Data Migration in Hybrid Environments
Data migration (transferring data from one storage platform to another) is an essential IT process used to achieve a technology refresh, data center relocation, or consolidation. Before cloud service prevalence, data migration was a cyclical task that delivered enhanced performance and reliability to critical applications through physical equipment replacement. However, with hybrid cloud (part on-premises, part cloud) architecture deployment increasing, new complexities have arisen, and data migration planning has never been more challenging. Early cloud adopters are now looking to migrate between cloud service providers (CSPs) to reduce costs and risks. In addition, multi-cloud environments became increasingly necessary as IT teams struggled to provide essential services without on-premises access during the Covid-19 pandemic.
Each of these data migration scenarios (on-premises, cloud, hybrid, multi-cloud) presents distinct challenges, which must be mitigated and managed. And as Benjamin Franklin might have said, failure to plan (by not knowing and addressing all the application service interdependencies) is planning to fail.
While verified backups and tested replication address data protection from catastrophic failure, a failed data migration will inevitably lead to increased costs, reduced quality of service, and application availability impacts to the organization. Protecting critical data as a valued organization asset is necessary but not sufficient for successful data migration. Meticulous planning through evaluation of all service dependencies must precede a cloud, hybrid, or multi-cloud migration to ensure continued availability and quality of service. But how do IT leads achieve thorough planning with primary data source and application propagation?
Migration Projects Must Begin with Discovery
Current environment validation (as-operating, not as-designed) is mandatory to identify where the data and supporting assets reside, either on (the physical estate) or in (a CSP). In addition, IT’s migration planning must include assembling a comprehensive project team to ensure that all dependencies, priorities, timelines, and processes are mapped and jointly understood across the group. The critical difference today is needing to know with certainty where and how data is served at the time of migration, and anticipating how it will behave post-migration, wherever it resides.
For on-premises upgrades of Fibre Channel (FC) storage arrays, IT primarily used OEM storage management tools to know the data placement and host connections to that data. Certainty becomes problematic when using TCP network services located on different local physical infrastructure or at a CSP. IT must now manage data across a fluid estate – with essential data on endpoints, data centers, the edge, and the cloud. Comprehensive, current, and automated asset management is a compelling foundation for planning a successful data migration. Perhaps some data sets should be retired or purged before they are migrated or replicated unwittingly to the new target; after all, the fastest data migration is the one that you do not have to do.
Maintaining accurate asset and service metadata reduces data migration costs and risks and ongoing data storage operations costs. When used systematically, asset management and data discovery proactively identify asset problems before they occur during migration.
An automated system can use real-world field reliability and supportability data and resource utilization data to flag assets that should be retired. It also makes it possible to identify opportunities to move high-value business data onto the right-for-purpose platform. If that platform is a CSP, organizations can more accurately plan the operation costs, reduce the need for future migrations, and improve cost transparency for operations.
The challenge to having correct data for data migration planning has been management’s choice to either use scarce IT resources to deploy new business applications or keep accurate estate data to reduce risks and future costs. Now it is possible to do both.
Introducing ParkView Discovery™, an end-to-end automated service that supports successful hybrid data migrations.
Since successful data migration depends upon accurate data and service knowledge, Park Place Technologies have responded with the ParkView Discovery™ managed service to bring automation, intelligence, and field experience to ITAM discovery. IT can automatically capture comprehensive metadata and identify all assets and data services on global networks and at CSPs using the service.
In addition, migration planners can rely on automatic agentless discovery across their hybrid estate to check the types of data and assets to migrate: from the O/S; to networking infrastructure; to virtual machines or containers, to storage and into the data center environmental support infrastructure – in short, if it exists on the network, ParkView Discovery™ will find, capture, and track it. The discovered physical, virtual, and cloud configuration items can also be bidirectionally synchronized to common ITAM CMDBs to operationalize the data in daily IT Service Management processes.
With this level of physical and logical asset metadata, answers to common IT data migration planning questions are available from a single, authoritative source that gives a distinct edge in making data migration projects successful.
- What’s changed in the application ecosystem, and when?
- What data services does this asset rely on to deliver its application services?
- What would the upstream/downstream impact of any changes be to paths or services?
- When was the configuration item updated?