The concept of cloud computing has been around for years, but cloud services truly became democratized with the advent of virtual machines and the launch of Amazon Elastic Compute in 2006.
Following Amazon, Google launched Google App Engine in 2008, and then Microsoft launched Azure in 2010.
At first, cloud computing offerings were not all that different from each other. But as with nearly every other market, segmentation quickly followed growth.
In recent years, the cloud computing market has grown large enough for companies to develop more specific offers with the certainty that they’ll find a sustainable addressable market. Cloud providers went for ever more differentiation in their offerings, supporting features and capabilities such as artificial intelligence/machine learning, streaming and batch, etc.
The very nature of cloud computing, the abundance of offerings and the relative low cost of services took segmentation to the next level, as customers were able to mix and match cloud solutions in a multi-cloud environment. Hence, instead of niche players addressing the needs of specific market segments, many cloud providers can serve the different needs of the same customers.
Introduction to Serverless
The latest enabler of this ultra-segmentation is serverless computing. Serverless is a model in which the cloud provider acts as the server, dynamically managing the allocation of resources and time. Pricing is based on the actual amount of resources consumed by an application, rather than on pre-purchased units of capacity.
With this model, server management and capacity planning decisions are hidden from users, and serverless code can be used in conjunction with code deployed in microservices.
As research firm Gartner Inc. has pointed out, “serverless computing is an emerging software architecture pattern that promises to eliminate the need for infrastructure provisioning and management.” IT leaders need to adopt an application-centric approach to serverless computing, the firm says, managing application programming interfaces (APIs) and service level agreements (SLAs), rather than physical infrastructures.
The concept of serverless is typically associated with Functions-as-a-Services (FaaS). FaaS is a perfect way to deliver event-based, real-time integrations. FaaS cannot be thought of without container technologies, both because containers power the underlying functions infrastructure and because they are perfect for long-running, compute-intensive workloads.
The beauty of containers lies in big players such as Google, AWS, Azure, Redhat and others working together to create a common container format – this is very different from what happened with virtual machines, where AWS created AMI, VMware created VMDK, Google created Google Image etc. With containers, IT architects can work with a single package that runs everywhere. This package can contain a long running workload or just a single service.
Serverless and Continuous Integration
Serverless must always be used together with continuous integration (CI) and continuous delivery (CD), helping companies reduce time to market. When development time is reduced, companies can deliver new products and new capabilities more quickly, something that’s extremely important in today’s market. CI/CD manages the additional complexity you manage with a fine grained, serverless deployment model. Check out how to go serverless with Talend through CI/CD and containers here.
Talend Cloud supports a serverless environment, enabling organizations to easily access all cloud platforms; leverage native performance; deploy built-in security, quality, and data governance; and put data into the hands of business users when they need it.
Talend’s strategy is to help organizations progress on a journey to serverless, beginning with containers-as-a-service, to function-as-a-service, to data platform-as-a-service, for both batch and streaming. It’s designed to support all the key users within an organization, including data engineers, data scientists, data stewards, and business analysts.
An organization’s data integration backbone has to be native and portable, according to the Talend approach. Code native means there is no additional runtime and no additional development needed. Not even the code becomes proprietary, so there is no lock-in to a specific environment. This enables flexibility, scale and performance.
The benefits of serverless are increased agility, unlimited scalability, simpler maintenance, and reduced costs. It supports a multi-cloud environment and brings the pay-as-you-go model to reality.
The serverless approach makes data-driven strategies more sustainable from a financial point of view. And that’s why serverless is a game changer for data integration. Now there are virtually infinite possibilities for data on-demand. Organizations can decide how, where, and when they process data in a way that’s economically feasible for them.