Why does IBM Cloud Analytics Engine decouple compute and storage?
IBM Cloud Analytics Engine decouples compute and storage to provide independent scaling and cost management capabilities. This approach allows organizations to scale compute resources (such as CPU and memory) separately from storage resources, optimizing both performance and cost.
Independent Scaling: Decoupling compute and storage means that users can scale the computational power (e.g., number of nodes, processing capabilities) independently of the storage capacity (e.g., data stored in IBM Cloud Object Storage). This is particularly useful in data analytics workloads where the compute requirements may vary significantly over time, but the storage requirements remain relatively constant.
Cost Control: By allowing compute and storage to be managed separately, users have greater flexibility to control costs. For example, users can increase compute power temporarily to handle a peak workload without the need to increase storage costs. Conversely, they can store large datasets without paying for unused compute capacity. This decoupling leads to a more cost-effective and efficient use of cloud resources.
Advantages in Cloud Environments: Decoupling compute and storage aligns with the best practices in modern cloud environments, where elasticity, scalability, and cost efficiency are paramount. It allows organizations to adapt quickly to changing business needs and workload demands, reducing overhead and improving resource utilization.
IBM Cloud Analytics Engine Documentation
IBM Cloud Architect Exam Study Guide
IBM Cloud Object Storage
Alesia
9 days ago