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The customers I speak with these days are typically dealing with two distinct yet related challenges. First, they’re having to store, manage and make sense of more data than ever before. Second, they have more options than ever before to do this.
With applications and their associated data now residing in multiple locations—from customers’ on-premises data centers to edge locations and hyperscale public clouds such as Microsoft Azure, Amazon Web Services, or Google Cloud Platform. This means customers are rapidly adopting multicloud strategies, which can deliver significant benefits around flexibility and agility. But they can also create new data management challenges.
Successfully implementing your own cost-optimized and easy-to-manage multicloud data management strategy comes down to five critical steps.
1. Have a Plan from the Outset
Many organizations lack a well-defined way to manage their data across heterogeneous environments. Some may even take a one-size-fits-all approach, starting with a single cloud and applying that same methodology enterprise-wide. The risks of this shortcut are limited collaboration, governance concerns and integration challenges.
Becoming a cloud-driven organization doesn’t end once you’ve amassed all the best cloud environments. It’s a journey, not an end-state. A clear strategy is absolutely key for adoption and evolution of your cloud environments. Consider interoperability and flexibility, which will help you be more strategic with resources and ultimately lead to better multicloud ROI.
2. Define Your Master Data Management Strategy
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In a multicloud environment, the complexity of data management can escalate exponentially. Without a clear plan, organizations often duplicate data, which can lead to waste and overspend. A data management strategy can consolidate and simplify data and workload portability. This can help inform the way you ingest, process, store and analyze data from multiple locations—on-premises, across multiple clouds, or from a range of endpoints.
A central, unified data architecture can greatly reduce data management complexities. Centralized storage management will ideally include an operating environment that works seamlessly on-premises and in cloud environments.
3. Opt for Solutions that Run Seamlessly Across Hybrid and Multicloud Environments
The ability to migrate data and applications between data domains is essential. However, on-premises and cloud environments are very different and don’t always speak the same language. The same can be said for different cloud environments. The resulting data silos can create management and efficiency challenges that can lead to friction and limited collaboration in a broad range of use cases.
To break down silos and get seamless data mobility, your operating environment should have a software defined storage solution that enables you to create a common infrastructure with a unified data plane. Non-negotiables include consistent APIs and an efficiency guarantee in writing depending on workload.
4. Determine Your Approach to Controlling Waste and Cost
Cost efficiency remains a top reason IT executives stay on-prem. Data repatriation to on-premises is common and regress charges are a major pain point for any cloud deployment. This challenge grows as cloud use increases.
Don’t let waste and overspend eclipse the tangible benefits of going multicloud. Ensure that your operating environment has best-in-class storage efficiency, thin provisioning, C and data compression. Leverage advanced analytics and AI-powered monitoring where possible to get better visibility into your clouds—especially as you adopt more services.
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An excellent way to augment efforts to reduce bloat: opt for storage as a service to remove the need to forecast and overprovision storage and only pay for what you use.
5. Consider Compliance and Data Sovereignty Requirements
Using more than one cloud for data and analytics can make data management, governance and integration even trickier. This is often driven by corporate compliance requirements, which are also sometimes government-mandated.
For instance, if you’re with a global company or in the process of expansion, you’ll likely require new disaster recovery (DR) zones in multiple regions. These often need to meet strict data governance regulations such as the General Data Protection Regulation (GDPR). This would mean certain data, including customer information or personally identifiable information, cannot leave the region.
Cloud-based backups in multiple high-availability zones (AZs) that reside on different tectonic plates and flood zones in the event of a disaster can help to solve for this. In terms of multicloud data recovery plans, look for a storage solution with continuous, asynchronous replication to meet your recovery point objectives (RPOs) and recovery time objectives (RTOs) with enough margin.
To fully embrace multicloud and create a strategy to manage this complex new world, don’t start with a single cloud and try to apply the same methodology to the whole enterprise. This can limit ROI and weaken business outcomes. You may risk ending up with a proliferation of silos and an opaque view of data assets across the organization. By embracing the multicloud world order with a plan, you’ll increase opportunities for data synergies and cost optimization without limiting accessibility or creating silos.
Once you’ve fleshed out your multicloud strategy, make sure you have the right solutions to support a seamless data mobility, resilience and a consistent experience—no matter where your data lives. That’s the secret to being able to gain true agility and elasticity across complex cloud environments—and the competitive advantage from your organization’s most valuable asset: data.
About the author: Dan Kogan is VP, Product Management within Pure Storage’s FlashArray Business Unit, focused on growing FlashArray into net new customers and markets as well FlashArray’s cloud and as-a-service products, including the Cloud Block Store. Prior to Pure, Dan led Global Product & Solutions Marketing at Veeam, and previously held senior roles at Azuqua, Tableau and Microsoft as well.
Related Items:
Understanding Your Options for Multi- and Hybrid-Cloud Data Management
Tackling Data Governance in a Multi-Cloud DW World
2021: Cloudy with a (Very Good) Chance of AI and Analytics
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