Managing the cost and complexity of cloud infrastructure will be the #1 task for enterprise IT in 2023. Cloud spending will continue, albeit at a perhaps more measured pace in times of economic uncertainty. What will be paramount is having the best possible cloud asset data to make sound decisions about where to move data and how to manage it for profitability, performance, and analytics projects. Data insights will also be important for migration planning, expense management (FinOps), and to meet governance requirements for managing unstructured data. These are the trends we’re following for data management in the cloud that will give CIOs clear guidance to maximize the value of data and minimize waste in the cloud.
Multicloud strategies will slow down or revert to single cloud preferences unless companies can manage cost and complexity
Many IT organizations today want the flexibility of using multiple cloud providers to balance cost needs and different workload requirements, as well as disaster recovery tactics such as replicating data to another cloud. . Yet managing multiple clouds adds management and skill costs to ensure ROI. IT teams will need full visibility into all data assets, metrics to inform decisions, and the ability to move data between platforms and environments without excessive costs (such as moving out of the cloud) and without security risks. This will require closer alignment and integration between storage/infrastructure and security/governance/compliance teams and tools and a storage-agnostic data management strategy.
Automated workflow solutions are emerging to support new cloud data services
Organizations today are more decentralized than ever, with a remote/hybrid distributed workforce as the norm and cloud-based applications and tools dominating the way we work. To meet the demands of business data services, IT will need to become a managed service provider to be agile and meet the demands of business stakeholders. New unstructured data workflow automation capabilities will support a variety of use cases, from governance and compliance to cost savings and chargeback to feeding the right data to data lakes and other analysis services. Tools that empower authorized users and departments to create automated, policy-based workflows managed and executed by IT will save time finding and moving data to the optimal location. For example, a legal data analyst can create a workflow to find all data related to a disposal project, run an external function to identify and label PII data, then move sensitive data to a cloud storage bucket locked by object.
Cloud Data Migration Difficulties Highlight the Resurgence of Enterprise IT Silos
Large-scale data migrations to the cloud, especially petabytes of file data that was historically stored on expensive hardware platforms, will continue to be a challenge for many businesses. The culprit often lies in the network. Migration issues, such as slow transmissions, data loss, and errors, not only derail timelines and increase project costs, but can also blunt the appetite for growing cloud spending. When it comes to file data migrations to the cloud, the complexity of network configurations (routing and security) has been underestimated. There are often technical bottlenecks that were not investigated before the migration. Storage and networking teams are often not on the same page, resulting in the perpetuation of IT silos, blame, and missed deadlines. Spending more time on initial network assessment and testing is critical to avoiding the complexities of data migration. IT leaders will need to thwart siled trends and instead create processes that allow networking, storage, and security teams to work closely together with the common goal of moving data workloads from large files to securely and quickly to the cloud without errors, data loss or risk. Increasingly, IT generalists are moving into storage roles, and these employees will need training and guidance to skillfully navigate the organization to support decision-making points along the storage journey. migration to the cloud.
Cloud migration plans will depend on specific FinOps practices
Cloud overspending is rampant. A third (32%) of cloud spend is wasted, up from 30% last year, according to Flexera. Cloud projects are also on average 13% over budget. Accordingly, FinOps, a cloud-based financial management discipline that strives to maximize business value by helping engineering, finance, technology, and business teams collaborate on data-driven spending decisions , will become common practice. IT managers will ensure that data migration initiatives to the cloud incorporate FinOps analysis. This will involve collecting metrics on data usage and age to determine data value, costs per TB for on-premises storage and target storage tiers, on-premises versus cloud management costs, target storage performance and availability metrics, and more.
Data storage trend monitoring expands to meet governance requirements
Customers want to receive more alerts from their unstructured data management solutions to stay informed about capacity thresholds, anomalies, threats and other unusual activity, according to nearly 40% of respondents to Komprise 2022 State of Unstructured Data Management investigation. Monitoring and observability of data and storage assets are becoming central to IT strategy as data volumes grow exponentially each year, along with data silos in hybrid cloud and edge environments. Enterprise data storage and security teams will also forge closer alignment and leverage new governance features in unstructured data management technologies.
Darren Cunningham is Vice President of Marketing at Komprise.
