This document gives us the definition of different cloud classifications and focuses on the Multicloud and Hybrid cloud and the organization’s tendency to adapt to the cloud, especially for multi-cloud. This document even refers to the challenges of multi-cloud at the management and technical level and the reasons for them, and in the last part of the document some services are introduced that can help in multi-cloud solutions.

Cloud classifications

This document classifies the cloud in the following pillars. The focus of this document is multi-cloud.

Figure 1: Definitions of different types of clouds

In fact, most enterprise adopters of public cloud services use multiple providers. This is known as multi-cloud computing, a subset of the broader term hybrid-cloud computing (Gartner) [3]

Multi-Cloud e.g., when some resources are on Azure, some on AWS and some on GCP, or some VMs on AWS and using Office 365 of Microsoft, or when you connect several cloud provider deployments with each other via VPN, they are considered as multi-cloud.

Organizations’ tendency for cloud

Almost all organizations have data and workloads, they must be stored and hosted. The organizations have two possibilities either a private data center or using the cloud.

If the organizations decide on an on-premises data center, they have to pay upfront, which requires capital expenditure (CapEx) with much software and hardware maintenance.

But if they decide on the public cloud, they will have only operational expenditure (OpEx), because it’s the model of the public cloud to pay as you go. Therefore, most organizations decided to use the public cloud. Organizations always tend to reduce expenditures and increase income, consequently, they are attracted to (having cost-efficient infrastructure) they intend to adapt to the multi-cloud. But of course, it’s not just this reason. More reasons are explained in the next section.

Organizations’ tendency for multi-cloud

There are many tendencies to embrace a multi-cloud strategy, here some of them are listed.

The common reason is to reduce cloud computing overhead by designing a cost-efficient infrastructure by using cost-effective options from multiple cloud vendors.

AzureVM instancesContainer clustersHosted AppsServerless functions
AWSAWS EC2AWS EKSAWS Elastic BeanstalkAWS Lambda
GoogleGoogle Compute EngineGoogle Kubernetes EngineGoogle App EngineGoogle Cloud Functions

The second common reason is different services that are offered by different cloud vendors because some vendors offer specialized services. It might not be the most economically efficient service, but it fulfills the requirements of the workload better, and it’s not available on another vendor.

The third reason is, to improve the reliability and availability of cloud-based workloads because they spread across multiple clouds and disruptions to those workloads are less likely.

The fourth reason is when globally distributed enterprises / international companies acquire offices/subsidiaries in different countries, or they have to be merged with other companies, and they may have their resources in different clouds. Since a particular cloud provider doesn’t have a data center in a country.

The fifth reason is, that the organizations want to avoid cloud provider lock-in. If the could provider changes the price of the services used in your workload, the entire workload is impacted. The solution is to architect the applications cloud-agnostic that can be run on any cloud. It does not mean that it would be cheaper or more efficient to run on more clouds, because the workflow can be optimized if a specific cloud is used, but it is better to have the option to be able to move the workload.

By using a single-cloud strategy you can also develop workloads that are able to move to another cloud without difficulty, but it happens really fast to get deeply dependent on the cloud vendor’s tools and services and encounter the following risks:

Migration is difficult and costly

Budget risk when the vendor raises the service costs

And the solution is:

  • Using multi-cloud strategy
  • Using tools that are cloud-agnostic and can be used in any clouds

The result of using a multi-cloud strategy is:

  • Easier migration/swap of a particular workload to another cloud
  • Not lock-in on a cloud vendor
  • Freedom to choose the cost-efficient services cloud provider
  • Avoid mirroring expenses

The reasons above are impacting the organizations’ infrastructure more and bring more benefit for projects because of being able to have multi-cloud architecture.

Basically, multi-cloud architectures are more expensive to implement because of the complexity (several toolsets for cloud management or cloud service broker, and each cloud provider has its own way of doing things). However, money can be saved considering the ability to pick and choose cloud services from multiple cloud vendors. In this case, the services that are not only the best but the services that are most cost-efficient. This is going to provide us a strategic advantage.

Another mandatory point is, to figure out the business case to understand costs vs. values, the organizations need some sort of value advantages of doing so, how can this value come back into the organization.

 Single public cloudTwo public cloudsTwo public clouds & Private Cloud 
Initial costs500,000 $750,000 $1,000,000 $– In terms of getting things up and running – Getting things scaled up – In 3rd case is because of the software and hardware of the private part
Yearly costs100,000 $125,000 $300,000 $– For pay as you go -Maintain
Value of choice0$200,000 $250,000 $– Value of move information -How beneficial it can be
Value of agility500,000 $800,000 $900,000 $-Ability to change things as the needs of the business change (speed of need)

Value of choice: it is more business and asks about the impact of this decision on KPIs.

Value of agility: it is more technical and asks more about how I can react to business changes.

Therefore, we have to understand the business metrics to be able to understand the business value and then decide on the best solution for the project.

Always the business metrics / KPIs (Key performance indicators) have to be considered. The KPIs have an impact on the value of choice.

