To ensure a successful cloud strategy, organizations need to holistically consider workload requirements for both present and future applications. Learn more about establishing a solution that meets evolving use cases and long-term requirements.
Many organizations are eager to adopt cloud solutions to take advantage of key benefits such as increased efficiency, agility and growth. However, to ensure a successful long-term cloud strategy, it’s important for organizations to holistically consider their workload requirements for both present and future applications. Taking a narrow view that only focuses on a single type of workload can result in a strategy that fails to address the full potential of the cloud.
Workloads vary widely, ranging from enterprise applications found in the typical datacenter to mobile apps born into the cloud. Most businesses begin using the cloud for distributed cloud native apps but rapidly realize the need to also incorporate the vast base of existing enterprise application workloads into a standardized cloud architecture. That can present challenges as the different categories of workloads each bears its own set of specific hardware, storage, networking, availability and redundancy requirements as well as different overarching architectural characteristics.
The majority of existing enterprise applications that live in the datacenter fall into this workload category. Traditional applications achieve scale by scaling up to increase the size of the application and database infrastructure. As a result, the architecture of these workloads is somewhat limited in scalability.
Enterprise workloads are also traditionally designed to run on reliable hardware and utilize complex technologies to ensure availability. Traditional workloads require fault tolerant architectures and are built using enterprise-grade infrastructure components.
The new generation of applications typically associated with cloud computing fall into this workload category. These applications achieve scale by scaling out across many loosely coupled, commodity-grade computing, networking and storage nodes. As a result, these workloads are able to achieve dynamic scaling and elasticity.
Cloud native workloads are built for infrastructure that isn’t expected to be resilient. Instead, they are designed to simply and efficiently handle the failure of any given node. Because they don’t require enterprise reliability, these workloads can use commodity and open-source architecture components.
Due to these inherent differences, workloads are one of the key factors organizations need to consider when developing a cloud strategy and selecting a cloud orchestration platform. By planning ahead to address both types of workloads, it’s possible to establish a solution that meets evolving use cases and long-term business requirements.