Home > Storage > PowerFlex > White Papers > Dell APEX Block Storage for Azure: IBM Db2 Database Deployment Best Practices > Executive summary
In the current global environment, many organizations choose public cloud deployments as part of their multicloud strategy to expand their business goals. However, running certain mission-critical workloads have not been considered feasible candidates for the public cloud due to agility, faster application deployment time and performance. As a result, expanding into the public cloud becomes even more challenging with inconsistent throughput, capacity charges associated with application requirements, and migrating workloads. In addition, new challenges and competencies are required in the public clouds to monitor performance and capacity utilization across storage resources.
Running Db2 instances on Microsoft Azure is simple and it is not required to tie them to specific servers or hardware configuration. With Dell APEX Block Storage for Microsoft Azure provides block storage for Db2 database storage.
This whitepaper provides best practices for deploying the IBM Db2 database on the Dell APEX Block Storage as the underlying software-defined storage layer hosted on Azure VM instances.
Dell APEX Block Storage for Microsoft Azure enables companies to run diverse workloads in the public cloud without the above-mentioned limitations and risks. Flexible deployment options and enterprise-grade resiliency offers a simplified public cloud experience that is powered by innovative storage solutions from Dell Technologies. The scale-out software architecture for Dell APEX Block Storage for Microsoft Azure enables exceptionally high performance by aggregating storage across multiple instances in a cluster. Dell APEX Block Storage for Microsoft Azure can be deployed on managed disks for most workloads or on instances with locally attached NVMe SSDs for performance optimized use cases. Configuration, deployment, and management is performed using built-in automation and intelligence that optimizes the instance types needed to support the capacity and performance requirements of workloads.