An Introduction to Hybrid and Multi-Cloud Connectivity

As the cloud industry matures, it’s no longer a question of if you’re in the cloud, but how many clouds you’re in. Most businesses now realize that there isn’t a “one cloud fits all” solution and have shifted towards a hybrid or multi-cloud model.

Hybrid and multi-cloud models have become popular for helping to prevent vendor lock-in, reducing costs, and allowing businesses to stay innovative by only using the best features of each cloud provider. Adopting a hybrid model has also been influenced by growing security concerns and tougher compliance regulations. Rather than migrate all data and applications to the public cloud, some businesses prefer (or are required) to keep some data on-premise to reduce the risk of breaches.

With that said, the complexity of setting up multiple environments and dealing with the day-to-day management can create a new set of problems.

To overcome these, more and more businesses are setting up VPNs, VPS peering, or direct links between their environments to create cross-cloud connectivity. This can be between their public clouds like AWS and Google, or between their on-premise and public clouds.

In this article, we will look at the benefits of hybrid and multi-cloud models, the difficulties that can arise during implementation, and why investing in cross-cloud connectivity can be vital to simplifying all the complexities of managing them.

What’s the Difference Between the Hybrid Cloud and Multi-cloud Model?

Let’s start by defining the hybrid and multi-cloud models.

In a hybrid cloud model, a business operates some of its workloads in a private cloud or on-premise, and some in a public cloud (or multiple public clouds). Many businesses adopt this model when they start gradually moving all their workloads to the cloud. Sometimes this is more of a permanent scenario, particularly when there are security concerns or regulatory requirements to host sensitive data on-premise. 

A hybrid model will involve creating connectivity between the private/on-premise network and the public cloud(s). As modern applications become more distributed, it’s common to have some components in a public cloud and others on-premise. For example, a business may be required to host their payroll data on-premise for compliance reasons but may want to access it from an analytics application hosted in AWS or GCP, so they will need to have connectivity in place between the two.

In a multi-cloud model, a business runs its workloads in one or more public clouds. Many businesses have adopted this model as they have started to convert monolithic applications to a distributed architecture. This way, they can deploy individual microservices in the most suitable cloud. 

For example, a business can deploy some services of a distributed application with AWS, some with Azure, and others with GCP. They may also want to take advantage of services or features that are unique to one provider. In another example, a business may have its data live entirely in AWS, provide its user authentication service from Azure Active Directory, and serve its message queuing service from Google Cloud Platform.

Benefits of Hybrid and Multi-Cloud Model

Whether you adopt a hybrid or multi-cloud approach, both models bring several benefits in comparison to an on-premise only or single cloud-only environment. Some of these benefits include:

Flexibility to choose any provider for any application. Sticking to one provider confines you to using only their services when your needs start to change over time. By deploying applications across multiple providers, you can access innovative technologies quickly and can combine the best from each provider.

This also ensures there are no vendor lock-ins. Lock-in with a particular cloud provider is a result of a business investing so heavily with a cloud provider that migrating away becomes too prohibitively expensive and complex. By spreading the services between different providers, a business has the freedom to deploy new or existing applications in whichever cloud is most beneficial.

Scalability allows your workloads to automatically adjust to spikes and dips in demand. One of the main benefits of public clouds is the automatic—and often limitless—scalability. This can go one step further when you have multiple clouds and want even more scalability and fault tolerance. The same scalability benefits apply when the capacity of a solely on-premise environment needs to expand.

Lower Opex and Capex. There’s no need for upfront payments for infrastructure when using a cloud environment, and the purchase model is pay-as-you-go. Cloud vendors often offer a cost-saving mechanism by enabling customers to make an upfront payment (Capex) in exchange for a much lower ongoing payment (Lower Opex). As the large cloud providers benefit from huge economies of scale, they often pass these savings on to the customer.

Better Resilience. Spreading modern, distributed applications across multiple environments also spreads the risk of downtime. Although uncommon, there have been events of cloud environments going offline in one or more regions. Having applications and services hosted on-premise, and in a mix of public clouds with a solid failover plan, reduces the exposure to vendor outages. 

For example, let’s say you host your website with Google, but host your email and desktop software with Azure. A Google outage would take down your website, but you could still access your office productivity applications. Even better, if you have web servers in Google and use Azure as a backup for your web server, then your website wouldn’t go down at all.

The Need for Cross-Cloud Connectivity

Hybrid and multi-cloud models have many advantages, but they undoubtedly add an extra layer of complexity. Although cloud computing has been around for more than a decade, effective network connectivity mechanisms and tools have only matured in recent years. 

So why is cross-cloud connectivity becoming so vital for hybrid and multi-cloud setups?

