A comprehensive guide on structuring multi-environment Terraform codebases, state locking, remote backends, drift detection pipelines, and automated module testing.
Key Engineering Principles
Folder hierarchy vs workspace strategies for isolation
Automating terraform plan PR checks with Atlantis & GitHub Actions
Enforcing policy as code using OPA (Open Policy Agent) & Checkov
Safe state migration and lock management strategies
#Terraform#OpenTofu#IaC#AWS#OPA
DevOpsContainers & SecurityGuide
Kubernetes Production Hardening & Zero-Trust Architecture
12 min read
Practical checklist for securing EKS/GKE clusters: NetworkPolicies, RBAC least privilege, Pod Security Admission (PSA), Kyverno policy enforcement, and mTLS via Istio.
Key Engineering Principles
Transitioning from PodSecurityPolicies to PSA standards
Automating container vulnerability scanning with Trivy in CI
Configuring Istio strict mTLS and ingress authorization policies
Runtime threat detection using Falco & eBPF
#Kubernetes#Security#Istio#Kyverno#Falco
DevOpsCI/CD & DeliveryBlueprint
ArgoCD & GitOps Multi-Cluster Deployment Pattern
10 min read
Declarative application management across dev, staging, and production EKS clusters using ArgoCD, Kustomize overlays, and automated canary analysis with Argo Rollouts.
Key Engineering Principles
App-of-Apps and ApplicationSet architectural patterns
Secrets management in GitOps with SealedSecrets & Vault
Disaster recovery and fast cluster recreation from Git
#ArgoCD#GitOps#Kubernetes#Helm#Kustomize
DevOpsObservability & SRECheatsheet
SRE Golden Signals & Alert Fatigue Reduction Cheatsheet
6 min read
How to construct high-signal Prometheus alert rules for Latency, Traffic, Errors, and Saturation while eliminating noisy alarms using burn-rate calculations.
Key Engineering Principles
Multi-window, multi-burn-rate alert math (SLO error budget alert setup)
Structuring PromQL queries for percentiles (p95, p99) accurately
Integrating PagerDuty escalation trees with Grafana dashboards
Cold-start optimization using fast local NVMe cache and S3 Mountpoint
Benchmarking Time-To-First-Token (TTFT) and Inter-Token Latency (ITL)
#vLLM#MLOps#GPU#Kubernetes#KEDA#PyTorch
MLOpsExperimentation & LifecycleGuide
Enterprise MLflow Model Registry & Lineage Tracking Pattern
9 min read
Setting up a centralized MLflow tracking server connected to S3 artifact storage and PostgreSQL, with automated model promotion gates in CI/CD pipelines.
Key Engineering Principles
Automated experiment logging and hyperparameter tracking
Integrating MLflow model registry stages (Staging -> Production)
Data versioning linkage using DVC and git commits
Security, authentication, and role-based access for data science teams
#MLflow#MLOps#DVC#Python#PostgreSQL
MLOpsData PipelinesBlueprint
Real-Time Feature Store Implementation with Feast & Redis
11 min read
Building a low-latency feature serving architecture for online machine learning models, connecting batch pipelines (Spark/Snowflake) with online stores (Redis/DynamoDB).
Key Engineering Principles
Defining feature views and entity definitions in Python
Preventing point-in-time data leakage during training set generation
Low-latency online feature retrieval (< 5ms) during inference
Automating feature pipeline sync schedules
#Feast#Redis#MLOps#FeatureStore#Spark
MLOpsObservability & QualityGuide
Continuous Model Monitoring: Data Drift & Concept Drift Detection
8 min read
Establishing continuous model performance monitoring to detect feature distribution shifts, prediction drift, and accuracy degradation in live production environments.
Key Engineering Principles
Statistical tests for drift (KS-Test, PSI, Wasserstein Distance)
Setting up Evidently AI & Deepchecks pipelines on Kubernetes
Automating model re-training triggers when drift exceeds thresholds
Correlating model input drift with SRE golden signals in Grafana