As any new technology takes hold, our vocabulary inevitably changes. New terms and phrases, or new meanings, take hold, and our vernacular grows and changes. When you talk to technologists about the cloud, the term du jour is Cloud Workload.
Cloud Workload Definition
Talking cloud environment, workload refers to any measurable utilization of cloud services. Cloud computing allows users to access and utilize computing resources, such as processing power, storage, and networking, on-demand over the internet from a managed cloud service provider. The more technical use refers to processor, memory, storage, or network loads. Workload often refers to a “package” of cloud use. The package may be part of an application, a full application, or a set of integrated applications.
Example of a Cloud Workload
Email is a workload; a file sync-and-share service is a workload; a back-end database is a workload; website analytics is a workload. The challenge, of course, is that your business does not think or run on technology components. You have people, processes, systems, and services.
Workloads can vary significantly based on their nature and purpose. Some common examples of cloud workloads include:
- Web Applications: Cloud platforms are commonly used to host web applications, websites, and web services. These applications can range from simple blogs to complex e-commerce platforms.
- Data Storage and Backup: Cloud storage services allow users to store and access data over the internet. These services often provide features like data redundancy and automated backups.
- Big Data Analytics: Cloud computing strategy enables organizations to perform large-scale data analysis and processing, leveraging the scalability of cloud resources to handle vast datasets.
- Machine Learning and Artificial Intelligence: Cloud platforms provide tools and infrastructure to develop and deploy machine learning models, making it easier for developers to integrate AI capabilities into their applications.
- Video and Media Streaming: Cloud-based video and media streaming services enable the distribution of multimedia content to a wide audience over the internet.
- Development and Testing: Cloud environments are frequently used for software development and testing, allowing developers to provision and configure virtual machines and other resources quickly.
- Internet of Things (IoT): Cloud platforms can handle data processing and storage for IoT devices, supporting the massive influx of data generated by interconnected devices.
The main advantages of running workloads in the cloud include flexibility, scalability, cost-efficiency, and reduced management overhead. Cloud providers offer various service models like Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS), or more recently SaaSOps to cater to different workload requirements.
When deploying a cloud workload, considerations include selecting the appropriate cloud service model, provisioning the required resources, ensuring data security, and optimizing performance to achieve the desired outcomes efficiently.
Importance of Managing Cloud Workload in Your Business
When planning your cloud presence, think of workloads in terms of business functions and systems. Yes, email may be a workload. But so maybe your “communication services,” your “customer service” function, or your “analytics services.” By looking at workload in terms of your business, you will be less likely to fragment your cloud and on-premise systems. Building and managing the hybrid environment will be simpler and more effective over time.
To discuss your workloads and which may be best in the cloud, contact us for a free and no obligation consultation.