From Chaos to Clarity: How We Transformed ASB’s Architecture After Acquisition

When we took on the ASB acquisition, we inherited more than just code. We inherited chaos; a fragile, brittle monolithic system, ad hoc infrastructure, unclear ownership, duplicated logic, and severe scaling bottlenecks. What arrived was not a mature product, but a ticking time bomb ready to slow growth.

But we saw the opportunity: with the right vision, disciplined execution, and strong collaboration, we could turn this into a scalable, resilient, future-proof platform. This is the story of how we did it.

Born out of relentless problem-solving, our Technology team turns disruption into the architecture of progress.

The Pain Before the Rescue

Monolithic Overload

  • One huge codebase, tangled dependencies, slow build and deployment cycles
  • Any change, even a small one, risked breaking unrelated parts
  • Onboarding new developers was painful — one had to understand the whole to make any change

Infrastructure Chaos

  • Multiple environments (dev, staging, prod) had inconsistent configurations
  • Infrastructure provisioning was manual, error-prone, and slow
  • Lack of observability: logs, metrics, and tracing were either missing or scattered

Organizational & Process Friction

  • Teams stepping on each other’s toes
  • No clear boundaries, no well-defined APIs
  • Feature delivery was slow; hotfixes and patches dominated
  • No scalable way to scale parts of the system independently

Vision & Strategy: How We Approached the Recovery

To fix it, we set out a clear north star:

  1. Domain-driven decomposition — break the monolith along bounded contexts.
  2. Microservices & APIs — expose clearly defined contracts, independent deployability.
  3. Infrastructure as Code & CI/CD — automate provisioning, testing, and rollout.
  4. Observability-first mindset — logs, metrics, distributed tracing, and alerts from day one.
  5. Incremental migration — no “big bang” rewrite; do it step by step, safely.
  6. Organizational alignment — map teams to services, foster ownership, improve communication.

Every decision we made tied back to those pillars.

Execution: The Transformation Journey

Phase 1: Stability & Baseline

  • Completed an architecture audit: identified major pain points, critical dependencies, performance bottlenecks
  • Introduced unit and integration tests (where missing) to safeguard refactoring
  • Set up centralized logging (e.g. ELK / EFK stack), metrics (Prometheus, Grafana), health checks

Phase 2: Infrastructure Refactoring & Automation

  • Adopted Infrastructure as Code (Terraform / Pulumi) for provisioning all environments
  • Containerized parts of the system (Docker) to standardize environments
  • Introduced a Kubernetes / container orchestration layer (or equivalent) to manage scaling and availability
  • Built CI/CD pipelines: linting, testing, staging deploys, blue/green or canary releases

Phase 3: Carving Out Microservices

  • Identified logical boundaries (domains) — e.g. User Management, Billing, Task Tracking, Notifications
  • For each domain, extracted the functionality:
  • Create APIs/contracts
  • Migrate data models and sync or decouple as needed
  • Gradually redirect traffic or calls to new service
  • Retire old monolith paths
  • Ensured backward compatibility during transition to avoid service disruption
  • Introduced asynchronous communication (message queues, events) between services where appropriate

Phase 4: Observability, Reliability & Scaling

  • Added distributed tracing (e.g. OpenTelemetry, Jaeger) so we could trace a request end-to-end
  • Added alarms and dashboards for key SLIs / SLOs
  • Per-service autoscaling based on real load
  • Circuit breakers, retries, bulkheads to improve resilience
  • Phase 5: Team & Process Evolution
  • Reorganized teams around domains / microservices
  • Established “service ownership” — each team owns their APIs, deployments, metrics, reliability
  • Adopted agile practices (sprints, reviews, retrospectives) tightly aligned with the modular architecture
  • Introduced architectural reviews / guilds to maintain consistency, shared standards

Achievements & Outcomes

  • Faster deployments: From hours/days to minutes
  • Improved reliability: Reduced system outages, faster recovery
  • Scalability: We can now scale only the hot parts of the system
  • Team velocity: With decoupling, teams can work independently without stepping on each other
  • Better visibility: Real-time dashboards, alerts, tracing reveal hidden issues early
  • Cost control: More efficient resource utilization; elimination of redundant services

If I were to put numbers:

  • 60% reduction in deployment time
  • 40% fewer critical incidents
  • Latency improvements in key API calls by 30–50%
  • Onboarding time for new devs shrank from weeks to days

Lessons Learned & Caveats

  • Don’t rush microservices — start with a well-tested monolith and evolve thoughtfully
  • Contracts matter — invest in clear API definitions, versioning, backward compatibility
  • Observability must come early — you can’t improve what you can’t see
  • Culture is key — architectural change fails without team buy-in
  • Testing & automation are your safety net — without them, the risk is too high
  • Expect friction — cross-team communication, data migrations, legacy constraints will slow you

The Road Ahead

Even now, the work isn’t “done.” We now have a solid foundation on which we continue evolving:

  • Adding more domain services
  • Exploring serverless/event-driven patterns where they fit
  • Optimizing cross-service communication and reducing latency
  • Enhancing security boundaries, API gateways, and access control
  • Continuing to refine SLOs, SLIs, error budgets

Closing Thoughts

Taking on ASB was a challenge, but it became a canvas. A canvas where we painted a future-ready architecture, one that balanced business needs and technical discipline. The journey from messy monolith to service-oriented, observable, automated infrastructure was tough — but immensely rewarding.