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Insights into a multi-cloud strategy with Google Cloud

  • 28 June 2021 / By Mark Ardito
  • Cloud Modernization Digital Transformation

Analysts and business experts report that companies in all industry sectors are using multiple cloud environments to achieve IT goals. The numbers vary, but all agree at least 80% of enterprises have or are planning to have some form of multi-cloud operation in the near term.

Having a multi-cloud operation is not the same as having a multi-cloud strategy. While many companies have numerous cloud environments, they have taken a tactical approach to this IT area. For example, different departments may use different clouds, each meeting the needs of the users. Then there can be pockets of shadow IT, off the official IT radar and operating its own cloud.

We’ve had many conversations with technology leaders from a range of industries about cloud computing, and multi-cloud in particular. Wherever you are in your own cloud adoption journey, the insights and observations that were shared in these conversations can help you make informed decisions about your cloud strategy.

Moving to the (multi) cloud

Your multi-cloud strategy depends on where you are today relative to cloud computing. A useful reference is the Cloud Adoption Maturity. This can help you pinpoint where you are in the cloud adoption journey and understand what steps are needed to get to the transformative stage, where you are fully cloud-native.

Anticipating organizational change

As you put your multi-cloud strategy into practice, your organization will change. Count on it. Here’s a high level view of how team operation changes at each stage in the maturity model:

  1. Initial: Teams operate with a traditional data center strategy.

  2. Opportunistic: Teams start to lift & shift, trying to just displace workloads without refactoring the way that they really work. They are not really cloud scalable yet, but as they progress, teams become smaller and more organized.

  3. Organized: Here we really start to see orchestration. Organizations start to use containerized systems, becoming more skilled at that instead of using primitives.

  4. Enterprise: As businesses move toward microservices, there is a change in the way the organization operates. There are now a lot of various little teams, each responsible for specific decoupled and scalable microservices that are going to the cloud.

  5. Cloud-native: This is the point of real transformative effect, where small teams that are on top of everything can add significant value to the business.

Moving up the maturity model, you will find that you can achieve more in smaller teams than before. Moving to microservices requires a shift in thinking for all team members. Anticipate these types of changes and prepare your staff for them, through regular communication and, if necessary, formal training. This will prepare them to be members of teams that are agile, transformative and committed to continuous improvement.


Cloud adoption maturity model and evolution

When prioritizing workloads to move to the cloud, find that sweet spot of that application that's going to deliver manifestly better business value with quantifiable risk and offer the best immediate delivery of value to your stakeholders — this will give you the best experience overall.

Eliot Danner - Director of Customer Engineering, Google Cloud

Going from “storage to story

Even if your company is well into its cloud adoption journey, it can be challenging to move past the batch process and really “liberate” your data to drive growth through improved competitiveness and operational agility. Think of it as a “central nervous system” for your organization, that allows it to unconsciously ‘stream’ data rather than consciously make batch calls. This paradigm shift gives applications the data they need when they need it.

Solutions to consider

Our conversations with tech leaders spotlighted some GCP solutions that are worth considering for inclusion in a multi-cloud strategy:

  • Google Cloud provides flexibility, enabling a decentralized, multi-cloud approach. Managed services can pull that all together by allowing your team to focus on driving the business rather than managing infrastructure.
  • Confluent Kafka acts as an organization’s “Central Nervous System,” allowing it to unconsciously ‘stream’ data rather than consciously make batch calls. This paradigm shift gives applications the data they need when they need it. As organizations grow, their data and tech landscape become exponentially complex; real-time data streaming helps cut through that complexity to deliver on the needs of the business.
  • To monetize their data and gather insights, organizations need to be able to stream that data from anywhere at any time. That’s where the Data Mesh Architecture concept comes in. Instead of being in a central lake, your organization’s data can be in multiple places, such as Google Cloud Platform’s BigQuery, or on-prem with Teradata. The Data Mesh Architecture takes multi-cloud to the next level — stretching your data wherever you need it to be, even to the edge


Multi-cloud strategy is the most strategic way to think about your cloud environment. It is the direction being taken by the majority of enterprises, and it is the foundation for future technology trends. Implementation of a multi-cloud environment has produced significant return on investment and run time and positions the company for competitive advantage as all business sectors become increasingly data- and software-driven.

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