Cloud migration is easy-peasy on paper — until you have a live production Spring app to migrate, that you need to do without breaking any customer transactions, APIs, databases or deployment pipelines. That is where real engineering begins.
For businesses investing in Java web development services, migrating Spring applications to AWS, Azure, or Kubernetes is no longer a concern solely for lower infrastructure cost. That means you are using them to do what is easy with application scaling, monitoring, security and improvement.
The shift is already significant. A full 82% of organisations running containers are now deploying Kubernetes in production according to the 2025 CNCF Annual Cloud Native Survey, compared with just 66% running it in production as recently as 2023.
So, how are teams making all the possible moves?
Why are companies moving spring applications to the cloud?
Conventional Java applications rely on things like virtual machines, manually provisioned servers, immutable infrastructure and painful deployment processes that start to hurt badly as traffic ramps up.
Cloud platforms change that equation. By using the managed database, automatic scaling, container orchestration like Kubernetes, central monitoring for all microservices with a managed security service and automated CI/CD pipelines.
However, a successful migration does not mean moving the entire solution on Day 1. The intelligent way to do this is with application assessment first.
Teams review Java and Spring versions, database dependencies, APIs, authentication methods and configurations, file storage details, messaging queues content, scheduled jobs properties, external integrations location/events and application state. They then select every component as either rehost, replatform, containerization or redesign.
That distinction matters. Migrating from one platform to another will be nothing more than moving existing problems, at the very best, into a more expensive cloud environment.
AWS Migration: From Spring Cloud to Amazon EKS
This gives teams running Spring Cloud microservices a path to using AWS. You can contain applications and deploy them to Amazon Elastic Kubernetes Service (EKS), and you can move parts of your Spring Cloud infrastructure experience through cloud-managed services.
This can include configuration, service discovery, API management, logging, monitoring, as well as Storage and Security
AWS also promotes containerization for modernising Java applications with business logic and data models that are too valuable to lose.
An example of a real-world use case and its potential scale. Pipedrive migrated 500+ microservices and 43 TB of data to AWS. The organisation experienced a 25% reduction in response time and a 20% cost reduction on hosting per customer.
These figures are company-specific, not promises. However, they demonstrate why the cloud migration is justified by organisations.
Azure Spring Migration: What Teams Need to Know
Yes, that twist is an even more important way in the current Java migration story for Azure.
Microsoft and Broadcom are stopping Azure Spring Apps. On 17 March 2025 the stopping window began and the complete service is scheduled to be totally stopped by 31 March 2028. Therefore, Microsoft recommends that people should use Azure Container Apps and Azure Kubernetes Service (AKS) as a replacement platforms.
This means that companies who use Spring applications on Azure should not just wait around for the deadline to happen. Now is the time for them to think about how they’re building their stuff.
Azure Container Apps is great for teams who wish to run managed charts without managing a whole Kubernetes ecosystem. AKS is better understood as a fit when teams require orchestration for Kubernetes along with complex scaling, platform engineering, or deep infrastructure controls.
If organisations already plan Java web development services, this migration is also an opportunity to clean the technical debt rather than simply change hosting providers.
Kubernetes Migration: Powerful, but Not a Magic Wand
Modern Java workloads have started to land in Kubernetes at scale. Now, one question rises in mind:- does every Spring application really need Kubernetes?
The answer is no.
It provides scheduling, rolling deployments, service discovery, health checks, scaling and workload isolation with large ecosystem support in Kubernetes.. It also brings operational complexity related to networking, secrets, resource constraints, ingress, monitoring capabilities, cluster upgrades and maintenance tasks like security patches and deployment automation.
The newest CNCF research reports that 98% of surveyed organisations have adopted native techniques and 82% of container users run Kubernetes in production.
So Kubernetes is mature and Maturity does not mean simple.
What Happens During a Real Spring Cloud Migration?
Migrations usually succeed in stages.
First, engineers audit the application. They demonstrate dependencies and risks of migration.
Then prepare the application for cloud deployment. This could mean upgrading Java or Spring Boot, externalising your configuration, removing local file system dependencies, better health checks and rendering some of the services stateless.
Then comes containerization. Packaged into smaller image containers and orchestrated against a CI/CD pipeline (Continuous Integration and Deployment), Spring Boot applications are optimised to be production-ready.
Resource management is especially important. AWS 2026 guidance shows how JVM memory and CPU behave inside the containers (and this can cause production failures!), i.e. when your JVM expectations don’t align with what containers allow.
Finally, teams establish observability. Logs, metrics, traces and alerts, as well as application health checks, need to be informative enough to allow distributed applications to be debugged rapidly.
Because when production is down at 2 a.m., “it seems to works on my laptop” is not exactly a satisfying incident report.
How Java Web Development Services Support Cloud Modernization
Whether to review old Spring applications, modernise legacy APIs, containerise existing applications or redesign their architecture for improved security and build automated cloud deployment pipelines — through experienced Java web development services, organisations can jump, skip, or go for it.
This cloud-native foundation can also sustain AI initiatives. Organisations launching Agentic AI Services and Solutions require scalable APIs and event-driven workflows along with secure data access, monitoring and reliable infrastructure. Those capabilities can be offered through modernised Spring applications.
On the other hand, when AI models, data-processing services, automation or Python-based agent components need to co-operate with existing Java Systems. Then teams can hire Python developers.
All this leads to some polyglot architecture in practice: use Java for all legacy enterprise services and let Python be a great fit for specialised AI/data workloads.
Let us begin with the future of migrating Java to the cloud
The largest insight gained from successful migrations is also the simplest: think of cloud migration as modernisation, not relocation.
Java web development services can help organisations modernise their Java applications, but organisations should first get an understanding of their applications before choosing the right migration strategy with incremental modernisation. While each of AWS, Azure, and Kubernetes provides powerful choices to host workloads in the cloud, there is no single well-fitting destination, as it depends on workload requirements (integration composition), team capabilities (team composition), costs per unit of output (cost framework), along with the scalability level expected from service options available today (offering maturity).
Thus, as cloud-native development continues to gain traction with the introduction of AI, Agentic AI Services and Solutions will lead to infrastructure that stands even greater on scalability. With the help of hiring Python developers and seasoned Java engineers, teams can design flexible architectures without leaving behind their Spring investments.
The goal is not to justify putting Java in the cloud just because everyone else sane is doing so. The end game is to have an application hosting environment that can be deployed faster, made scalable more easily, observed with greater simplicity and ready for whatever comes next.
