Multi-Cloud & Hybrid Cloud: Workload Optimization




Wissen Team


September 7, 2023

In 2023, 84% of IT decision-makers foresee a surge in data stored within the public cloud. On average, businesses assign 14% of their IT budgets to public cloud storage services for optimizing workloads.

However, there are still many challenges associated with using the public cloud. One challenge is that it can be difficult to optimize workloads across multiple cloud platforms. This is where multi-cloud and hybrid cloud strategies can be helpful.

As companies continue to merge their IT environments to increase return on investment (ROI), they will likely realize that hybrid cloud strategies can prove to be valuable tools in optimizing workloads across platforms.

Workload Classification and Placement

As per a study, 60% of all corporate data was in cloud storage in 2022. Indeed, the placement and classification of workloads in a cloud environment is crucial. It should be carried out in a manner that maximizes performance and cost efficiency.

A placement plan requires basic knowledge of the workload's composition, how it can benefit from various cloud deployment models, and how it will interact with other workloads running in the same environment. Here's how you can go about workload classification and placement:

Identify suitable workloads for a multi-cloud or hybrid setup

Analyze workload characteristics, dependencies, and latency requirements to select workloads suitable for multi-cloud or hybrid architecture.  

Determine workload distribution across platforms

Some factors to consider when determining workload distribution include cost, performance, and security. Why these factors? Because they can vary across different cloud platforms.

Challenges of Optimizing Workloads Across Platforms

When optimizing workloads across cloud platforms, organizations face several challenges, including:

  • Data silos: Siloed data is stored in different systems and is not easily accessible. This can make it challenging to manage and analyze data.
  • Security: Security is a major concern when using multiple cloud platforms. Organizations need to ensure that their data is secure and that they are compliant with regulations.
  • Vendor lock-in: Vendor lock-in occurs when an organization becomes dependent on a particular cloud provider. This can make switching providers or moving workloads to other platforms difficult.
  • Cost: The cost of using a multi-cloud or hybrid cloud environment can be higher than using a single cloud platform.
  • Complexity: Managing a multi-cloud or hybrid cloud environment can be complex. It can make tracking costs, ensuring compliance, and troubleshooting problems difficult.

Strategies for Multi-Cloud & Hybrid Cloud Workload Optimization

In 2023, it is expected that approximately 63% of SMB workloads and 62% of their data will be effectively hosted in cloud environments. This is predominantly driven by the promise of multi-cloud and hybrid-cloud workload optimization.

Here are some strategies to optimize workloads across multi-cloud and hybrid cloud:

Load Balancing and Auto-Scaling Techniques

Load balancing distributes workloads across multiple cloud resources, which can help to improve performance and reduce costs. On the other hand, auto-scaling automatically adjusts the number of resources used to meet demand, ensuring that workloads are always running at peak efficiency.

In a hybrid or multi-cloud setting, load balancing plays an immensely critical role, for it serves to distribute the traffic among different cloud servers running across different cloud environments. With the use of universal traffic management policies, enterprises can ensure that their load balancing efforts are delivering, especially when it comes to optimizing resource usage and reducing the application response time.

Leveraging Automation

There's no doubt that it can be daunting to manually manage multiple cloud resources. Multi-cloud and hybrid cloud settings can, in fact, be more complex. There's so much to manage, including workloads, nodes, containers, and services.

The good news is that you can significantly reduce the complexity by leveraging automation. But what does it look like? For one, teams can leverage event-driven triggers to execute scripts and commands when certain events take place, enabling them to automate tasks such as deployment and backup. But that's not it! They can do so much more by automating the:

  • Provisioning of server capacity
  • Configuring and managing cloud services
  • Scaling and managing applications
  • Monitoring and analytics

At the end of the day, such automation can help improve the response time and boost application performance. It enables teams to ride on fewer resources to achieve more — thus optimizing the usage and management of workloads. Once they have an automation workflow set up, it becomes easier for them to continue running automation with little effort.

Redundancy and Failover Mechanisms for Critical Workloads

Critical workloads are those that are essential to the business. Redundancy and failover mechanisms ensure that these workloads can continue to operate even if one or more cloud resources fail. This can be achieved by using multiple cloud resources for each workload or by using cloud-based services that provide redundancy and failover capabilities.

These are just some of the strategies that can be used to optimize workloads across multi-cloud and hybrid-cloud environments. The specific strategies a company can look forward to adopting will depend on their unique requirements.

Analyzing Workload Demands

This might sound rudimentary, but it is also important to get down to the basics. You'll need to identify the various workloads that will be hosted in the hybrid or multi-cloud environment and how they will be used. Plus, it's exceptionally important to have a clear picture of what each workload demands from the infrastructure. For example, are there any complex workloads that rely on high compute power? Are the hybrid cloud servers capable of handling these workloads? If not, how do you distribute computing tasks?

Such questions will help teams get a more profound and holistic picture of what's required to run these workloads. They will also pave the way for determining the reliability of the cloud resources and the best ways to utilize them.

In a Nutshell

All in all, there are so many things to consider when hosting critical workloads across hybrid and multi-cloud environments, and understandably so. In a world where data, security, cost, and automation are crucial to ensuring the sustainability of the business, organizations need to have a clear understanding of what they need from the cloud infrastructure. Only then would they be able to embark on a journey where they successfully optimize their resource usage and the subsequent deployments.

Seeking the knowledge and support of cloud experts can be helpful in achieving this goal. By carefully analyzing the requirements of each workload and appropriately configuring the infrastructure, a cloud services expert like Wissen can help organizations take advantage of hybrid and multi-cloud settings. Get in touch for a more nuanced discussion!