Replace "hope it works"
with git push origin main.

Short answer: no. If your scale is small (1–3 servers in one region, under 20k requests/min), Docker Compose, AWS ECS Fargate, GCP Cloud Run, Fly.io or Render bring far less operational burden. Kubernetes earns its complexity when you have 5+ services, multi-region, auto-scaling, advanced rollout strategies (canary/blue-green) and inter-service mesh needs. The decision is made together in the audit; we will not push you to "follow the trend". If we do go to K8s, we recommend managed (EKS/GKE/AKS) — you do not have to run your own cluster.

Usually no, not immediately. If Jenkins works, we run the new pipeline in parallel (GitHub Actions / GitLab CI / Drone). New services flow through the new pipeline, old ones stay on Jenkins. They co-exist for 2–3 months; once the team is comfortable, migration completes. The "throw it all away and rewrite" approach takes six months and leaves everything half-done. Our experience: a strangler-fig strategy always wins. If Jenkins is genuinely unmaintainable (ancient version, plugin explosion, no one understands it) — we will tell you straight.

Typical schedule: basic CI/CD (containers + test + build + deploy) 2–4 weeks. Adding Helm + Kubernetes +2–4 weeks. Full observability (Prometheus + Grafana + Loki + alerts) +2–3 weeks. Cloud management with Terraform/IaC +3–6 weeks (depends on existing resources). Total: small team 4 weeks, mid-size 8–10 weeks, enterprise 12–16 weeks. Important: phase by phase, business never pauses. You benefit the moment phase one ships; every later phase adds value. We do not wait for a single "everything is ready" moment.

Yes, and we treat that as part of the job. When setup completes: (1) full markdown documentation of the pipeline, (2) two-day hands-on workshop, (3) a 30-day shadow period — we watch in the background, the team leads, we answer questions. A developer's daily life barely changes: git push, pipeline runs. The complexity hides in infrastructure. For the ops side (alert handling, runbooks, rollback), we set up an on-call rotation. After 3 months your team can own the pipeline solo.

Two line items: (a) our setup + 3-month handover service — priced per project, low four figures for a small one, mid five figures for an enterprise build (EUR/USD, fixed price). (b) Ongoing infrastructure cost — you pay this from your own cloud account, we are not a middleman. Typical numbers: small SaaS 200–600 EUR/month cloud, mid 1500–4000 EUR, enterprise 8000+. Important: a correct design typically saves 30–50% of cloud spend (rightsizing, spot instances, auto-scaling). DevOps usually pays for itself within six months.

Yes. AWS + GCP + Azure + Hetzner + DigitalOcean — active production experience on all. Terraform/Pulumi provide vendor-agnostic abstraction; Kubernetes manifests run on every cluster. "Multi-cloud" is often not what you actually want (operational complexity 2.5×) — we usually recommend a single primary cloud + different region (multi-region) + a second provider for DR only. If true multi-cloud is required (e.g. EU data on AWS, US data on GCP) we set that up too. Region choice driven by data sovereignty (GDPR/KVKK) is a frequent conversation.

Yes. We have built pipelines compliant with ISO 27001, SOC2 Type II, PCI DSS, GDPR and KVKK. What we put in place: immutable builds (cannot be altered retroactively), separation of duties (the author cannot deploy), full audit trail (who approved what when), encrypted secrets (Vault/SOPS), encryption at rest + in transit, MFA-gated production access, vulnerability scan on every build. Auditor evidence packs come as ready templates. We have 6+ cases where independent auditors signed off on pipelines we built — references available.

When a problem is spotted after a release, two paths. (1) Kubernetes rollout undo: the previous revision still sits in Deployment history; one command or one ArgoCD UI button — the old image is live again in seconds, not minutes. Typical time: 12–25 seconds. (2) If a database migration is involved, more care: reverse migration first, then container rollback. That is why we always design migrations as backward-compatible (NULL-allow → backfill → NOT-NULL, two-step pattern). Automated rollback rule: an SLO breach or error-rate spike halts ArgoCD's progressive rollout and rolls back if needed. Human intervention is optional.