The increased complexity of managing multiple environments is one of the biggest reasons. Without cross-cloud connectivity, engineers would spend more time on the administration of each cloud environment than on developing new application features. 

Another reason is the increasingly distributed nature of applications. Microservices are spun up and spun down automatically by container orchestration engines. These can run on clusters spanning across on-premise and cloud boundaries. To keep such huge footprints running smoothly, guaranteed connectivity between all environments is mandatory. 

When multiple teams work across different clouds, there is also a risk of unnecessary duplication of workloads and effort. For example, one application may be hosted in AWS and another in Azure, both requiring an authentication mechanism. Without multi-cloud connectivity, each environment would need a separate authentication server—doubling the cost.

Security can also become difficult to manage. The distributed nature of hybrid and multi-cloud environments increases the attack surface. To keep things under control, consistently applying network ACLs and firewall rules becomes increasingly complex and difficult.

One way to address these challenges is to segment workloads and data between different providers. For example, an application can have all its data stored in AWS, and another application can have all its data residing in GCP. The problem with this approach is that there’s no single view of data and the enterprise application footprint. 

The Solution: A Separate Cloud Connectivity Layer

A much better approach to address these challenges is to introduce a separate connectivity layer between the on-premise and cloud environments. This layer takes care of all the underlying work to ensure each environment can talk to each other. If the underlying distributed infrastructure needs to expand due to increased load, this layer would transparently ensure the relevant API calls are conveyed to the correct cloud provider. With such a dedicated cloud connectivity service, not only does the whole IT infrastructure become more resilient and fault-tolerant, but enterprise IT is freed to pick and choose any service, from any cloud provider, that best suits the business’ needs.

Here are some of the benefits of a separate and dedicated cloud connectivity solution. 

Expansion on Demand

One of the main selling points of cloud computing is “Cloud Bursting”. In theory, this involves automatically scaling out resources when application demand rises and scaling back when the demand recedes. Thus, ideally, you only pay for the resources that you use, in the time that you are using them. 

This works great when using only one cloud provider. Most scalability scenarios can be automated with either the cloud provider’s own tools or by writing custom scripts. However, when it comes to hybrid or multi-cloud setups, the process isn’t always easy to implement. In fact, it can be extremely difficult if resources need to be scaled across on-premise and cloud boundaries. It requires careful planning and automation to trigger the creation or deletion of new servers at the right time, all the while ensuring the application isn’t adversely affected, or the resources chosen are cost-effective. Wrong or suboptimal scalability can mean introducing data inconsistencies, lax security, or unprotected resources across different sites.

Adding a connectivity layer between on-premise infrastructure and a public cloud makes it much easier to expand on resources when needed and scale back when the demand falls. The connectivity application can work seamlessly across each cloud environment. All that an automation mechanism needs to do is to call its API, which in turn will translate the scaling request to the appropriate API commands of the underlying cloud.

Maximum Resilience, Minimum Downtime

Most public cloud service providers—including big names like AWS, Azure, and Google—have extremely large infrastructure at their disposal and can offer high Service Level Agreements (SLAs) to their customers. It also makes cloud outages very rare. Having said that, sometimes outages do happen, as shown in this page from AWS. 

By leveraging a hybrid or multi-cloud model, enterprises can achieve stronger resilience against outages and minimize downtime. Using a dedicated multi-cloud connectivity solution, businesses can load-balance across multiple clouds. In the event of one cloud service going down, the load-balancer will automatically direct application traffic to a backup service in another cloud. This is made possible with tools like service meshes that give you the ability to smartly monitor networks and routes to automate the redirection.

Celebrate Diversity

Embracing a multi-cloud setup allows organizations to try and buy the best features from different providers. For example, one cloud provider may offer the best Function-as-a-Service (FaaS) feature, while another may offer the best price/performance ratio for a message queuing service, and yet an on-premise system may offer the best storage option. Each aspect can be utilized together to form a diverse and competitive system.

Using different providers also gives you extra flexibility when onboarding new teams and applications from mergers and acquisitions. There’s no need to migrate an already-running application to a whole new cloud provider or re-train engineering and operations staff to work in a new environment.

However, this also adds a level of complexity as operations teams now have to manage and monitor multiple cloud environment resources and services, each with its own set of APIs. 

A multi-cloud connectivity platform can add an abstraction layer to streamline this administration via a single pane of glass.

Conclusion

In theory, operating a hybrid or multi-cloud model will allow organizations to get the best of each cloud service and improve the performance, availability, and security of their applications.

However, manually implementing and managing these models is extremely complex. Without proper planning and intelligent use of cloud management tools, this often leads to spending more time troubleshooting.