DevOps Tech Stack 2026
Good DevOps is invisible — when it works, nobody notices; when it doesn't, everything stops.
DevOps tooling choices at WeBridge are driven by one principle: automate the things that cause human error. Infrastructure as code, automated testing gates, and one-command rollbacks are non-negotiable. We've seen too many projects fail not because of bad code but because of fragile deployment processes and unmonitored production environments. Our DevOps stack centers on GitHub Actions for CI/CD, Terraform for infrastructure, and Kubernetes for container orchestration, with a strong emphasis on observability from day one.
The Stack
Frontend
Backstage by Spotify is worth implementing at 20+ engineers — it provides a unified developer portal for service catalog, documentation, and scaffolding. Grafana is the standard for infrastructure and application metrics dashboards.
Backend
GitHub Actions for CI (testing, building, security scanning) and ArgoCD for CD via GitOps — infrastructure state lives in git, and ArgoCD reconciles Kubernetes clusters to match. This pattern gives you full audit trails and easy rollbacks. Jenkins is legacy — migrate off it if you're still using it.
Database
Terraform with remote state in S3 and DynamoDB for state locking is the production standard. Pulumi is compelling for teams that prefer TypeScript over HCL — you get real programming constructs instead of declarative config. OpenTofu (the open-source Terraform fork) is worth monitoring as HashiCorp's licensing changes mature.
Infrastructure
Kubernetes with Helm charts for application deployment, Terraform for cluster provisioning. Prometheus + Grafana for metrics, Loki for logs, Tempo for traces — the LGTM stack provides full observability. Datadog if budget allows — it's expensive but the unified platform saves significant ops time.
Estimated Development Cost
Pros & Cons
✅ Advantages
- •Infrastructure as code enables reproducible environments and disaster recovery
- •GitOps (ArgoCD) provides audit trail for every deployment and easy rollback
- •Kubernetes autoscaling handles traffic spikes without manual intervention
- •Prometheus/Grafana alerts catch issues before users notice
- •Preview environments from GitHub Actions improve QA velocity significantly
- •Automated security scanning (Snyk, Trivy) catches vulnerabilities in CI pipeline
⚠️ Tradeoffs
- •Kubernetes has steep learning curve — requires dedicated DevOps expertise
- •Terraform state management requires discipline — conflicts cause infrastructure drift
- •Observability stack is expensive at scale (Datadog pricing is notoriously aggressive)
- •GitOps adds deployment complexity for simple single-repo applications
- •Alert fatigue is real — monitoring requires ongoing tuning to stay actionable
Frequently Asked Questions
Do I need Kubernetes for a small startup?
No. Start with Railway, Fly.io, or Heroku for sub-$10K MRR. Move to AWS ECS when you need more control. Graduate to Kubernetes when you have multiple services with different scaling requirements and a team member dedicated to infrastructure. Kubernetes before you need it is a tax on developer velocity.
Terraform vs Pulumi — which IaC tool should I use?
Terraform if your team is comfortable with HCL or you're hiring DevOps engineers who know it. Pulumi if your team is TypeScript/Python-first and wants to use real programming constructs for infrastructure. Both are production-ready — pick based on team preference. Avoid hand-clicking infrastructure in the AWS console for anything beyond a quick test.
What's the minimum viable observability setup?
Error tracking (Sentry), uptime monitoring (Betteruptime or UptimeRobot), and application metrics (Prometheus + Grafana or Datadog). Add distributed tracing when you have more than 3 services. Set up alerts for error rate, latency p99, and disk/memory pressure before launch — don't wait until production is on fire.
How do I set up a good CI/CD pipeline with GitHub Actions?
Lint and typecheck on every PR, run tests in parallel with matrix builds, build Docker images and push to ECR on merge to main, trigger ArgoCD sync for deployment. Add Snyk or Trivy for container scanning. Keep CI under 5 minutes — slow CI pipelines kill developer flow. Cache aggressively (npm, Docker layers, Gradle).
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