Cloud Migration: Building the Foundations for Digital Transformation

How can you modernise your infrastructure without putting your organisation at risk?

Cloud migration is often a central part of an organisation's wider digital transformation strategy. Moving away from legacy infrastructure can create opportunities to modernise applications, improve scalability and introduce new technologies.

However, cloud migration affects how applications perform at every layer of the stack. Moving workloads from on-premise infrastructure into the cloud introduces changes in latency, resource distribution and system behaviour.

Performance is not defined solely at the point of migration. It is shaped by how workloads are designed, deployed and managed once they are running in the new environment. Getting these considerations right can help organisations build a foundation for further digital transformation.

Workload architecture and cloud alignment

Applications built for on-premise environments are often designed around fixed infrastructure, predictable latency and tightly coupled components.

When these workloads are moved to the cloud, they may continue to function, but their performance characteristics can change. This is particularly relevant where applications rely on consistent network behaviour or specific hardware configurations.

Aligning workloads with cloud infrastructure often involves reconfiguring how components interact. This may include decoupling services, introducing load balancing or distributing workloads across multiple instances to improve resilience and responsiveness.

These changes can also support application modernisation, making it easier to introduce new capabilities and adapt services as requirements evolve.

Latency and network design

Latency is one of the most immediate performance considerations during cloud migration. Data that previously moved across local networks may now travel between regions, availability zones or external services.

This can affect response times, particularly for applications with real-time requirements or high volumes of data transfer.

Network design plays a critical role in managing latency. This includes selecting appropriate data centre locations, configuring routing paths and ensuring that dependencies between services are structured to minimise unnecessary data movement.

Understanding how traffic flows through the environment is essential to maintaining predictable performance.

Resource allocation and scaling behaviour

Cloud infrastructure enables dynamic resource allocation, allowing workloads to scale based on demand. However, this behaviour must be configured correctly to support consistent performance.

If resources are under-provisioned, applications may experience slow response times or instability under load. If they are over-provisioned, this can lead to unnecessary cost without improving performance.

Scaling policies should reflect how workloads behave in production. This includes identifying peak usage patterns, setting thresholds for scaling events and ensuring that additional resources are available when required.

Dependency mapping and system interactions

Applications rarely operate in isolation. They depend on databases, APIs, storage systems and third-party services, all of which contribute to overall performance.

During migration, these dependencies may be distributed across different environments, which can introduce variability in response times.

Mapping these interactions before migration helps identify potential bottlenecks. It also allows for adjustments to be made, such as relocating services closer together or redesigning communication patterns to reduce latency.

Data transfer and storage performance

The way data is stored and accessed changes in the cloud. Storage systems may offer different performance characteristics compared to on-premise hardware, particularly in terms of throughput and input/output operations.

Large-scale data transfers during migration can also impact performance, both during the migration window and afterwards if data access patterns are not optimised.

Choosing the appropriate storage configuration and understanding how data is accessed in production are key factors in maintaining performance.

Monitoring and performance visibility

Performance in cloud environments depends on continuous visibility. Metrics such as response time, resource utilisation and error rates provide insight into how workloads behave under different conditions.

Without effective monitoring, it becomes difficult to identify performance issues or understand their root cause.

Monitoring tools need to be configured to reflect the structure of the environment, capturing data across compute, network and storage layers. This allows teams to respond to performance changes and make informed decisions about optimisation.

Supporting long-term digital transformation

Performance considerations should be central to any cloud migration strategy, influencing decisions around architecture, deployment and ongoing management.

Moving workloads to the cloud can be an important step in modernising legacy infrastructure, but the value of migration also depends on what organisations can achieve with their new environment.

By considering workload architecture, resource allocation, dependencies and ongoing performance management early in the process, organisations can create a more adaptable cloud environment that supports their wider digital transformation objectives.