI/CD Pipeline Failures — MLOps — A practitioner's notes on building an Isolation Forest and LSTM-based anomaly detector for CI/CD pipeline failures: which features actually had signal, why class imbalance and label noise dominate th…
From Zabbix to Datadog: A Real Migration Playbook — DevOps — A practitioner's playbook for migrating ~1,400 hosts from Zabbix to Datadog: why trigger thresholds don't map 1:1, the replication-lag alert gap that nearly caused a missed incident, real timeline an…
Scaling Beyond 800 Targets: Prometheus & Grafana's Breaking Points — Installations — We hit some hard limits with Prometheus and Grafana once our monitored targets crossed 800. From cardinality explosions to federation woes, here's what actually broke and how we fixed it.
Bare-Metal K8s with kubeadm: The Post-Install Reality on 7 Nodes — Installations — Setting up a 7-node bare-metal Kubernetes cluster with kubeadm brought unexpected challenges, from CNI choices to etcd I/O, and the critical post-install steps often neglected in guides.
MLOps at the Edge: 300 IoT Devices and Our Over-The-Air Ordeal — DevOps — Deploying machine learning models to 300 geographically dispersed IoT devices taught us hard lessons about model packaging, OTA updates, and monitoring drift without a steady stream of raw data.
Kubernetes for Public Services: SLOs, Accessibility, and the Compliance Drag — DevOps — Moving government websites to Kubernetes promised agility, but we quickly learned about the unexpected compliance overhead and the critical need for accessibility as a core SLO.
Running 40 Training Jobs a Day on Kubernetes: Patterns That Stuck — DevOps — We scaled our ML training platform to run 40 jobs daily on Kubernetes, facing GPU fragmentation and scheduler challenges. Here's what worked, what didn't, and the patterns that finally stuck.
Containers on Retail Edge: Bandwidth, Boot-Time, and Burnt Weekends — DevOps — We containerized everything for 3,000 retail edge gateways, battling intermittent connectivity, tight bandwidth, and the never-ending systemd vs. containerd debate. Our biggest lesson? Image size dis…
47 Tools, 9 Teams: Our DevOps Consolidation Story — DevOps — We found 47 different DevOps tools across 9 engineering teams, leading to duplicate spend and integration nightmares. Here's how we consolidated without chaos.
LLMs in DevOps: Where They Earned Their Keep (and Where They Hurt) — DevOps — This year, large language models became a core part of our DevOps toolkit for several tasks, dramatically improving efficiency in some areas. But we also hit some painful snags where their limitation…
From Monolith to 18 Microservices: The One We Merged Back — DevOps — Splitting a monolithic application into 18 distinct microservices was a hard-fought battle. We learned crucial lessons about contract testing, the saga pattern, and when 'micro' might be too small, e…
Why Our MLOps Stack Failed For Large Language Models — MLOps — Our battle-tested MLOps platform, refined over years of traditional ML, crumbled when we threw LLMs at it. The observability, evaluation, and CI/CD paradigms shifted dramatically, forcing a complete…
Leaving Docker for OCI: Gains, Losses, and a Week-Long CI Trap — DevOps — When our team shifted off Docker Desktop and its daemon-centric workflow to OCI-compliant tools, we hoped for better CI builds and licensing relief. We got what we wanted, but not without hitting a c…
What I Tell New Platform Engineers About Kubernetes on Day One — DevOps — Joining the platform team means Kubernetes is your bread and butter. I've seen where new hires stumble most often, and these are the crucial points I emphasize from day one to avoid common pitfalls.
Migrating off Ingress-NGINX: Our Production Gateway API Journey — DevOps — Facing Ingress-NGINX's deprecation, we had to migrate 18 production clusters to Gateway API. This is the story of choosing between Envoy Gateway, Istio, and Cilium, the annotation translation nightma…