Legacy applications hosted on physical or virtual servers often fail to scale under user load, lack redundancy, and generate unpredictable maintenance costs. Performance degradation, patch dependencies, and high downtime risk make innovation almost impossible.

Codewave simplifies this transition by strategically migrating your applications to the cloud without disruption. We assess your current setup to determine the right migration path: rehost, replatform, or rebuild. Workloads are containerized with Docker and deployed on AWS ECS, Azure Kubernetes Service (AKS), or Google Cloud Run for scalability. Automated CI/CD pipelines in GitLab ensure testing, integration, and deployment happen smoothly while your systems stay live.

Once migrated, your applications perform consistently across environments, auto-scale during traffic surges, and recover instantly from failures. Teams spend less time managing servers and more time building features that move your business forward.

Example: An on-premises insurance CRM hosted on Windows servers may struggle during open enrollment periods and crash when more than 5,000 concurrent users are active. After migrating to AWS with autoscaling and load balancing, it can sustain over 25,000 concurrent sessions with 99.98% uptime, without increasing infrastructure costs.

Monolithic applications make even simple updates slow and risky. One small change can trigger regressions, delay releases, and lock your teams into long testing cycles. Over time, this rigidity limits innovation and inflates maintenance costs.

We help you re-architect legacy systems into modular, cloud-ready architectures that scale and evolve faster. Using frameworks such as Spring Boot, Node.js, or .NET Core, we break down tightly coupled components into independent microservices. Each service runs in its own container, managed by Kubernetes. For high-volume workloads, asynchronous messaging with tools like Kafka keeps operations smooth under load.

As a result, updates roll out independently, releases become predictable, and downtime drops dramatically. Your teams gain agility to experiment, ship faster, and respond to market needs without disrupting core systems.

Example: Say a retail firm needs two weeks to deploy a pricing change due to monolithic dependencies. After re-architecting the system into microservices, the pricing logic will be isolated and deployable independently. This will reduce the update time to under 3 hours while improving fault isolation.

Aging systems drain productivity. Rigid workflows, outdated frameworks, and tangled logic make even minor enhancements time-consuming. Manual data handling, redundant API calls, and slow queries further impact user experience and business responsiveness.

We reengineer applications to be faster, leaner, and easier to scale. The process starts with an architecture audit to pinpoint bottlenecks and redundant logic. Backends are refactored with tools such as Python’s FastAPI or Java’s Spring Boot for modular, asynchronous processing. 

Frontends are modernized with React or Angular for consistency and responsiveness. Redis caching accelerates frequent queries, and optimized PostgreSQL indexing improves data access speeds. 

As a result, reengineered systems become lighter, more responsive, and easier to maintain, freeing your development team from the constant need for firefighting.

Example: Imagine a logistics tracking system that refreshes shipment statuses every 15 seconds through a batch job, which delays visibility and overloads the database. After reengineering, each event will trigger an immediate update. This reduces the database load by over half.

Legacy applications built on outdated languages like COBOL, VB6, or Delphi create security risks, integration issues, and talent gaps that slow growth. Over time, maintaining these systems becomes costly and limits your ability to innovate.

We modernize such applications by recoding them into secure, scalable frameworks such as .NET Core, Django, or Go, while preserving your core business logic. Data layers are migrated to MongoDB for greater flexibility, and automated regression testing ensures functionality remains intact after the migration.

Once recoded, applications become more secure, maintainable, and future-ready, with the flexibility to integrate with analytics, AI, or mobile platforms.

Example: A healthcare portal built on VB6 may not be able to integrate with digital records. By rebuilding it in .NET Core and deploying on Azure App Service, it will be able to process patient data faster and support lab integrations.