Cloud migration: types, strategies and role of AI - incl. how-to

Jan Schäfer

In order to work more flexibly and innovatively, companies are moving an increasing number of their applications, resources and processes to the cloud. It is becoming increasingly clear that a successful combination of on-premise and multicloud provides the efficiency and security that companies need to compete.

But how does the move to the cloud actually work? In our guide, we show you in detail what you need to look out for when migrating to the cloud, how you can benefit from it and why artificial intelligence plays a crucial role in linking and using data.

The most Important in a Nutshell

Cloud Migration - Definition

Cloud migration describes the process of moving company data, applications and IT resources from local data centers or other physical infrastructures to cloud platforms. Depending on the type of migration, the cloud migration process comprises various phases. As a rule, these include the evaluation of existing systems, the selection of suitable cloud services, data migration, the adaptation of applications to the cloud environment and, finally, ongoing operation in the cloud.

Companies are migrating to cloud platforms to modernize their IT infrastructure, increase agility and improve access to advanced technologies.

In addition, they often increase the performance of their applications and their scalability as a result of the move. To benefit from these cloud migration advantages, companies need to plan and implement the process carefully.

cloud migration types

Cloud Migration - 5 Types

There are different types of cloud migrations that vary depending on the organization. Choosing the right migration strategy depends on an organization's specific business needs, existing infrastructure and long-term goals. Here are 5 common cloud migration types:

Full data center exit (Full Data Center Exit)

This refers to the comprehensive relocation of all of a company's data, applications and IT resources from a local data center to a cloud platform. The aim is to move the entire IT infrastructure to the cloud.

Migration from one cloud to another (cloud-to-cloud migration)

Sometimes companies decide to switch from one cloud platform to another. This may be due to cost efficiency, better services or extended access to artificial intelligence, the platforms offer.

Migration of certain applications or datasets to the cloud

In this case, companies move selected applications or databases from a local environment to a cloud infrastructure. This allows them to gradually migrate to cloud services without moving their entire infrastructure. Organizations often use this for Business intelligence, CRM, datasets, applications for machine learning and others.

Migration of certain workloads (cloud workload migration)

Here, migration takes place on the basis of workloads or specific tasks. Companies move certain workloads, such as development environments, test systems or applications with seasonal requirements, to the cloud in order to use resources more efficiently.

Reverse cloud migration

Reverse cloud migration refers to the process of moving applications or data from the cloud back to local infrastructures. This is often done for reasons such as security concerns or changing business requirements. We do not discuss this type of migration in detail in our article.

Cloud Migration Strategies and Methods

To successfully move to a cloud, companies can use various cloud migration strategies and methods. The following table summarizes the most important ones: 

StrategyGoal and descriptionBenefitsDisadvantagesFor whom suitable
Host change: Lift-and-shiftMinimal changes during migration, rapid deployment of applications in the cloudFast implementation with minimal effort, low risks during migrationOften does not use all cloud-native features and efficiencies, limited optimization and adaptation to cloud servicesOrganizations with predictable peak usage patterns, often the first step in a larger digital transformation project
Platform change: Lift-and-OptimizeLifting and optimizing existing applications for the new cloud environmentHigher performance and efficiency in the cloud, use of cloud functions such as microservice architecture or containersRequires more work than lift-and-shift, platform change requires careful testing and validationOrganizations that want to use all the core competencies of the cloud or are looking for flexibility in their choice of infrastructure
Refactoring: Moving and improvingDesigning applications in cloud-native style, often through code changes without changing the front endBetter utilization of cloud features for improved performance, ability to add new features such as scalability or machine learningCan be more complicated than rehosting, requires more extensive changes to the codeCompanies that need new cloud functions and scalability or are looking for more flexibility and customization options
RemodelingChanging the way the application code works to optimize for cloud-native featuresUtilization of cloud advantages such as scalability and security, transformation into independent microservices possibleRequires more time and effort than refactoring, higher complexity and potentially new errorsCompanies that want to take full advantage of cloud-native benefits such as scalability and security
Create newComplete rewrite of an application for the cloudSelection of cloud-native tools and functions from the outset, re-planning and optimization possibleTime-consuming, possible errors or performance problems, not suitable for all applicationsCompanies that want to plan from scratch and use cloud-native tools from the outset
Repeated purchasesSwitch from local applications to cloud-hosted software-as-a-service solutionsSimple change of resources compared to refactoring or conversion, uses established cloud servicesCan be more expensive, limited control over cloud environmentOrganizations that prefer the convenience and simplicity of cloud-hosted SaaS solutions and can accept the cost
Cloud migration in 5 steps with best practice

Cloud Migration Best Practice - How it works in 5 Steps

To successfully migrate to the cloud, companies can use this cloud migration best practice as a guide:

Step 1: Evaluate

Evaluation is the starting point for cloud migration. First define the resources and capacities of applications. Create a list of applications, identifying their frequency of use and key stakeholders. Determine which applications are suitable for the cloud. In this context, also determine the necessary security and compliance requirements.

Step 2: Planning

For a successful cloud migration, it is crucial to select a suitable strategy for each application. This lays the foundations for the subsequent migration plan. Develop a cloud infrastructure from areas such as computing, network, storage and security. Identify the functions of the workloads that you want to migrate to the cloud.

Step 3: Testing

Before the actual migration begins, you will develop a comprehensive test strategy. You use this to test the migration of data and its synchronization and validate security controls. You document any necessary changes that you make during the tests in detail.

