Managing the cost and complexity of cloud infrastructure will be Job No. 1 for enterprise IT in 2023. Cloud spending will continue, although at perhaps a more measured pace during uncertain economic times. What will be paramount is to have the best data possible on cloud assets to make sound decisions on where to move data and how to manage it for cost efficiency, performance, and analytics projects. Data insights will also be important for migration planning, spend management (FinOps), and to meet governance requirements for unstructured data management. These are the trends we're tracking for cloud data management, which will give IT directors precise guidance to maximize data value and minimize cloud waste.
Multicloud strategies will slow down or revert to single-cloud preferences unless enterprises can manage cost and complexity
Many IT organizations today want the flexibility of using more than one cloud provider to balance the needs of costs and different workload requirements, as well as disaster recovery tactics such as replicating data to another cloud. Yet managing multiple clouds adds management and skills costs to ensure ROI. IT teams will need full visibility across all data assets, metrics to inform decisions, and the ability to move data between platforms and environments without excessive costs (such as cloud egress) and security risks. This will require tighter alignment and integration between storage/infrastructure and security/governance/compliance teams and tools and a storage-agnostic data management strategy.
Automated workflow solutions emerge to support new cloud data services
Organizations today are more decentralized than ever, with distributed remote/hybrid workforces the norm and cloud-based apps and tools dominating the way we work. To keep up with data services demands from the business, IT will need to become a managed service provider to be agile and meet the demands of stakeholders across the enterprise. 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 analytics services. Tools that give authorized users and departments the means to create automated, policy-driven workflows, managed and executed by IT, will save time on finding and moving data to the optimal location. For example, a legal data analyst could create a workflow to find all data related to a divestiture project, execute an external function to identify PII data and tag it, and then move the sensitive data to an object-locked cloud storage bucket.
Cloud data migration pains highlight the resurgence of enterprise IT silos
Large-scale data migrations to the cloud, especially petabytes of file data that historically has been stored on expensive hardware platforms, will continue to be problematic for many enterprises. The culprit often lies in the network. Migration issues — such as slow transmissions, data loss, and errors — not only derail timelines and add costs to projects but can sour 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 in the way that haven't been investigated prior to migration. Storage and networking teams are often not on the same page, which causes perpetuation of IT silos, finger pointing, and missed deadlines. It's critical to spend more time in upfront assessment and testing of the network to prevent data migration complexities. IT executives will need to counteract silo tendencies and instead create processes for networking, storage, and security teams to work together closely for the common goal of moving large file data workloads safely and swiftly to the cloud without errors, data loss, or risks. Increasingly, IT generalists are moving into storage roles, and these employees will need training and guidance to deftly navigate the organization to support decision-making points along the cloud migration journey.
Cloud migration projects will depend upon accurate FinOps practices
Overspending in the cloud is rampant. One-third (32%) of cloud spending is wasted, up from 30% last year, according to Flexera. Cloud projects are also on average 13% over budget. As a result, FinOps, a cloud 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 a mainstream practice. IT leaders will ensure that cloud data migration initiatives incorporate a FinOps analysis. This will entail gathering metrics on data usage and age to ascertain data value, per TB costs for on-premises storage and target storage tiers, management costs in on-prem versus cloud, performance and availability metrics of target storage, and more.
Data storage trend monitoring expands to meet governance requirements
Customers are interested in getting more alerts from their unstructured data management solutions to stay informed on capacity thresholds, anomalies, threats, and other unusual activity, according to nearly 40% of respondents to the Komprise 2022 State of Unstructured Data Management survey. Monitoring and observability of data and storage assets are becoming central to IT strategy as data volumes expand exponentially every year along with data silos in hybrid cloud and edge environments. Enterprise data storage and security teams will forge tighter alignment, too, and will rely upon new governance features in unstructured data management technologies.
Darren Cunningham is VP of Marketing at Komprise.