Cloud migration - Challenges, methods and best practices for migrating a data platform to the cloud
Get the keys to mastering the different aspects of data migration to the cloud, for a smooth, successful transition tailored to your organization's needs.
- Anticipate the challenges of a Cloud migration : migrating a data platform involves technical issues (interoperability, security, compliance) and organizational issues (team training, change management, etc.).
- Choosing the right strategy: different approaches to Cloud migration exist (Lift & Shift, Re-platform, Re-factor), depending on the company's needs and level of maturity.
- Maximize benefits: a migration to the cloud offers scalability, cost optimization, access to advanced technologies (AI, analytics), and enhances innovation and agility.
Understanding data migration to the cloud
What are the main challenges involved in migrating a data platform to the cloud?
Technical complexity
Migration involves managing the coexistence of different information systems that have developed over time. This technical diversity, in terms of both architectures and data formats, calls for meticulous planning to orchestrate the transfer to the cloud.
Compliance & safety
Complying with regulations such as RGPD or ISO 27001 is essential to guarantee the protection of sensitive data (such as for the healthcare sector) and avoid any legal or operational risks.
Team adoption
The success of a migration also depends on the support of employees, who must be trained in the new tools and supported in the evolution of their existing ones.
Key steps for a successful Cloud migration of your data platform
1. Assessment of existing systems: mapping data and applications
Before starting migration, it's essential to carry out a detailed audit of existing infrastructures. This includes mapping data, applications and processing flows, to identify dependencies and potential friction points.
What's more, it's important to anticipate performance and scalability requirements, so as to adopt an architecture adapted to the company's growth objectives.
Identifying critical data and defining priorities, in conjunction with business and IT teams, ensures smooth, secure data transfer, minimizing interruptions and operational risks.
2. Choice of Cloud migration strategy
There are several migration strategies tailored to the needs and constraints of each company:
Re-host (Lift & Shift) :
This approach involves moving applications and data to the cloud without any major modifications. It is ideal for companies wishing to migrate quickly without impacting their existing processes. Although it's quick to implement, it doesn't always allow you to exploit the full benefits of the cloud.
Re-platform :
This is a partial adaptation of applications to take advantage of native cloud services, such as autoscaling or managed databases.
Autoscaling is a cloud feature that automatically adapts and resizes resources according to usage, guaranteeing performance and cost optimization. Managed databases, on the other hand, are services where infrastructure, backups and maintenance are managed by the cloud provider, enabling companies to focus on data exploitation rather than infrastructure maintenance.
This approach improves performance and reduces operating costs, while minimizing change.
Re-factor :
This strategy involves a complete overhaul of applications so that they are designed specifically for the cloud. This may include a transition to a microservices-based architecture or the use of containers.
Microservices are an approach in which an application is broken down into several independent services, each with a specific function. This facilitates scalability, agility and maintenance.
Containers, on the other hand, enable applications to be run in an isolated, portable way between different environments. Technologies such as Docker and Kubernetes facilitate their management and orchestration, improving application portability and enhancing security through container isolation.
The adoption of microservices should respond to concrete needs, rather than be a fad. This architecture reveals its full potential when an application requires autonomous components, capable of evolving at their own pace. While it offers greater agility and easier maintenance, it also makes the business complexity of the application more visible: each service clearly exposes its responsibilities, interactions and dependencies. This transparency requires solid technical expertise to properly design, orchestrate and monitor the entire system.
Repurchase/Replace :
In some cases, it may be more advantageous to replace an existing application with a SaaS solution on the market. This means immediate access to functionality and updates, without the need for in-house maintenance.
Hybrid approach :
Some companies opt for a combination of several strategies, depending on the complexity and criticality of the applications being migrated. For example, they may opt for a Lift & Shift for some applications and a complete overhaul for others, in order to optimize costs and performance.
3. Selecting your solution for efficient Cloud deployment
When it comes to migrating your data to the cloud, you can choose between several leading cloud providers: AWS, Microsoft Azure or Google Cloud Platform; and use platforms such as Snowflake and Databricks. Discover our experts' guide to choosing the right cloud solution and technology tools.
4. Planning and implementing your Cloud migration
Once the strategy and cloud environment have been defined, the migration must be planned in several phases.
Step 1) Drawing up detailed specifications
The first step in a successful Cloud migration is to draw up precise specifications, defining the project's technical and operational requirements. These should include :
- Identification of the applications and data to be migrated as a priority, taking into account their criticality and existing dependencies.
- The definition of a realistic timetable, in line with business needs and technical capabilities.
- Assessment of the resources required, both in terms of infrastructure and in-house skills.
Two key indicators must be defined at this stage, as they have a direct impact on migration planning, technical choices and changeover strategy:
- RTO (Recovery Time Objective): The maximum acceptable downtime in the event of an incident. The shorter this objective, the more robust high availability solutions and rapid recovery strategies will need to be.
- RPO (Recovery Point Objective): The maximum amount of data the company is prepared to lose in the event of a failure. A low RPO requires advanced backup and real-time replication mechanisms.
