Redesign application architecture for performance, scalability, resilience, and security — without starting from scratch. Cloud-native, event-driven, CQRS, and DDD patterns with quantified before/after benchmarks.
These five patterns are consistent signals that the architecture — not the code, not the team — is the root cause of performance, reliability, and security problems.
The architecture doesn't scale horizontally. Adding more servers helps for a while, then stops. The bottleneck is architectural — not compute. Users experience slow responses exactly when the business needs the system most.
One service going down takes everything with it. There's no graceful degradation — just a complete outage. Incident post-mortems always identify the same structural issues, never fixed because a 'fix' would require rearchitecting.
You can't change one thing without changing five others. High coupling across modules means every feature request triggers a dependency analysis meeting. Development velocity slows as the system grows.
Authentication, authorisation, encryption, and audit logging were added as afterthoughts. Controls are patchy and inconsistent — some endpoints are protected, others aren't. Every compliance audit surfaces new gaps.
The architecture is compute-inefficient — it doesn't leverage managed services, auto-scaling, or right-sized resources. You're paying for peak capacity 24/7 because the architecture can't scale down when demand drops.
We match the pattern to the problem — not the other way around. Each of these patterns solves a specific class of architectural challenge.
12-factor apps, container-first design, auto-scaling, and self-healing. Built for the cloud from the ground up — not lifted from on-premise.
Asynchronous communication via events, decoupled producers and consumers, event sourcing. Systems react to business events in real time.
Separate read and write models, optimised independently. Write side handles commands; read side serves queries from optimised projections.
Bounded contexts, aggregates, and ubiquitous language aligning code with business domains. The model is the competitive advantage.
Core business logic isolated from infrastructure. Swap databases, APIs, and UIs without touching domain logic. Built for longevity.
Event-driven compute, zero idle cost, managed scaling. Functions handle specific responsibilities — no servers to manage, no idle capacity to pay for.
Every architectural decision we make is documented as an Architecture Decision Record (ADR) — a lightweight structured document that captures what was decided and why. ADRs prevent the most common post-project problem: a year later, nobody remembers why the architecture looks the way it does.
# ADR-007: Use Event Sourcing for Order Domain
## Status
Accepted
## Context
Order processing requires a complete audit trail for regulatory compliance and the ability to replay events to rebuild state after incidents. The current state-based model loses historical context and cannot answer temporal queries ("what was the order status at 14:32?").
## Decision
Implement event sourcing with EventStoreDB for the order bounded context. All state changes are stored as immutable events. Read models (projections) are rebuilt from the event stream.
## Consequences
Added complexity in building and maintaining projections. Benefit: full auditability, temporal queries, and the ability to add new read models without schema migrations.
Every project gets a living ADR log committed alongside the code. You'll always understand why your architecture looks the way it does — even years from now when the original team has moved on.
Four specialised services covering the most common architecture re-engineering needs.
Redesign applications for cloud-native patterns — containerisation, auto-scaling, managed services, and 12-factor principles.
Learn moreDesign and implement event-driven systems with Kafka, EventBridge, or RabbitMQ — decoupled, reactive, and scalable.
Learn moreArchitecture-level performance engineering — bottleneck identification, horizontal scaling design, caching strategy, and load testing.
Learn moreThreat modelling, secure-by-design re-architecture, zero-trust network design, and compliance-aware security controls.
Learn moreSix phases from assessment through production-validated re-engineered architecture — with measurable outcomes at each milestone.
Review current architecture, identify bottlenecks, SPOFs, security gaps, and scalability limits with quantified findings.
Define target state, create C4 diagrams, document Architecture Decision Records (ADRs) for every major design choice.
Build a vertical slice through the new architecture to validate performance, resilience, and operational readiness before full implementation.
Implement the target architecture module-by-module, running new and old in parallel with progressive traffic migration.
Load testing, capacity planning, and latency profiling with documented before/after comparison at each milestone.
Threat modelling (STRIDE), penetration testing, secure-by-design review, and compliance validation before production.
We establish baselines before we start and measure outcomes after every milestone. These are representative results from actual re-engineering projects.
API Response Time (p99)
Before
800ms
After
95ms
Throughput
Before
200 req/s
After
12,000 req/s
Availability
Before
99.5%
After
99.99%
Deployment Frequency
Before
Monthly
After
Daily
Critical Vulnerabilities
Before
47
After
0
Representative results from actual re-engineering engagements. Individual results vary based on application complexity and starting architecture.
Pattern-agnostic tooling — the right tools for the chosen architecture, not the tools we happen to know.
Backend
Event Systems
Cloud-Native
Performance
Security
Architecture Tools
Real architecture re-engineering outcomes — measured in performance, availability, and business impact.
Re-architected a synchronous order processing pipeline to event-driven with Kafka, achieving a 50× throughput improvement and enabling real-time inventory updates across 200 stores — with zero data loss during the migration.
Read Case StudyRedesigned a multi-tenant architecture from shared-everything to domain-isolated services with CQRS read models, reducing dashboard load times from 12 seconds to 400ms and cutting infrastructure cost by 35%.
Read Case StudyImplemented hexagonal architecture for a clinical decision support engine, allowing the same core domain logic to serve web, mobile, and HL7 FHIR API interfaces without duplication — enabling FHIR certification in 6 weeks.
Read Case StudyEvery decision is captured in an Architecture Decision Record. You'll always know why your system looks the way it does — even years from now.
Cloud-native, event-driven, CQRS, DDD, hexagonal, and serverless — we match the pattern to the problem, not the other way around.
Performance improvements are measured, not estimated. We establish baselines before re-engineering and publish before/after comparisons at every milestone.
Threat modelling and secure-by-design review at architecture phase — not a pentest bolted on at the end of the project.
We re-engineer module by module with the old system running in parallel. There's no 'freeze everything for 6 months' moment.
Common questions about architecture re-engineering — answered directly.
