Migration Services
Codimite provides Python to Go migration services for applications, APIs, and microservices. Improve performance, scale efficiently, simplify deployment, and optimize cloud resource usage through a controlled migration approach.
Scale with Go
Use compiled Go services to support faster and more predictable backend performance.
Handle high volumes of simultaneous requests using goroutines and Go's built-in concurrency model.
Potentially reduce memory, compute, and infrastructure requirements for suitable workloads.
Deploy compiled Go applications with fewer runtime dependencies.
Develop scalable APIs and microservices for containers, Kubernetes, serverless platforms, and distributed environments.
Use static typing and compile-time checks to identify issues earlier and improve maintainability.
Migration Process
Review the codebase, architecture, dependencies, costs, and performance bottlenecks.
Identify the Python services that offer the strongest migration value.
Rewrite and benchmark a selected component before expanding the migration.
Re-engineer services while preserving functionality and integrations.
Run parallel testing and complete a staged or controlled cutover.
Why Codimite
Codimite combines application modernization, cloud engineering, and Go development expertise to deliver secure, scalable, and risk-managed migration projects.
Talk to a Migration ExpertMigration-Led Technical Assessment. We evaluate your Python architecture, dependencies, performance, and infrastructure before recommending what should move to Go.
Experienced Go Engineering. Our engineers design and build scalable Go applications, APIs, microservices, and cloud-native services.
Business Logic Preservation. We carefully document and rebuild existing functionality, integrations, and workflows to maintain application continuity.
Risk-Managed Delivery. Phased migration, pilot testing, rollback planning, and controlled deployment help reduce operational disruption.
Cloud and DevOps Expertise. We support containerization, Kubernetes, CI/CD pipelines, observability, and deployment across modern cloud environments.
End-to-End Support. Codimite manages assessment, architecture, rewriting, testing, deployment, optimization, and knowledge transfer.
Comparison
| Comparison Area | Python | Go Advantage |
|---|---|---|
| Performance | Runtime performance depends on the framework and workload | ✓ Compiled performance for demanding backend services |
| Concurrency | Relies on threading, multiprocessing, or asynchronous frameworks | ✓ Built-in goroutines and channels for concurrent processing |
| Multi-core processing | Standard CPython threads can be limited for CPU-bound workloads | ✓ Efficient use of multiple CPU cores |
| Resource usage | Some Python applications require more memory and compute resources | ✓ Potentially lower memory and infrastructure usage |
| Deployment | Requires a Python runtime, packages, and dependency management | ✓ Deploys as a compiled executable with fewer runtime dependencies |
| Startup time | Can vary based on framework and package loading | ✓ Fast startup for containers and autoscaling environments |
| Type safety | Dynamic typing can allow some issues to appear at runtime | ✓ Static typing and compile-time checks improve predictability |
| Microservices | Suitable with supporting frameworks and runtime management | ✓ Strong fit for APIs, microservices, and distributed systems |
| Cloud scalability | Scaling may require additional processes or containers | ✓ Efficient scaling for high-volume cloud workloads |
FAQs
No. Codimite can migrate selected APIs, microservices, background workers, or performance-critical components while keeping suitable workloads in Python.
Yes. Go services can run alongside Python applications through APIs, message queues, and shared data platforms, supporting a gradual migration approach.
It may reduce infrastructure usage for suitable workloads. Actual savings depend on application architecture, traffic, memory consumption, deployment design, and current cloud usage.
Yes. Codimite can assess and migrate suitable Django services, Flask APIs, FastAPI applications, background processes, and third-party integrations.
Minimal or zero-downtime migration may be possible using parallel environments, staged releases, traffic switching, and rollback planning. The final approach depends on the existing architecture.
The timeline depends on codebase size, architecture, dependencies, integrations, test coverage, and migration scope. A technical assessment is required to provide a reliable estimate.
Identify which services should be migrated, optimized, or retained with a focused technical assessment.
Talk to a Migration Expert
