How automated discovery tools can ensure cloud migration success
As more organizations seek the benefits and cost savings of migrating from legacy to cloud infrastructure, it is crucial to accurately determine what, how and when to migrate into the modern environment.
To ensure an effective and successful cloud migration, CIOs and their organizations should conduct an extensive discovery process, aided by automated discovery tools, to determine the right applications for cloud migration and assess the cost and operational considerations of doing so.
Organizations embarking on a major cloud infrastructure migration should complete an initial assessment of migration readiness and develop a high-level business use case.
Once an organization establishes a general understanding of where it stands on its overall cloud journey, an action plan will help determine the gaps so the IT team is ready to migrate workloads at scale. Additionally, a portfolio discovery and analysis exercise is required to create a detailed enterprise-level migration plan and validate its business use case.
This analysis yields detailed knowledge of the legacy environment, a realistic understanding of the interdependencies of applications and workloads in the portfolio, as well as a migration wave plan detailing the sequence and scheduling of the workload migrations. To decide how, when and which workloads or applications to migrate, organizations need a complete and accurate data set of the infrastructure and application interdependencies.
This includes compute, storage, network and application documentation and a complete mapping of the interdependencies between infrastructure, applications and workloads across the entire business environment.
Automated discovery tools can significantly accelerate the cloud migration discovery process, thus reducing the time and effort required. These tools should find and categorize every piece of hardware and software in the legacy environment, preferably with agentless technology. They should also provide a server instance to hardware mapping and a server instance — including related storage and networking — to application mapping for all hardware in the environment.
This highlights all dependencies of each application on the infrastructure, other applications and IT support services like message passing buses, shared databases, VDI and VPN services. In a dynamic IT environment, automated tools can regularly update discovery maps to reflect environment changes. In this case, repeat discovery processes, which are often necessary as workloads shift from on premises to cloud service providers over months of a typical migration, become a rerun of a discovery script instead of a major manual exercise.
Automated data collection usually takes two to four weeks, with initial results available within 48 to72 hours of tool activation. The tool should be able to assimilate upward from infrastructure to applications to services, creating a bottom-up mapping of the infrastructure and its relationship with service-based workloads. An additional benefit is if the tool can start at the top of the server stack and work down to all hardware and software components and services included in the computational stack of the application and workload.
