A Strategy for Taming the Multi-Cloud Goliath

It would not be an exaggeration to say a tsunami of Cloud Adoption has taken the industry by storm. With the pandemic further accelerating its pace, businesses are yet to come to terms with these rapid changes. What should today’s businesses do to ride this crest? Let’s explore some options.

Data Management and Governance Strategy: “Data is the New Oil,” but handle it with care as it can catch fire!  As a primary step before embarking on a cloud journey establish a sound data governance and management strategy. It should cover the basics such as data elements that are essential to the business, owning applications of such data, a guideline to reconcile conflicts especially when data originates from multiple data sources, dissemination methodology, security and compliance framework, toolkits, etc. Never yield to the alluring temptation to capture all possible data. It will result in a data deluge and will quickly spiral out of control. Once a base strategy is established, extend it to include cloud parameters such as preferred regions, storage tire and levels of encryption, authorization and authentication policies, etc. A disaster recovery plan with well documented drill frequency between hybrid clouds will be icing on the cake

Training Strategy: An oft-rumored fallacy on cloud adoption is the imperative need to double up on resources for maintaining the legacy and to migrate to cloud. It’s not factually true, that with a customized training plan, a transparent communication and execution framework you can embark on cloud journey, not only transforming the systems but also making your on-prem team be the best proponents of the cloud move. Spotify’s experience of migrating a system supporting 170 million user base to the cloud is a strong vindication of this fact. Let’s face it, your applications were not built overnight, it got hardened over multiple deployment spread over years. No one understands it better than your in-house SMEs. So, engaging a vendor to support the cloud move is just like involving “Packers and movers.” Once the job is completed, the load of maintenance, new build and upgrade shifts back to your team. So, make “Learning and Development” as an indispensable ingredient to your cloud recipe. Training should start as early as you have firmed up on the choices of primary and secondary cloud. A training plan, besides covering the basics of the chosen cloud, must include the shortlisted tool kits and provide a sandbox for practice and assignments

Time to Market: Once a team is assembled, it will be tempting to attempt a Big Bang “Lift and Shift” approach. While this looks convenient it’s equally risky, not merely due to the high cost of failure but also due to the conflicting business priorities. To explain, at any point in time, there will be multiple large-scale programs in different stages of execution from business and regulatory perspectives. Such programs cannot be abruptly paused. Cloud strategy should factor-in this shifting architectural and organizational goal posts. Besides embracing an easier lift and shift means you are not maximizing on the potential of cloud, which is as good as driving on the slowest gear in the fastest lane. So, the best bet will be an incremental approach backed up by the “Value vs Risk” grid.

Budget: Business class costs more than economy but it comes with its own set of convenience and comfort. Similarly, a multi cloud approach will cost you more, but it brings you comfort of an airtight plan for business continuity (remember the infamous Netflix outage in 2012 during the peak holiday season). It insulates from the fear of vendor lock in and adds the flexibility of choosing tools from multiple marketplaces, etc. In addition, you can further cut down costs if your team does a solid homework on predicting type of resources and their durations. Negotiating on porting your on-prem licenses can save additional costs. In essence, the greater the clarity, the lower is the cost. So never venture into cloud negotiation without completing a whiteboarding exercise with your architects.

Hidden Costs: Continuing on the costs, multi-cloud has few hidden costs such as data egress, over/under provisioning of resources, unused resources, choice of support tiers, cost of additional DR drills etc. Let’s consider data egress (i.e.) when there are no charges for bringing data into the cloud. There is a cost when it leaves. Conventionally, while estimating annual cloud budget, these charges are ignored. But it haunts us when the actual bill pops up denting your ROI promises to the board. Even the brightest talents in NASA weren’t immune to this trap, with an estimate of $65 million of annual cloud provider charges they were way off the mark by more than 50 percent solely due to data egress. Let’s simplify this concept with an example. Assume your architecture has data is stored in AWS and your machine learning jobs run in GCP. For every model building, Giga bytes of data is transferred from AWS to GCP (Egress -1) and on completion the transformed data is stored back from GCP to AWS (Egress -2). This sample work-packet besides the regular computational and storage cost will incur additional egress charges. With cloud you should be aware of such hidden costs and also design your systems to minimize such unplanned spikes.

In conclusion, a multi-cloud approach does bring in its own complexity, training and budgetary constraints. However, with a structured strategy and meticulous execution, the benefits far outweigh the challenges and it’s well worth the effort.


Shammy is an 8x Cloud certified, Distinguished IT Specialist/Architect for Cloud, Data Transformation, and Automation, with 21+ years of experience in providing technical leadership for complex business problems in the IT services industry. Shammy is a well-seasoned, business-driven, solution-oriented, Cloud, Automation Techno-Business Leader and Executive IT Architect who has led many large client engagements and provide solutions on various technology platforms, such as Azure, AWS, Google Cloud Platform with legacy system integration with Windows, Solaris, Linux and converged systems platforms.