Every time a server runs an application, it processes a workload. A workload can be a small program running in the background of a server or a large database application managing millions of query requests. The size of the workloads will drive the amount of computer resources necessary to run enterprise applications.
What Is a Workload?
The load on a server’s resources is defined by the workload. Workloads can be very small where only a small amount of memory and central processing unit (CPU) calculations are necessary. For example, small input commands from a keyboard are small workloads. Larger workloads include applications requiring high amounts of memory and CPU usage, including database engines or machine learning analytics.
Although an application is a workload, not all workloads are applications. The computer’s operating system handles several basic tasks invisible to the user, but these small tasks are also considered workloads. When you turn on a computer, the operating system loads and executes basic operations for you to interact with the CPU. These operations are workloads, but they aren’t applications a user can control. These workloads are necessary and require computer resources.
Since workloads require computer resources, many enterprise businesses have a placement strategy to determine if a workload should run in the cloud or on premises. A hybrid cloud environment is common where some business resources run on premises, and more complex and advanced workloads run in the cloud. A placement strategy leveraging cloud computing lowers the costs of equipment and provides companies with advanced technology that would otherwise not be available to most of them.
What Is a Cloud Workload?
In cloud computing environments, businesses only pay for resource usage rather than buying all the high-end computing equipment and hosting it on premises themselves. Offloading workloads to the cloud lowers IT costs, especially for advanced technologies. Most businesses offload their web servers to the cloud, and the cloud provider handles all the equipment, housing, and security to host web applications.
Most workloads can be offloaded to the cloud, but businesses must create a placement strategy before considering a migration to the cloud. Every workload responsibility can be migrated to the cloud, including identity management, productivity applications, storage, databases, and backend processing for departments. A placement plan should consider current workflows and match a corresponding cloud resource for business workloads to ensure a smooth transition to the cloud.
Different Cloud Workload Types
Businesses can pick and choose the workloads they want to migrate to the cloud. The most common strategy is to offload web services to the cloud. Web workloads include the servers hosting websites, web applications, and APIs. The benefit of offloading web services to a cloud provider is that the provider has load balancers and fast equipment to scale resources and handle spikes in traffic and resource usage.
Serverless or cloud-native applications use only cloud resources without requiring management of a virtual machine (VM). All data processing is handled in the cloud, so workloads have the computing power necessary for user workflows and applications. Legacy applications are often migrated to cloud native to leverage the power of the cloud without finding outdated equipment to handle unique workloads.
The cloud has virtually endless resources. Businesses scale up or down as necessary, so high-performance computing workloads are perfect for cloud resources. An example of a high-performance workload is a database server handling thousands of queries every minute or every hour. A business needs extensive workload resources for these applications, and the cloud offers scalability during spikes in usage. The database workloads can be linked to internal and external workflows and maintain security of the environment.
What Are Amazon AWS Workloads?
Amazon Web Services (AWS) cloud resources handle some of the world’s biggest workloads. EC2 virtual machines can be used for web applications and user traffic without the need for administrators to manage local equipment. Data warehousing with AWS Redshift handles large database workloads, and AWS Mobile Hub handles applications for smartphones and mobile users.
Migration to AWS locks businesses in with most of its services, so always take time to assess business operational needs before choosing a cloud provider. Some businesses choose to have a multi-tenant environment to handle different workloads and eliminate a single point of failure. A business migration to AWS or any cloud provider requires a plan, thorough testing, and user training for the new environment.
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What Workloads Can Microsoft Azure Handle?
Microsoft Azure is another cloud provider popular with businesses working with Microsoft applications. Similar to AWS, Azure offers virtual machines that administrators can provision for web applications without the need to manage hardware locally. Although Azure is a Microsoft provider, virtual machines can run Linux or Windows server operating systems.
Serverless operations are available using Azure App Service. For example, a business can run a WordPress application using serverless technology instead of using a virtual machine. Serverless resources require no server management, so businesses use the application without any upgrades for operating systems or patch management of software.
For businesses with internet of things (IoT) integration, Azure IoT Hub is available to handle workloads of mobile devices. For example, a warehouse using IoT to monitor machinery could use Azure IoT services to manage the storage and processing of artificial intelligence used to alert administrators of anomalies. Offloading IoT services is much more convenient, scalable, and available for small and large businesses, and it requires much less setup and deployment overhead.
Pure Cloud Block Store now offers block datastore support for Azure VMware Solution workloads. Read on to learn more. >>
Workloads Google Cloud Platform Can Manage
Google Compute Engine is similar to Azure and AWS virtual machine services. Businesses interested in using Google Cloud Platform (GCP) can work with Compute Engine for offloading entire servers to the cloud. Similar to AWS and Azure, businesses working with GCP deploy virtual machines and manage servers, but they don’t need to absorb costs for hardware or housing the equipment.
Businesses working with microservices, containerization, and Kubernetes orchestration can use GCP to lower costs. Containerization is a common architecture for software development where applications are deployed in containers that interact with each other. Kubernetes deploys containers and manages them automatically, and the technology works well with GCP.
Serverless is also available from GCP. Businesses can migrate their applications to GCP without management of servers or virtual machines. Business applications running in a serverless environment still run in the same way as normally to users, but the backend processes do not need any administrative management such as patching and operating system updates. The cloud provider handles all security and server management, so business administrators can focus on other responsibilities.
Free and Open Source Cloud Vendors
Although cloud providers handle much of the overhead for hardware and infrastructure, businesses still need tools to manage resources. Orchestration, monitoring, and infrastructure management for specific applications are still necessary. Several free and open source cloud vendors give administrators ways to manage cloud resources.
A few examples of open source vendors include:
- OpenStack: Manage barebones servers, virtual machines, and containers.
- Kubernetes: Orchestration for containerized development and application execution.
- CloudStack: Developed by Apache, CloudStack helps administrators deploy infrastructure as a service (IaaS), virtual machines, and account management.
Conclusion
Every business has workloads, and these workloads will determine server resources to handle user productivity and customer processes. Offloading workloads to the cloud lowers costs, eliminates overhead for administrators, and provides availability of applications to remote employees. Before migrating to the cloud, make sure you create a placement strategy for a smooth migration.