By Ranjith Ramachandran, enterprise solutions architect at Wavicle Data Solutions, shortlisted for Best Cloud Consultancy or MSP at 2021-2022 Cloud Awards

Organizations increasingly manage data across several types of cloud platforms, often from more than one provider. This multicloud environment might include different software as a service (SaaS) offerings for email, customer experience management, and finance; infrastructure as a service (IaaS) for overall IT environment support, such as storing data; and platform as a service (PaaS) to facilitate application development.

Analyst firm Gartner says more than 80% of organizations have a muticloud environment; while Hosting Tribunal reports that enterprises using a cloud service are each doing so across an average of five different cloud platforms.

It turns out the single cloud environment was a stepping stone to multicloud, where best-in-class technologies and services are more reliable and deliver more flexibility, scalability, and efficiency.

But if yours is like most organizations, this multicloud environment sprouted from a combination of careful consideration and happenstance. Perhaps the multicloud environment grew out of acquisitions, individual business unit decisions, or geographic needs.

And if that’s the case, you may be struggling with the challenges of multicloud more than you are reaping the rewards. For example, it can be more challenging to integrate, transform, access, and secure data across multiple cloud environments.

Whatever your situation is, it’s not too late to step back and take a more strategic approach to your multicloud situation. By aligning your cloud strategy with business and data strategy, you have a better chance of maximizing the value and minimizing the complexities of multicloud.

Four pillars of your multicloud strategy

Strategy matters because it helps determine which workloads live in each cloud and which providers are best for specific needs. A strategy allows you to optimize the cost and performance of different cloud providers; get faster access to data; and better address the complexity of using multiple providers, such as integrations, architectures, and data structures. Additionally, a strategy helps ensure that your team has the necessary skills to work with different tools and provides mechanisms for better control and visibility.

Organizations using multicloud should unite business and technical strategies into a cohesive method around four key areas: managing people, managing data, managing technologies, and security.

  1. People: leadership, collaboration, and skills

When developing a multicloud strategy, be sure to assemble the right teams, from executive oversight and governance to skilled technologists. For example, gather input and involvement from key stakeholders including the CIO, CTO, other C-level business leaders, top cyber security executives, governance committees, and executives from finance, legal, and risk management. Also include leaders in data science and analytics. Also, in a multicloud environment, you need a team that is experienced in managing the various cloud environments, architectures, services, and security protocols. Expect to invest in training requirements, pay increases, and additional headcount to satisfy the skill requirements of a multicloud environment.

Strong collaboration among these teams is critical for a successful multicloud strategy with a cohesive connection to data and analytics initiatives. Establishing review boards and centers of excellence can go a long way to ensuring continued success with multicloud.

  1. Data: master data for single version of truth

As you build your multicloud strategy, you need a clear understanding of what types of data will achieve business objectives and how you’ll leverage cloud platforms to manage and deliver that data.

The growing volumes of raw data spread across a multicloud environment creates challenges such as multiple data formats and siloed data that are more difficult to manage. This requires an architecture that can bring together data, no matter where it’s from, and make it accessible and usable to the right people and groups.

A master data management (MDM) solution can help ensure consistency and uniform classification of data across domains such as customer, product, employee, and supplier. MDM combines tools, technologies, governance, and the overall philosophy toward data and helps protect data accuracy and integrity of your single version of the truth.

  1. Technology: best-in-class technologies for your use cases

Once you’ve identified use cases, strategies, and data to be migrated, you’ll evaluate various technologies, eliminating those that aren’t ideal for a mutlicloud environment. Organizations will need to consider new vendors in many cases, including cloud native and open source software that offers speed, flexibility, integrated management, better control, and more compatibility with other tools. Storage and backup methods also must be considered.

Different cloud products are ideal for different workloads. Data and analytics, marketing, advertising, customer transactions, and cold storage like archival data may require different clouds. For example, developers will use sandboxes to test and iterate new ideas. At the same time, data scientists will want fast access to raw data that can be explored and experimented with to determine what value or insights it holds.

A good example of the need for cloud-native technology is extract, transform, and load (ETL) technology. As data volumes and types continue to increase, and data is spread across multiple cloud platforms, legacy ETL solutions can be difficult to convert for the cloud and often struggle with performance issues, resulting in delayed delivery of important data and analytics.

Cloud-native, or serverless, ETL solutions can offer lower cost and maintenance requirements, increased scalability, and easier integration with other cloud services and applications, ultimately allowing more users to interact with your data.

       4. Security: Balancing internal and external responsibilities

With the growing risk and increasing sophistication of threats, it’s critical to pay thorough attention to security protocols. Data security is often more challenging in a multicloud environment and must be shared between cloud providers and the customer (you).

Each of the cloud vendors has different cloud-native cybersecurity solutions. Be sure to examine different providers’ security policies and review Service Level Agreements (SLAs) to ensure overarching security requirements are addressed. This includes compliance requirements, the need for third-party add-ons to protect data, and what kind of data loss protection is offered, particularly since transferring data can introduce errors.

Multicloud adoption adds extra layers of management complexity because there are many different components, architectures, platforms, and applications to consider. This is compounded when entities within an organization add cloud services in an ad hoc manner. Policies should address the overarching security requirements of the organization and make it clear that this applies to any “shadow IT” endeavors.

Onward with multicloud

As you develop your multicloud strategy, keep in mind the dynamic nature of data, technology, and business. As your organization’s needs change, be prepared for the strategy to evolve with them. Expect to revisit the strategy often to make sure it’s serving the needs of the business and digital transformation initiatives as they move forward.

About the Author: Ranjith Ramachandran

Ranjith Ramachandran, an enterprise solutions architect at Wavicle Data Solutions, has nearly two decades of experience working with complex systems, data analytics, and various cloud architectures. Ranjith is an expert in automation and integration solutions in support of customer relationship management (CRM) and other business functions. He contributes to the data, analytics, cloud, AI, and ML communities through mentoring, publications, and webinars. Ranjith holds a Master of Data Science degree and completed the Artificial Intelligence Business Strategies and Applications executive immersion program with UC Berkeley.