Sales revenueNet profit marginGross marginSales growth year-to-date
Cost of customer acquisitionCustomer loyalty and retentionNet promoter scoreQualified leads per month
Lead-to-client conversation rateMonthly website trafficMet and overdue milestonesEmployee happiness

To have a successful multi-cloud infrastructure and deployment, it’s important to have a configuration of services, which is both compliant with the organization’s regulations and cost-efficient. Unless the deployment in production would be a big challenge.

Multi-cloud challenges and considerations

When an organization decides to adopt multi-cloud and use multi-cloud strategies, they have to prepare for the following items and have a strategy for them:

  • Integration
    • How do share data between workloads running on multi-cloud?
  • Management
    • How to manage resources from an abstract layer without making your hands dirty with different cloud vendors’ command lines and tools?
    • How do monitor resources?
    • Which cloud service brokers can be used?
  • Optimization
    • How should be the service configuration to have a cost-efficient infrastructure?
  • Compliance
    • How do keep the service configuration compliant with the regulatory outlines of the organizations?
  • Technical
    • They are adding complexity to the architecture and adding more risk but how it can bring more value back into the organization?

How can we do each of them?

  • For integration
    • Managing all workloads from a central monitoring hub
      • Using third-party tools for management and monitoring like Using a universal control plane, which abstracts the workload from the underlying cloud, where the workload is hosted. Cross-plane and Kubernetes are the tools that can be used for multi-cloud architecture. The drawback of this approach is,
        • Workloads that cannot be containerized
        • Lack of knowledge and experience with Kubernetes
  • For Management/Monitoring
    • Universal Control Plane can be used
    • Third-Party solution
    • A custom solution can be developed (using clouds’ APIs) but this solution is less centralized. The API approach also demands more hands-on effort from IT personnel, both upfront and for maintenance.
    • Management console of each of the clouds (navigating between tools for different clouds).
  • For Optimization performance
  • Compliance
    • Unifying all workloads within a common security and access-control framework
Figure 2: Multi-cloud toolset basic architecture for custom tools or third-party

The important point is

Cloud vendors don’t make it easy to integrate a workload running on one cloud with another workload hosted on a competitor’s cloud.

Most cross-cloud compatible tools provided by cloud vendors focus on importing workloads from another cloud rather than offering support for ongoing integration between workloads running across multi-clouds.

And finally, we have to pay for the services and tools of the third party.

Multi-cloud governance and security

Security is not governance but has to be linked for multi-cloud. Governance is about putting limitations on the utilization of resources and services, in other words, governance is restrictions based on identity and policy. Security is about authenticating and authorizing the person and machine that use this resource, in other words, security is restrictions based on identity and access rights (Identity Access Management is an important requirement for multi-cloud). [4]

The hierarchy of security and governance is as follows.

For a successful multi-cloud infrastructure, it’s necessary to have a good governance and security outline.


Leveraged resources e.g., storage, compute, database, cloud server broker (CSB), etc. If they are still used or de-provisioned, how high is the charge, if they follow the usage rules e.g. only specific sizes of VMs are allowed to be used.


Keep track of services e.g. data transfer services.


It’s about who’s using what and when, and how much they should be charged. This is about the policies for the utilization of resources and services. It must be done for a show back and chargeback (this is a part of the reimbursement process). It can be used for the health of the multi-cloud system. The other usage is putting limitations to manage the budget of the projects. It is one of the challenges that enterprises are encountering.

For doing governance a Cloud Management Platform (CMP) is needed. This provides a common interface to manage the resources and services across different clouds by providing a layer of abstraction to remove complexity.

CMP monitors the charge of provisioning, de-provisioning of resources, and usage rules of resources as well. The advantage is, because of the abstraction layer, it’s not necessary to be the expert on everything.

Multi cloud Requirements

As Many multi-cloud architectures are similar to hybrid cloud architectures and they have almost the same requirements and needs.

Figure 4: Multi and hybrid cloud expectations from a development perspective

Multi-cloud workloads categories

The common workloads that can use the multi-cloud strategy are as follows:

Deploying the same workload on two or more clouds simultaneously e.g., a business might store copies of the same data in both AWS S3 and azure storage. By spreading data across multiple clouds, that business would gain greater availability and reliability (without paying higher costs for mirroring data, because the mirroring is expensive e.g., multi-region is expensive in AWS)

Running multiple workloads at once, with some workloads running in one cloud and the others in another cloud (this approach provides cost efficiency and cloud agnosticism but doesn’t make individual workloads more reliable than using a single cloud)

It’s to keep multi-tier applications in the same cloud and region (then you can use the cloud provider’s backbone for internal traffics.)

The same applies to multi-cloud architecture for hybrid deployments

Whereas you can purchase dedicated bandwidth between on-prem and Azure (for example), can’t easily do the same between public cloud providers.

The workload might have regulatory requirements, which means that you might be in a Geo, that has a particular piece of legislation, and that particular piece of legislation might specify where data can go, or the security configuration might be a set of standards.

