How developers can turn multi-cloud complexity into a data advantage

Multi-cloud is quickly going from a niche possibility to a business necessity.

IDC’s recent Cloud Pulse survey showed an increasing number of organisations across Australia are using multi-cloud to address the business and technology challenges of the pandemic.

According to the analyst firm, over the last year, Australian organisations have been at the forefront of regional cloud adoption and infrastructure transformation across all sectors.

There are many reasons why organisations end up in a multi-cloud state: the desire to add flexibility, avoid vendor lock-in, find the most cost-effective platforms to support certain workloads, or gain access to specific tools, integrations or differences in regional performance and pricing. There’s also the accidental sprawl that happens in big organisations with acquisitions and siloed teams often working on a variety of platforms.

A successful multi-cloud strategy is one where a business can be run seamlessly across multiple cloud providers to achieve more availability, access to more services, improve customer experience and deliver better business continuity.

So, typically company X could use cloud A for infrastructure, cloud B for analytics and ML, and cloud C for data localisation in a region.

Developers can’t afford to turn their eyes away from multi-cloud. They have an obligation and opportunity to understand how they can take advantage of this megatrend. However, the multi-cloud approach does come with its challenges.

Data challenge

What organisations need from a multi-cloud perspective is to build an application or a microservice, and either be able to run it from anywhere or to run it in a specific cloud to take advantage of specific services.

While technologies like kubernetes and Terraform have made some elements of multi-cloud more manageable, particularly at the application layer, the data layer is a whole different story.

For many organisations and developers, multi-cloud often leads to data ending up siloed between different transactional, analytical and search systems. This is further complicated by data’s tendency to get caught with a particular cloud provider, the dreaded data gravity.

As a result, developing across multi-cloud often means:

More work: To migrate or duplicate any data from one cloud provider to another, developers have to create and maintain bespoke processes.

Living in hope: If one cloud region goes down, failing over to another is not seamless and results in slower experiences for all.

Incompatible operations: It’s difficult to secure, monitor, maintain and govern access across multiple clouds.

The need to rewrite the majority of application code for each cloud: And even then, datasets can remain siloed. This slows developers down, forcing them to focus on the infrastructure rather than the applications or data.

An example

Legacy systems haven’t been designed to work seamlessly across multi-cloud platforms and the proprietary cloud services are, by design, tied to a single provider.

Organisations today need to rethink their approach and turn to native multi-cloud infrastructures and databases which are designed specifically for those complex environments. A native multi-cloud approach empowers developers to turn multi-cloud from a hindrance into a data advantage.

For example, Australia’s leading ticket distributor, Ticketek, can handle up to 300,000 ticket sales in less than 30 minutes. It has data in various regions across AWS and Google Cloud, as well as a secondary ticketing platform that runs in Google Cloud’s Sydney region.

Imagine taking a modern application like this one a step further and deploying a single data layer across AWS, Google Cloud and Azure at the same time. All without the deployment and interoperability hassles. It’s possible.

Multi-cloud, a data ally

Organisations such as Ticketek, and many others, have found an effective way to thrive in multi-cloud environments. But how?

First, you need to find the right data layer. For most organisations that means a database as a service (DBaaS) that has three key features. First, it abstracts away underlying software, infrastructure and management. Second, the DBaaS uses a developer-centric data model which can handle any data type and easily deploy new functionality. Third, it’s the obvious one: the database as a service must be platform agnostic, so you can deploy anywhere, anytime.

If you can get that right and find a platform with native multi-cloud capabilities then development teams benefit in a number of key ways. These include:

• Pick and mix the best tools across clouds, which is not only a preferred way to work but also gives organisations enough flexibility to accommodate their customers’ preferred cloud provider/s.
• Expand apps globally with high availability and low latency.
• Distribute data across more regions and sleep better at night knowing resilience and recovery is built in.
• Satisfy local data sovereignty requirements, especially for organisations working with regions covered by only one cloud provider (ie, AWS in Australia, Azure in India, Google Cloud in Japan).
• Benefit from portability with the easy migration of apps from one cloud to another in any situation.

If Australian organisations want to stay at the forefront of their industries and truly reap the benefits of multi-cloud environments, they need to empower their tech teams with the right platforms that are fit for purpose. This means allowing developers to build once, host anywhere, anytime.

Image credit: ©stock.adobe.com/au/Alex