Step 4: Migrate

Perform the cloud migration according to the pre-defined plan for each application, workload and instance. This is done in phases, with each phase being validated in the cloud. Apply lessons learned from one phase to the next phase.

Step 5: Optimize 

The process does not end after cloud migration. Monitor all applications and processes in the cloud to ensure efficient use and improve the user experience. Keep an eye on running costs and react to any changes in requirements.

Cloud Migration Benefits

Cloud migration offers a variety of benefits that motivate companies to move their IT infrastructure from local data centers to the cloud or from a cloud to a more powerful, more suitable cloud. The main advantages of migrating applications are as follows:

Scalability and flexibility

A cloud enables companies to scale their resources as required. This means that they can flexibly adapt their computing power, storage capacity and other resources to respond to fluctuations in demand or business requirements.

Example: An online retailer uses considerably more server capacity in the cloud during a sales event such as "Black Friday" to cope with the expected rush of customers. After the event, it reduces capacity again to save costs.

Cost efficiency

Cloud services enable a pay-as-you-go model where companies only pay for the resources they actually use. This eliminates the need for expensive upfront investment in hardware and enables more accurate budgeting.

Example: A company that operates a temporary application for a limited period of time adds additional cloud resources during this time and reduces them again once the project is complete to avoid unnecessary costs.

Faster time to market

The cloud enables companies to provide resources in the shortest possible time without having to wait for physical hardware to be purchased and set up. This accelerates the development and market launch of new products and services.

Example: A software company uses cloud resources to quickly set up a development and test environment to test new functions or applications before they are released on the market.

Improved collaboration and accessibility

Cloud services enable access to data and applications from anywhere in the world, which promotes collaboration between distributed teams. Employees work more efficiently, regardless of their location.

Example: An international company with branches all over the world uses the cloud to provide a shared platform for collaboration. Employees access the same data and applications from different locations and work together effectively.

Automation and efficiency

Some cloud platforms offer extensive automation options - from the provision of resources to scaling and management. This leads to a more efficient use of IT resources and reduces the manual workload.

Example: A company automates the provisioning and scaling of applications in the cloud based on predefined utilization thresholds. This increases efficiency as resources are automatically adjusted to meet current demand.

cloud migration challenges

Cloud Migration Challenges

In order to benefit from these advantages, companies initially face a number of cloud migration challenges. To overcome these, you should plan a successful migration thoroughly and work closely with all parties involved. Pay particular attention to the following challenges to avoid errors and failures:

Complexity of data migration

Transferring large amounts of data from local servers to the cloud can be very complex, especially if the data is available in different formats or structures.

Practical example: A company wants to migrate its extensive customer database to the cloud. This database contains customer names, contact details, order histories and specific preferences. The challenge is to ensure that all data is transferred to the cloud consistently and correctly, while eliminating possible inconsistencies or duplicates.

Security and compliance challenges

Ensuring security and compliance during cloud migration requires careful planning and implementation to ensure that sensitive data remains protected and legal requirements are met.

Practical example: A financial institution is planning to migrate its customer account data to the cloud. In doing so, it must adhere to strict security standards to ensure that personal information is protected. At the same time, it must take into account the industry's data protection regulations and possibly country-specific regulations in order to avoid legal consequences.

Application dependencies and integration

Many companies operate complex IT landscapes with closely interconnected applications. The migration of an application to the cloud can therefore have an impact on other applications that are dependent on it.

Practical example: A manufacturing company migrates its enterprise resource planning (ERP) system to the cloud. However, this ERP system is highly integrated and dependent on various internal applications, from supply chain to accounting. The challenge is to ensure that there are no interruptions in the integrated processes during the migration.

Cost management and scalability

The cost of cloud resources can be difficult to predict. Inaccurate planning can therefore lead to unnecessary expenditure. Similarly, scaling resources to increase or decrease performance as needed is a challenge.

Practical example: An e-commerce company migrates its website to the cloud to cope with seasonal peaks in online shopping. The challenge is to manage the cost of the additional resources during peak periods and ensure that the website remains scalable in the event of a sudden increase in traffic.

Skills shortage and training needs

The successful implementation of a cloud computing migration strategy requires specialized knowledge and skills in dealing with cloud platforms. A lack of qualified specialists leads to delays and uncertainty.

Practical example: A medium-sized company is planning to migrate its IT infrastructure to the cloud. However, the existing IT department does not have sufficient experience in the cloud area. The challenge is to train the team or hire external experts to ensure a smooth migration.

Konfuzio as the Key to Efficiency in the Cloud 

Cloud migration has many advantages such as flexibility and scalability, but companies with large datasets in particular face the challenge of managing the complexity of data migration and data analysis as efficiently and error-free as possible. To support companies in this, Konfuzio has a powerful artificial intelligence, which combines Machine Learning, natural language processing, optical character recognition and Deep Learning, among others.

In practice, this means: Konfuzio supports companies in efficiently and accurately transferring existing data volumes from applications, resources and processes to the (new) cloud. AI makes it possible to (partially) automate these processes and thus reduce the effort and susceptibility to errors involved in cloud migration.

Once the migration to the cloud is complete, you can use Konfuzio to automatically analyze and evaluate the data that is now in the cloud and make sound, data-based business decisions based on this. This allows you to use your resources efficiently.

Would you like to know how you can automate and improve your data management with AI from Konfuzio? Then talk to one of our experts now, with no obligation, and find out how you can make the most of your data's potential - and stay competitive.

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