The Payments Launch That Slipped Three Quarters—Until We Modernized Just Enough to Ship
How an anonymized fintech unblocked a revenue-critical launch by upgrading the right 20% of their stack—without a risky rewrite or lengthy freeze.
> We didn’t need a rewrite. We needed to make the next deploy safe. That’s what unblocked the launch.Back to all posts
Key takeaways
- Modernize the release path first: GitOps + progressive delivery removes fear and unlocks velocity.
- Target the bottlenecks with surgical changes: online schema, circuit breakers, and tracing—not a rewrite.
- Prove safety with SLOs and rollback automation; don’t rely on heroics during cutover.
- Build the new runway next to the old one: parallel EKS and logical replication keeps downtime measured in seconds, not hours.
- Measure business outcomes, not just tech wins: faster deploys, lower MTTR, better conversion.
Implementation checklist
- Stand up a parallel prod cluster with Terraform + ArgoCD; freeze nothing until traffic shifts.
- Define SLOs and alerts before changes land; wire Prometheus + Grafana + Alertmanager.
- Introduce canaries with Argo Rollouts and automatic rollback on SLI regression.
- Fix schema pain: `strong_migrations`, concurrent indexes, timeouts, and dry-run CI checks.
- Add circuit breakers and timeouts at the edge and in app (e.g., `semian` for Ruby).
- Instrument hot paths with OpenTelemetry; export traces to a real backend (Honeycomb/Jaeger).
- Replace DIY feature flags with a provider (LaunchDarkly) for kill switches and staged rollout.
- Rehearse cutover with a playbook and a hard rollback plan.
Questions we hear from teams
- Did you replace the monolith with microservices?
- No. A rewrite would have blown the deadline. We modernized the release path (GitOps + Rollouts), stabilized the database changes, and instrumented the critical path. Once the launch was safe and shipped, the team had air cover to plan extractions with real data.
- Why not add a service mesh like Istio?
- We evaluated it, but it wasn’t the bottleneck. NGINX Ingress plus Argo Rollouts and Prometheus-based gating delivered 90% of the value with 10% of the operational overhead. Mesh can come later if you need mTLS, traffic splitting by header, or detailed L7 policy.
- How did you manage the Postgres upgrade with near-zero downtime?
- Logical replication via `pglogical` from RDS 9.6 to 13, rehearsed twice. We kept the writer on the old DB, mirrored reads to the new, validated lag and checksums, then flipped writers with a 17-second read-only window. We also enforced `lock_timeout` and `statement_timeout` to avoid accidental long locks.
- What if our CI is the main bottleneck?
- Treat CI like prod. Cache Docker layers (`buildx`), shard tests (RSpec via Knapsack), and fail fast. Tie deploy gates to SLOs so you don’t ship regressions. Cutting CI from 90 to 20 minutes was a bigger morale win than any dashboard.
- How do you convince leadership to do this instead of a rewrite?
- Show the math: lead time from PR to prod, change failure rate, MTTR, and the dollars tied to launch. Promise a boring cutover with a rehearsed rollback. Executives don’t want heroics—they want the revenue date. Modernize the path to prod and you’ll hit it.
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