A Multi-Cloud World Presents Challenges and Opportunities for Big Data

Like it or not, multi-cloud is the new normal —whether it’s the result of a deliberate strategy or Shadow IT.

That means every business needs a plan to manage multiple clouds in a uniform way. It’s about more than just maintaining a view of resource utilization. Left unchecked, multi-cloud sprawl can devalue one of your most precious assets: your data.

Once you open the floodgates by allowing stakeholders to put data workloads on the cloud, that data becomes scattered across various platforms, due to the ease and familiarity of cloud provisioning. “Silos within data centers were bad enough,” says Rob Smoot, VP of product marketing at VMware. Now businesses have to contend with silos across different clouds. Certain data might be accessible by some applications, but not others, depending on where they’re hosted.

The risk of multi-cloud data fragmentation is especially problematic in today’s IT climate. First of all, it’s becoming an increasingly common challenge. With cloud security concerns subsiding, 80 percent of enterprises now plan to increase data management in the public cloud over the next year, according to a new study by Forrester Research, commissioned by Rackspace.

Meanwhile, big data is one of the fastest growing areas in cloud computing. Business stakeholders increasingly expect IT to harness big data to help them understand their customers’ preferences and buying habits. But when business intelligence applications, for example, can’t access all of the relevant data stores, there will be gaps in the intelligence that could lead stakeholders to make poor decisions.

The aforementioned Forrester study suggests that this issue is already a major blocker for big data initiatives: when asked to identify the top five barriers preventing them from moving data and analytics to an off-premises or public cloud platform, 65 percent of IT leaders chose “data integration becomes more complex in the public cloud” — behind only security and compliance challenges.

You need a big data strategy and supporting architecture to address the challenges of sprawling data — especially in this era of multi- and hybrid cloud environments. Data issues are prevalent regardless of the cloud platform (public or private), and big data solutions transcend all clouds (e.g., AWS, Microsoft Azure, Dedicated, OpenStack and VMware).

The same set of technologies, IP and expertise enterprises use to store and process large amounts of data can be applied across all the various cloud platforms in a multi- or hybrid cloud environment. Expertise, planning and supporting initiatives focused on data is critical to ensuring a successful cloud strategy.

That’s why it’s so important to have a defined multi-cloud strategy supported by the right tools, people and processes. “Unified management will be essential for freely moving workloads and data among and between multiple public clouds, as well as an organization’s private clouds,” says Dana Gardner, principal analyst with Interarbor Solutions

Lori MacVittie, principal technical evangelist at F5 Network, agrees: “Systems and solutions capable of providing a single, authoritative source for managing the entire lifecycle of services – from provisioning to ongoing maintenance to end of life – spread across multi-cloud is a must if organizations are going to effectively expand their footprint across cloud environments.”

However, it’s not as simple as buying a cloud management tool and calling it a day. You also need to develop a plan and invest in the right expertise, whether internal or external. This is critical to ensuring successful integrations and making smart decisions about which data stores belong on which platform. As Steve Prentice, senior writer at Cloud Tweaks, puts it, “The management of data, applications and processing held within a multi-cloud environment demands as much attention and care across the C-suite as does a company’s brand.”

When it’s done right, a multi-cloud approach to data hosting can yield significant benefits. These include improved performance, by running each data workload on the best-fit platform, and better disaster mitigation by backing up your data with multiple providers in the event that one has an outage. In addition, 68 percent of companies report that shifting data management to cloud reduced IT costs, according to Forrester.

For more insights into the drivers, benefits and challenges of moving big data workloads into the cloud, read the full Forrester report, “Navigating the Complexity of Big Data Transformation.”

Looking for help defining your big data strategy? Here at Rackspace, we offer proven expertise in this critical area, working side by side with the teams of our customers and partners to help them extract real business value from their data. Our Big Data Accelerator offering provides a workshop approach to sharing best practices and lessons learned across multi- and hybrid cloud environments.

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Rachel Cassidy is the Senior Vice President and General Manager for Professional Services at Rackspace where she oversees the company’s portfolio of professional services in the Americas, serving as our customers’ trusted advisors across all platforms through their cloud transformation. She also is responsible for the Global Service Catalogue defining Rackspace’s professional services strategy and offerings.

Prior to this role, Rachel served as Vice President of Global Solutions and Services at Rackspace, evolving and building professional services, strategic deal desk and technical sales focused on breadth and depth of knowledge defining solutions for our customer.

Before coming to Rackspace, Rachel spent a decade at Red Hat where she built out the pre-sales and professional services organization as Vice President of Global Professional Services. She later worked to create a robust global partner ecosystem, serving as the Vice President of Global Partner and Technical Enablement.

Rachel has been recognized as CRN’s Women of the Channel Power 100 and as a CRN Channel Chief. She holds a BS from Cornell University and an MSM from the Georgia Institute of Technology.

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