How to Navigate the Complexities of a Multi-Cloud World

Jun 03, 2021 |
Mamun Reza

Data Engineering, Product Marketing

navigating the complexities of a multi-cloud world

Multi-cloud is the default state of business technology today, either by accident or design. As cloud adoption rapidly proliferates, it is becoming clear for organizations that a simple “one cloud fits all” approach does not meet their business needs. Organizations are using a variety of IaaS, PaaS, and SaaS products to deliver cost-effective and flexible applications required for agile and innovative operations. At the same time, they are also likely to be running private cloud or/and on-premises infrastructures. According the Flexera 2021 State of the Cloud Report,  92% of enterprises have a multi-cloud strategy and 82% have a hybrid cloud strategy. From ensuring uptime and robustness to shifting workloads to capturing maximum efficiency, cost savings or avoiding vendor lock-in, there are a lot of good reasons for running your infrastructure across multiple clouds.

The multi-cloud world has evolved well beyond the initial promise of commodity cloud storage and compute power and enables a host of differentiated services. A multi-cloud ecosystem helps you achieve more by letting you move workloads between clouds to get the best of each cloud service without disruption.

From the perspective of data management specifically, multi-cloud strategies allow for adopting best-of-breed features and differentiators among the major cloud platforms. However, organizations face critical challenges in realizing the full potential of cloud analytics in a complex, multi-cloud world.

Challenges in a highly distributed multi-cloud world

Moving to the cloud doesn’t solve the data management challenges of digital transformation, it amplifies them – exponentially. With exploding data volumes and new data types cropping up all the time, your company’s data is sprawled across on-premises systems as well as public and private clouds. This creates more data silos, making it increasingly difficult to connect, transform, manage, and sync all that disparate data, faster, to make it useful for your enterprise. With most organizations today working with multiple cloud service providers, they are facing common challenges around accessibility, integration, visibility, security, and data governance.

  • Integration – As applications are spread across multiple clouds, the new architecture needs to ensure that the underlying data is interoperable and moves seamlessly across the clouds, irrespective of where it resides (on-premise, public or private cloud). This requires cloud data integration with cloud-native ELT and ETL. Data storage mechanisms and the database, as well as data lake choices, can play a pivotal role in ensuring portability of the data.
  • Security – In a multi-cloud environment, enterprises find it challenging to monitor and secure all the different systems since there is no single point of control to monitor security and compliance. As foundational architectural services are created for data backup, discovery, protection, replication and restoration across multiple cloud environments, capabilities should also be developed for cloning data, masking certain elements, and securely storing replicated data. This can become a great enabler in creating a truly agile organization that delivers more applications and features seamlessly and securely.
  • Accessibility – As data becomes fragmented, it adds an additional risk to environments by creating data silos that are harder to manage and sustain. Architectures must be established that can ensure data is available, regardless of where it resides, or the complexity involved in retrieving that data and its lineage – understanding where your data is coming from and how it gets transformed at every step of the data pipeline.
  • Visibility – As organizations start deploying multiple clouds, they are challenged by the lack of visibility across divisions or regions. Additionally, in the absence of a central console, organizations struggle to gain information or knowledge about cost, configuration, usage, and performance in a multi-cloud environment.
  • Governance/Compliance – Highly scaled, shared, and automated IT platforms, such as the cloud can hide the geographic location of data — both from the customer and the service provider. This can give rise to regulatory violations.

Furthermore, in larger data-driven organizations, there are often complex requirements for handling data. For example, there will sometimes be a need to deliver different subsets of the customer data to different teams:

  • in different applications
  • In different formats
  • all with different services level requirements or specifications

And now imagine if the data of these different teams are located in different clouds. You can clearly realise the kind of complexity such a situation can gives rise to. In the new multi-cloud world, it is imperative for organizations to account for these considerations and include comprehensive data management as one of the critical foundational blocks in their architectures.

Avoid the data management mistakes of the past

  • Manual approaches, such as hand coding, are expensive to develop and difficult to maintain, even in the new world of cloud. While hand coding may seem like a plausible solution during a project’s initial stages, it has several drawbacks that make it unsuitable for modern cloud data management. Hand coding requires skilled developers and lacks reusability. Changes in technology, platform, or processing engine require reengineering and recoding—costly and time-consuming processes that hamper agility and innovation.
  • Using multiple point products that are not integrated increases cost and complexity. It can take an organization up to 10 different point products to achieve true end-to-end cloud data management. Stitching together these disjointed products means that organizations are consigned to constant do-it-yourself integration, changing roadmaps, project overruns, and inconsistent data governance and quality.
  • Limited solutions from platform-as-a-service (PaaS) or infrastructure-as-a-service (IaaS)vendors—although designed for the cloud—combine many of these downsides. They typically offer basic data integration and ingestion, are reliant on hand-coded development, and provide capabilities that extend only as far as their own platforms          

How Informatica can empower you to meet the demands of data-driven transformation in hybrid, multi-cloud ecosystem

Take advantage of one of the most exciting innovations in Informatica’s history – the industry’s first Intelligent Data Management Cloud (IDMC), designed to help businesses innovate with their data on any platform, any cloud, multi-cloud, and multi-hybrid. This complete cloud-native and AI-powered platform is the critical missing piece for businesses to move from simply modernizing to truly transforming for a digital world. IDMC is the industry’s first and only cloud focused solely on data management. A true multi-cloud environment should provide a way to seamlessly manage, share, and collaborate with data. A multi-cloud data management platform can help organizations realize the benefits of working with multiple clouds without the complexity and risk.

Intelligent Data Management Cloud Graphic

The Intelligent Data Management Cloud is designed to help businesses efficiently handle the complex challenges of dispersed and fragmented data to truly innovate with their data on any platform, any cloud, multi-cloud and multi-hybrid. This is the industry’s first and most comprehensive, cloud-native, AI-powered, end-to-end data management platform.  And with over 200 intelligent cloud services, you can catalog, ingest, integrate, prep, cleanse, master, and share all of your data, wherever it is, process it in any way you want, ensure it is trusted and democratized on a foundation of governance, while delivering intelligent insights with a 360-degree view of your business. 


Informatica Intelligent Data Management Cloud and CLAIRE

With Informatica’s Intelligent Data Management Cloud, all these services are available to you natively on a cloud-first, microservices-based, API-driven platform that’s both elastic and serverless. CLAIRE, our AI technology, is embedded in every service. We can bring data from any source, of any type, to serve any user anywhere – whether he or she is a business or technical user.

Watch this video to learn more on how Informatica allows you to have self-service access to both reliable data and real-time analytics, across any cloud, anywhere, and at any scale.