One monolith → independent services
deploys / wk
1 → 40
blast radius
1 service
When one deploy makes the whole company hold its breath, the monolith is the bottleneck. We decompose it into microservices — bounded contexts, clean APIs, containers, distributed tracing — so teams deploy independently and a single failure stays contained.
More frequent deploys
Lower p95 latency
Blast radius (was full outage)
Big-bang rewrites
Why decompose the monolith
Microservices aren't a fashion statement — they exist to let teams deploy on their own cadence and to keep one failure from taking everything down.
We split the monolith along real business boundaries — orders, billing, search — not arbitrary lines, so each service owns one job and its own data.
Teams ship their service on their own cadence behind an API gateway. One deploy stops making the whole company hold its breath.
When a service goes down, the blast radius is that service — not a full-system outage. Resilience patterns keep the rest serving traffic.
Distributed tracing, centralized logging, and per-service metrics ship with the migration, so a decomposed system is one you can actually operate.
What you walk away with
Decomposition is only a win if the result is observable and consistent. You get the services plus everything needed to run them in production.
From monolith to mesh
We map the monolith to business capabilities and design service boundaries and API contracts before extracting anything.
An API gateway goes in front, and the highest-value capability is extracted as the first independent service.
Capabilities move across one at a time, with data kept in sync and traffic routed incrementally to the new services.
Tracing, logging, and integration tests confirm each service before routing fully cuts over and the monolith shrinks away.
Migration, in production
A marketplace's single deploy pipeline meant one bad release froze every team and one bad query took the whole site down. We migrated it to services with the Strangler Fig pattern.
Plata Marketplace
Online marketplace · USA
Deploys/week
p95 latency (was 820 ms)
Failure blast radius
Big-bang rewrite needed
“A single bad deploy used to freeze every squad and risk the whole site. pyronix peeled the monolith apart one capability at a time — now teams ship dozens of times a week and an incident is one service, not a homepage outage.”
Straight answers
Microservices migration is the process of breaking a monolithic application into smaller, independently deployable services organized around business capabilities. Each service owns its data and exposes a clean API, so teams can build, deploy, and scale their part of the system without coordinating a single big release.
The Strangler Fig pattern migrates a monolith incrementally: new microservices are built alongside the legacy system, and an API gateway routes specific requests to the new services while the rest still hit the monolith. Over time more functionality moves across until the monolith is fully replaced — with no risky big-bang rewrite or extended outage.
We use patterns like the transactional outbox and sagas to synchronize data asynchronously between services, so a workflow that spans several services stays correct without distributed locks. During migration we keep the monolith and new services in sync until each capability has fully moved over.
No — and you shouldn't. We decompose by business capability, prioritizing the parts that change most or scale worst, and migrate them one at a time behind the API gateway. You get value from the first extracted service while the rest of the system keeps running unchanged.
Yes. Services are packaged as Docker containers and deployed to orchestrated environments such as EKS, AKS, or ECS, with CI/CD pipelines, distributed tracing, and centralized logging so the resulting system is observable and operable, not just decomposed.
Tell us where the monolith hurts most — the slow deploys, the shared outages. We'll design the service boundaries and a strangler-fig path that ships value from the first extraction.
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