It's essential to involve IT and business teams right from this phase to ensure that the migration strategy meets operational needs, while minimizing risks and service interruptions.
Step 2) Choosing the type of Cloud migration planning
It depends on a number of factors, such as system complexity, business continuity requirements and risk tolerance. Three main approaches can be considered:
This approach involves migrating all data and applications at once. It is well suited to less complex environments, or to systems requiring a rapid transition. However, it does present a higher risk in the event of failure, as it is more difficult to turn back the clock.
This gradual approach allows workloads to be migrated one by one, or by functional category (e.g. databases first, then analytical applications, etc.). It reduces risk and enables adjustments to be made along the way, but requires finer coordination.
This approach involves deploying the cloud environment in parallel with the existing system, with a period of coexistence before the final switchover. This enables the cloud infrastructure to be tested without interrupting operations, but entails additional costs associated with maintaining both environments.
Step 3) Defining failover tests
To ensure a smooth transition, it is essential to test the failover mechanisms between the old system and the new cloud environment. It is necessary to ensure data integrity and performance, as well as the compatibility of applications with the cloud environment. These tests should include :
These tests check that the new environment is capable of handling the volume of data and transactions.
The aim is to ensure that all applications and databases function correctly after migration.
They validate the application of access management, encryption and compliance policies.
They involve simulating failure scenarios to check the ability to restore services rapidly in the event of an incident.
Migration to the cloud requires automation of two distinct aspects. On the one hand, infrastructure provisioning is managed by Infrastructure as Code tools such as Terraform or Ansible. On the other, data flows are orchestrated via ETL pipelines dedicated to migration. This dual automation secures deployments and ensures data consistency throughout the migration process.
Step 4)Defining a synchronization strategy
During migration, it's crucial to ensure that data remains consistent between the old system and the cloud. A good synchronization strategy helps avoid data loss and inconsistencies. Several options are available:
Data is copied to the cloud in real time, guaranteeing a smooth transition with no major interruptions.
Updates are carried out in batches at defined intervals (e.g. every 24 hours), which may be sufficient for certain non-critical applications.
Some organizations choose to maintain dual synchronization between the cloud and the old environment for a given period, before making a definitive switchover once stability is assured.
Step 5) Adoption of Agile, DataOps and DevOps methodologies
These approaches enable processes to be rapidly adjusted in line with user feedback, with a view to continuous integration and process optimization.
Step 6) Post-migration cloud monitoring and optimization
Once the migration is complete, it's essential to monitor performance, optimize the use of cloud resources and adjust configurations to meet changing business needs.
The benefits of migrating data from your data platform to the cloud
Scalability to meet growing needs
Cost optimization
Migrating your data platform to the cloud reduces operational costs by eliminating the expense of maintaining physical infrastructures and reducing the complexity of day-to-day operations. By opting for a pay-as-you-go model, companies can adjust their spending according to actual consumption, avoiding heavy investment in physical infrastructure.
This flexibility also enables financial resources to be better allocated to strategic, high value-added projects. In the long term, the cloud promotes better process optimization by automating many data management tasks, reducing the workload of IT teams and improving their efficiency.
Cutting-edge solutions only available in the cloud
Some of the most powerful solutions for data management and analysis, such as Snowflake and Databricks, can only be accessed via the cloud. By migrating to a cloud environment, companies can leverage these advanced tools to enhance their analytical capabilities, optimize their data flows and gain insights faster.
Enhanced security and compliance: compliance with standards (RGPD, ISO...)
Contrary to popular belief, cloud environments offer high levels of security thanks to advanced encryption protocols, stringent access controls and real-time monitoring. Cloud providers are certified to strict standards such as RGPD, ISO 27001 and SecNumCloud, guaranteeing enhanced compliance with current regulations.
Accelerating innovation
The cloud encourages innovation by enabling companies to rapidly experiment with and deploy new technologies. Unlike traditional infrastructures, it eliminates the need for upfront investment, giving organizations immediate access to advanced technologies such as artificial intelligence, data analysis or IoT.
Thanks to this flexibility, companies can quickly and easily test new solutions, even under heavy load, without impacting their existing infrastructure. This ability to experiment without constraint significantly reduces financial risk, as it becomes possible to fail quickly and cost-effectively, then iterate to improve solutions. By offering this agile environment, the cloud accelerates digital transformation and enhances responsiveness to market changes.
This flexibility encourages digital transformation and improves responsiveness to market changes.
Leveraging Artificial Intelligence (AI)
Artificial intelligence is now an essential asset for companies wishing to optimize their business processes, but large-scale access to it is only possible via the cloud.
The computing power provided by hyperscalers makes it possible to run complex machine learning models in record time, which would be impossible with a conventional infrastructure. What's more, managed services simplify the integration of AI into workflows, reducing the need for in-house technical expertise. By automating data analysis and repetitive tasks, teams gain in productivity and can focus on higher value-added activities, such as innovation and business strategy.
