DevOps

DevOps — Page 7 of 8

Browsing page 7 of 8 — 95 articles on devops.

LLM Observability in Production: Token Tracking, Latency Budgets, and Prompt Drift Detection
DevOps ·

LLM Observability in Production: Token Tracking, Latency Budgets, and Prompt Drift Detection

How to monitor LLM-powered features beyond basic logging. Covers token cost attribution, latency budget design, prompt drift detection, quality regression alerting, structured tracing for agent chains, and a comparison of Langfuse, Helicone, and custom OpenTelemetry.

Cost Optimization for Cloud Infrastructure: Spotting Waste, Right-Sizing Resources, and Serverless Economics
DevOps ·

Cost Optimization for Cloud Infrastructure: Spotting Waste, Right-Sizing Resources, and Serverless Economics

A practical guide to reducing cloud infrastructure costs without sacrificing reliability. Covers idle resource identification, right-sizing methodology, serverless cost modeling, reserved instance math, and a monthly review process for small teams.

DNS Architecture for Production Systems: Record Types, Failover, CDN Routing, and Debugging Resolution
DevOps ·

DNS Architecture for Production Systems: Record Types, Failover, CDN Routing, and Debugging Resolution

Most engineers treat DNS as a lookup table and move on. This guide covers the resolution chain, TTL implications, every record type worth knowing, DNS-based failover, GeoDNS routing, CDN integration, DNSSEC, and a practical debugging toolkit with dig commands.

SLIs, SLOs, and SLAs in Practice: Designing Reliability Targets for Startup Engineering Teams
DevOps ·

SLIs, SLOs, and SLAs in Practice: Designing Reliability Targets for Startup Engineering Teams

SLIs measure the thing, SLOs set the target, SLAs are the business contract. This covers how to choose the right SLIs for different service types, set achievable SLO targets, implement error budget policies, instrument SLIs in TypeScript, and build burn-rate alerts that actually fire at the right time.

Blue-Green Deployments in Practice: Zero-Risk Releases for Startup Engineering Teams
DevOps ·

Blue-Green Deployments in Practice: Zero-Risk Releases for Startup Engineering Teams

Blue-green deployments give you a clean rollback story and near-zero downtime during releases. This covers the architecture, traffic switching strategies, database migration challenges, session handling, smoke testing, and when the pattern is overkill.

Load Testing for Startups: Finding Breaking Points Before Your Users Do
DevOps ·

Load Testing for Startups: Finding Breaking Points Before Your Users Do

Most startups skip load testing until the first traffic spike breaks production. This guide covers the three test types, tool selection, realistic k6 scripts in TypeScript, and integrating load tests as deploy gates.

Production Database Backup and Recovery: Automated Snapshots, Point-in-Time Restore, and Disaster Recovery Runbooks
DevOps ·

Production Database Backup and Recovery: Automated Snapshots, Point-in-Time Restore, and Disaster Recovery Runbooks

Most startups discover their backup strategy is broken during the incident where they need it. This covers backup types, RPO and RTO target selection, automated backup architecture for PostgreSQL with WAL-G and managed services, point-in-time recovery mechanics, cross-region disaster recovery, and how to write and test a runbook that actually works under pressure.

Incident Management for Small Teams: Runbooks, Postmortems, and Escalation That Actually Works
DevOps ·

Incident Management for Small Teams: Runbooks, Postmortems, and Escalation That Actually Works

Most incident management guides assume a dedicated SRE team. This one is for 2-10 person engineering teams. Severity classification, runbooks people actually use, postmortems that produce improvements, and tooling that doesn't break the budget.

Kubernetes vs Serverless in 2026: A Decision Framework for Startup Infrastructure
DevOps ·

Kubernetes vs Serverless in 2026: A Decision Framework for Startup Infrastructure

A concrete comparison of Kubernetes and serverless for startup infrastructure in 2026. Covers cost at 1K, 10K, and 100K MAU, operational overhead, cold starts, local development, observability, and a decision matrix by team size and workload type.

Structured Logging in TypeScript: From Console.log to Production Observability
DevOps ·

Structured Logging in TypeScript: From Console.log to Production Observability

console.log fails at scale in ways you will not notice until you are debugging a production incident. This covers structured logging fundamentals, library tradeoffs, log pipeline architecture, OpenTelemetry integration, cost-effective storage options, and a complete Hono middleware implementation.

Chaos Engineering for Startups: Breaking Things on Purpose Before Production Does It for You
DevOps ·

Chaos Engineering for Startups: Breaking Things on Purpose Before Production Does It for You

Chaos engineering is not a Netflix luxury. Startups benefit disproportionately because their blast radius is smaller and their redundancy is thinner. This covers the principles, how to run your first experiments, practical tooling, hypothesis design, blast radius control, and how to build a chaos practice that does not terrify your team.

Infrastructure as Code for Startups: Terraform, Pulumi, and SST Compared
DevOps ·

Infrastructure as Code for Startups: Terraform, Pulumi, and SST Compared

A practical comparison of Terraform, Pulumi, and SST for startups. Covers state management, team workflow, CI/CD integration, and a decision framework for picking the right IaC tool based on your stack, team size, and cloud provider.