Multi-Cloud has become an essential pillar of the digital strategy of companies seeking performance, flexibility and resilience. However, this approach brings with it increased complexity, particularly when it comes to costs. Controlling these costs is a major challenge, requiring appropriate strategies and effective tools.
Why adopt a Multi-Cloud strategy?
Multi-Cloud allows businesses to deploy their services across multiple providers, offering freedom of choice and risk diversification. As each provider has its own strengths, it is possible to combine the most effective solutions for each specific use. In the event of the failure of one provider, business continuity is ensured by the other platforms, reinforcing overall resilience.
For example, a company specialising in data analytics can take advantage of the strengths of several providers: it uses AWS to store its raw data via Amazon S3, Google Cloud BigQuery for real-time analysis, and Microsoft Power BI for consolidating its reports. By combining these solutions, the company exploits the best tools from each platform while reducing its dependence on a single provider.
Multi-Cloud offers unprecedented architectural freedom, allowing companies to choose the best technology for each use case.
This approach also meets regulatory requirements, allowing data to be stored in specific geographical regions, and improves the proximity of data centres to reduce latency. However, it comes with challenges that need to be anticipated and mastered.
What are the major challenges of the Multi-Cloud and how can they be overcome?
1. Interoperability and centralised management
Each cloud provider offers its own interfaces, APIs and management tools, which can complicate the integration and administration of services. Centralised management, via orchestration platforms and automation solutions, can simplify operations and limit the risk of errors.
Example: A financial services company synchronises its data between AWS, Azure and Google Cloud using tools such as Apache Airflow and Terraform, ensuring smooth interoperability and efficient orchestration of data flows.
The key lies in implementing automated pipelines to manage the complexity inherent in these heterogeneous environments.
2. Security and compliance
The multiplicity of cloud environments means that cybersecurity policies need to be harmonised. It is crucial to put in place continuous monitoring mechanisms, strict access controls and incident response strategies to guarantee optimum data protection.
Example: A bank operating on several clouds adopts a Zero Trust model, combining a multi-factor authentication system and data encryption to secure transactions and protect sensitive information.
Security in the Multi-Cloud relies on constant vigilance and a strict access control policy.
3. Managing and optimising costs
Differences in pricing between suppliers, as well as the hidden costs associated with data transfer and storage, can quickly lead to inflation in spending. Adopting cost monitoring and optimisation tools is essential to gain a clear view of spend and adjust resources accordingly.
Example: A big data company allocates its analytical workloads between Google Cloud and Azure based on cost and resource availability. Using tools such as Spot.io and FinOps, it optimises the cost of instances and reduces cross-cloud data transfer costs.
How do you optimise costs while maintaining performance?
Adopting a Multi-Cloud strategy offers valuable flexibility, but can quickly become costly without rigorous management. There are several strategic levers that can be used to control this expenditure:
- Continuous monitoring of resources: Tracking resource usage in real time helps to detect under-utilised services and reduce unnecessary costs.
Example: A gaming company uses Datadog to monitor its cloud servers and adjusts resource allocation based on the number of connected players, optimizing performance and spend
- Deployment automation: By automating processes, human errors are reduced, updates are faster, and resource allocation is optimised.
Example: A fintech player uses Terraform and Ansible to manage the deployment of databases across multiple clouds, guaranteeing better management and precise cost control.
Dynamic scalability: Automatically adapting resources to demand prevents over-provisioning and aligns costs with actual consumption.
Example: A marketing analytics platform continuously adjusts the computing power of its Snowflake databases on AWS and Google Cloud according to the volume of queries, guaranteeing a balance between performance and budget control.
Automation and continuous monitoring are the real levers for optimisation in a Multi-Cloud environment.
At CBTW, we support our customers in implementing high-performance Multi-Cloud strategies, simplifying management and optimising costs thanks to our expertise and tailored solutions.
Conclusion
Multi-Cloud offers undeniable advantages in terms of flexibility, resilience and performance. However, it requires rigorous cost management, made possible by the adoption of automation tools and clear governance. A strategic approach not only reduces expenditure, but also optimises the added value of the services deployed, guaranteeing a sustainable competitive advantage in an ever-changing digital world.