The challenges and complexities of the Cloud migration process
Data migration to the cloud, while offering many advantages, also brings its share of challenges and complexities. These obstacles can stem from a variety of technical, organizational and regulatory aspects that require rigorous preparation and management. In this section, we'll explore the main challenges encountered during this process, as well as solutions for overcoming them effectively.
A need for training
Migrating a data platform to the cloud can involve reviewing existing architectures, adapting applications and ensuring interoperability between systems. This transformation requires in-depth technical expertise and effective management of dependencies between services. Companies also need to anticipate changing needs and choose the most appropriate technologies.
This transition often requires the training of technical and business teams, so that they can fully exploit the new cloud solutions. Specialized training in cloud tools, migration best practices and distributed data management is essential to ensure successful adoption and minimize potential errors.
It is therefore crucial to prepare teams for this transition. To this end, companies can set up a Cloud Center of Excellence (CCoE), a group of people in charge of supporting teams, animating internal communities and disseminating best practices linked to the use of the cloud. This center of expertise plays a key role in cloud acculturation, facilitating the adoption of new technologies and ensuring an efficient transition.
This preparation includes :
- Training courses on cloud technologies and new data management tools.
- Training courses on cloud technologies and new data management tools.
- Encouraging staff certification on the cloud platforms used (AWS, Azure, GCP), guaranteeing structured skills development.
Resistance to change
Adopting the cloud represents the biggest challenge in any migration. It is essential to support this transition with appropriate training, clear communication and a strong commitment from all stakeholders to limit reluctance and ensure successful adoption.
IT teams need to be involved from the earliest stages of the project to avoid fears of loss of control. Effective change management also relies on strong sponsorship and internal ambassadors to support employees in adopting new practices and tools.
Managing sensitive data and regulations
Contrary to popular belief, public cloud providers are not "open door" environments; on the contrary, they offer advanced data encryption and security solutions. They feature robust security measures, including data-at-rest and data-in-transit encryption mechanisms, multi-factor authentication systems and role-based access management. However, teams need to be trained to use these tools appropriately and guarantee data protection.
Some industries, such as finance and healthcare, are subject to strict regulations that impose restrictions on data storage and processing. For example, certain C3 data cannot be stored in the cloud, as is the case for certain information in the banking and healthcare sectors. In this context, it is essential to choose cloud providers or environments that meet the specific requirements of each sector. In addition, effective data governance ensures that all processes meet compliance and confidentiality requirements.
Avoid common mistakes when Cloud migration your data platform to the Cloud migration
Lack of planning for Cloud migration
Lack of detailed planning is one of the most common mistakes made when migrating a data platform to the cloud.
Without a clear roadmap, teams risk encountering unforeseen obstacles, such as technical incompatibilities, deployment delays or unexpected costs. It's essential to take the time to define the key stages of the migration, establish priorities and determine the necessary resources.
Underestimating resource requirements
Lack of alignment between stakeholders
In the absence of a shared vision and collaboration between different teams (technology, security, legal, sales, etc.), conflicts can arise over priorities, security requirements or even the objectives to be achieved.
The IT team may want to focus on technical performance, while the legal department may be more concerned with compliance. To avoid these pitfalls, it's important to set up an ongoing communication process, clarify expectations from the outset, and define a governance plan that involves all stakeholders.
Progressive testing not enough for a successful Cloud migration
Progressive testing plays a crucial role in the success of cloud migration, but this step is often overlooked. Testing must be carried out regularly and systematically to ensure that every component works as expected in the cloud environment.
This includes not only performance testing, but also security and resilience testing. Progressive testing allows errors or inconsistencies to be identified and corrected before they affect the whole system. Testing should be carried out in small steps throughout the migration process, rather than waiting until the end of the project to carry out a final test.
How do you create an effective data migration plan?
Successful data migration to the cloud requires careful planning and structured execution. An effective plan must incorporate several key stages to ensure a smooth, controlled transition.
1. Identify priorities
Before embarking on migration, it is essential to identify priorities based on business needs and technical constraints. Some data or applications may be more critical than others, requiring priority migration to ensure business continuity. It is important to :
Classify data
according to their criticality and frequency of use.
Determining workloads
who will benefit most from the move to the cloud (performance, flexibility, cost).
Prioritizing migration
in line with the company's strategic objectives.
2. Define a realistic timetable
A timetable needs to be defined, taking into account technical and organizational complexities. It is necessary to :
Cutting out migration
in progressive phases to minimize risk.
Schedule tests
at each stage to identify and correct problems before going into production.
Ensuring flexibility
to be able to adapt to unforeseen circumstances.
An over-ambitious schedule can lead to errors and service interruptions, while one that is too spread out can generate additional costs and slow down the company's digital transformation.
3. Measuring return on investment (ROI)
Migration to the cloud represents a significant investment, so it's essential to measure the benefits to justify the transition. To do this, you need to :
Evaluating costs
before, during and after migration (infrastructure, maintenance, team training).
Identify gains
in terms of performance, salability and agility.
Tracking key indicators
such as data processing time, reduced operating costs, improved service availability.
Ready to embark on the Cloud migration your data platform?
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