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Demystifying Cloud Trends: Plan Now for Your Future Hybrid or Multi-Cloud Business

By Brian Wood, Director and Cloud Advocate at Teradata

Over the past year, many enterprises dramatically accelerated their digital transformations, as the COVID-19 pandemic compelled businesses to begin or increase their embrace of the cloud. Flexera's 2021 State of the Cloud report notes that 83% of enterprises now spend at least $1.2 million annually on cloud services, up from 74% in 2019. That marked growth obscures a challenge: While enterprise data is inherently portable, migrating data-based analytic applications to the cloud is sometimes easier said than done.

For both business and technological reasons, data analytics can become more complex when data moves from an enterprise's local servers to one or more clouds. To deal with the demands of a hybrid or multi-cloud world, businesses need an analytic platform with the flexibility to manage data anywhere -- from on-premises to public clouds including Amazon Web Services, Google Cloud, and/or Microsoft Azure -- while providing coordinated analytics and avoiding lock-in with any single cloud or architecture.

Regardless of whether you're early in the process or midway through a cloud migration, your enterprise should have a comprehensive cloud strategy mapped back to your overarching business goals. Due diligence is the first and most critical step. You must take a holistic look at your enterprise's data needs so you can ensure that whichever cloud option you ultimately choose will have the right combination of pricing and capabilities for your current demands, yet scale with future changes.

Choose Your Cloud Strategy and Partner(s)

Many large enterprises are looking to migrate data-rich analytic applications to the cloud, reaping the benefits of scale and flexibility. But choosing the right cloud partner or partners isn't easy.

It's important to think pragmatically about your current and longer-term business needs before moving applications and assets to the cloud. Large enterprises cannot move everything to the cloud overnight, so thoughtfully identifying which data and workloads need to move in which order will ultimately save you time and money. For each analytic workload, you should consider these factors:

  • How many queries will be requested?
  • What will the response time distribution be?
  • How much processing will be performed?
  • How much I/O will be needed?

Collecting this information from your on-premises system will enable you to determine whether a cloud platform will be able to meet your performance requirements, plus the cost for doing so for each workload. You'll need to consider daily, monthly, and seasonal workload activity patterns to determine whether public cloud services' flexible pricing models will enable you to achieve cost savings. If the cloud can't affordably deliver the necessary resources to meet your goals, the workload may need to stay on-premises.

Once you have settled on a cloud strategy, it's time to choose a cloud partner, bearing in mind that hyperscalers aren't all interchangeable. Technologies vary between cloud database services, including different architectures, processing nodes, storage configurations, query optimizers, and indexing systems. Moreover, running the same on-premises query on various cloud platforms will yield different performance and resource consumption results.

You will also need to consider factors salient to your industry, as well as your current and future business needs. As just one example, retailers will want to know each cloud provider's speed and cost parameters, as they may frequently scale cloud services up and down to accommodate seasonal  or promotional changes.

Hyperscalers strategically differentiate their offerings to entice specific business segments. In the near term, your company's best hyperscaler choice(s) will deliver enough performance to meet your business requirements without unnecessary costs, but over time, your calculations should anticipate growth in both the quantity of managed data and the number of users accessing it.

Demystifying the Multi-Cloud Approach

Multi-cloud approaches are appealing, as they promise the flexibility of distributed cloud assets and applications across several cloud hosting environments, avoidance of vendor lock-in, minimized downtime, and improved business resiliency. But multiple clouds can also present multiple challenges, including:

  • Data Siloing: Siloing your data across three hyperscalers might avoid vendor lock-in, but managing it can be complicated. This problem is solved by Teradata Vantage, a multi-cloud-ready data analytics platform that orchestrates AWS, Azure, and/or Google Cloud data into a single source of truth for enterprises.
  • Resource Optimization: In the modern era, any robust enterprise data strategy demands system-level consideration of how both data and workloads may dynamically move between on-premises and one or more cloud environments. Ideally, your solution will be architected to optimize resource allocation, meeting shifting workload expectations at the lowest cost.
  • Cost: Clouds can introduce expenses that may be hidden and certainly don't apply to on-premises environments, which create budget and cost control challenges that can differ between data warehouse providers. Make sure you have flexible pricing models - blended- or consumption-based - to prevent costs from spiraling as workloads move across multiple cloud environments.

Using Data as an Asset

Whether you opt for a single cloud, multi-cloud, or hybrid cloud strategy, your objective is putting your data to work, which means a data analytics platform will be critical. Unfortunately, it's not easy to choose between analytics vendors, so you'll want to start by asking yourself the following two questions: How do you query data  in the most efficient, scalable, and cost-effective way? And what is the best method to make the most of your data so that it actually drives transformation of your business? The answers will help you select the right platform for your current and future needs.

To future-proof your business, regardless of your scale and industry, you should be strategically orchestrating cloud data to ensure that you're maximizing analytic performance at scale. If you haven't already begun the journey, now is the time when you should be asking tough questions and fleshing out your strategy, as thoughtful choices today will help you get the most from your data in the cloud for years to come.

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ABOUT THE AUTHOR

Brian-Wood 

Brian Wood is director of cloud marketing at Teradata. He has over 15 years' experience leading all areas of technology marketing in cloud, wireless, IT, software, and data analytics. He earned an MS in Engineering Management from Stanford, a BS in Electrical Engineering from Cornell, and served as an F-14 Radar Intercept Officer in the US Navy.

Published Thursday, June 03, 2021 7:30 AM by David Marshall
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