Multi cloud for workloads with complex regulatory requirements

  • Each cloud has diverse ways of assessing compliance with regulatory standards.
  • While cloud providers themselves are compliant with standards, the configuration for your organization’s workload may not be.

What should the technical lead know before starting with multi-cloud

The compute offering on the cloud is lying along a spectrum from IaaS (when you manage your servers, storage, networking, firewalls, and security on the cloud) to PaaS ( when you use platform-specific tools for scaling, versioning, and deployment). PaaS can help to go to production faster.

AzureVM instancesContainer clustersHosted AppsServerless functions
AWSAWS EC2AWS EKSAWS Elastic BeanstalkAWS Lambda
GoogleGoogle Compute EngineGoogle Kubernetes EngineGoogle App EngineGoogle Cloud Functions

In the first column, we have more low-level access to hardware, underlying operating system, and machine, with virtual machines we have abstraction over hardware. At the right end, you have hosted apps and serverless functions, that give you fewer ops and less administrative overhead and you don’t have to provision your own machine. We focus on the code and the platform takes care of the rest. However, this means you have less control and more platform lock-in.

As you see in the table above no matter which cloud provider you use, you have almost the same services.

If you want to have less administrative overhead and more platform support and don’t worry about provisioning, then you have to use platform-specific tools. On one side platform-specific tools offer convenience and on the other side lock you into a particular platform and the code that you write is not portable.

You can choose more control, then you have less platform support and you end up using open-source tools. This is a balance that you need to get to.

The balance between embracing platform capabilities and enduring vendor lock-in: search for your own sweet spot.

This sweet spot companies have found often involves the use of containers.

Containers offer the right trade-off between IaaS and PaaS offerings. Containers are just a unit of software, which basically package your application and all of its dependencies into an isolated unit. Containers are a key technology when you’re planning for a hybrid or multi-cloud.

A single container does not offer scalability, load balancing, fault tolerance, and all other bells and whistles that you need when you’re building at scale. What you need is a cluster of containers. Once you have a cluster, you need an orchestrator, that’s where Kubernetes comes in.

Kubernetes is an orchestration technology for containers and allows you to convert isolated containers running on different hardware into a cluster. Kubernetes embrace platform capabilities while maintaining the portability and flexibility of your code. The cool thing about Kubernetes is, no matter what cloud platform you’re on. All of them support Kubernetes.

A successful multi-Cloud solution/deployment

Elements of successful multi-cloud deployments would be as follows:

  1. A consistent set of tools to manage workloads across clouds (several tools for maintenance across multi-cloud might not be a good idea, for example, if we have to use something like PowerShell to manage each cloud, then we have to know the different command lines of Azure, AWS, and GCP, and this is cumbersome). A good solution is to have only one tool for managing all VMs and pay for this service. These expenses are for efficient maintenance.
  2. A consistent way of monitoring the security of workloads across clouds.
  3. Easy to manage and monitor costs for each cloud in the multi-cloud deployment.
  4. Ability to migrate workloads between clouds as necessary (to avoid the lock-in issue)

Multi cloud identity

Manage identity and access management for cloud [3] admins, app developers, and users. For cloud-based solutions, identity management and access management (IAM) must be always available.


[1] Why Organizations Choose a Multicloud Strategy, Goasduff, Laurence, Production date: 2019.05.07, Accessed date: 2020.06.23

[2] Multicloud strategies, Linchicum, David, Accessed date: 2020.07.03

[3] Public Cloud Inter-region Network Latency as Heat-maps, Agarwal, Sachin, Accessed date: 2020.07.09

[4] TECH INSIGHTS: THE IT TECH SHAPING TOMORROW, Christopher, Tozzi , Production date: 2019.10.21

[5] Microsoft’s New Azure Arc Services Can Run on ‘Any Infrastructure’, Sverdlik, Yevgeniy , Production Company: Datacenter Knowledge, Production date: 2019.11.04, Accessed date: 2020.06.06

[6] Governance guide for complex enterprises: Multicloud improvement, Production Company: Microsoft, Production date: 2019.9.17, Accessed date: 2020.6.21

[7] Multi-Cloud Governance: Agility, not Chaos in your Multi-Cloud, Production Company: Microsoft, Production date: 2019.1.21, Accessed date: 2020.7.15

[8] Making Sense of a Multi-Cloud API Approach, Anthony, Art, Production date: 2020.05.17, Accessed date: 2020.06.03

[9] Hybrid Cloud Infrastructure Foundations with Anthos, Production Company: Google, Production date: 2019.12.10, Accessed date: 2020.5.25

[10] 12 Business Metrics That Every Company Should Know, Karlson, Karola, Accessed date: 2020.07.03

[11] Multicloud identity and access management architecture, Production Company: IBM, Accessed date: 2020.07.03

Published by parisamoosavinezhad

- Software Engineer - Software Architect - Software and database specialist - Cloud solution architect

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