Cloud services have become an essential digital transformation platform for business, allowing technology to build new business models or processes through converging access to communication, media, and software. While innovation has changed SWOT charts for many businesses, innovation has been coming for the cloud itself.
One company leading the charge is Google, by incrementally adding serverless tech into its cloud services. Google has been doing so for some time. Google App Engine was Google’s first service compute service, launched in 2008.
In fact the term serverless has received a lot of buzz in the IT marketplace, especially with the growing competition from AWS Lambda, Microsoft Azure, and IBM OpenWhisk.
What is “serverless”?
But some confusion exists on just what tech is considered “serverless”. Bret McGowen, developer advocate at Google, took time to explain Google’s approach to its cloud services, relative to the serverless trend:
“The term serverless is still quite new in the technology community, and can be confusing to folks who see it without context or explanation. In particular, there still are servers, but someone else is managing them. It’s definitely not code running in the ether. So it’s less likely you’ll see a Google use ‘serverless’ in a product name for at least a little while longer while the term gains adoption. In the meantime however, we definitely use ‘serverless’ to describe tools like Cloud Functions, BigQuery, App Engine and Firebase.”
While Amazon has been recognized as a leader in cloud platform, Google has made serious inroads, looking to unify its platform with its burgeoning machine learning capabilities. Google has garnered new customers, and respect from satisfied executives, such as this observation from Andrew Duffle, director FP&A, analytics and optimization at the American Precious Metals Exchange:
“We have found BigQuery data to be immediately actionable. It focuses our marketing efforts, personalizes our onsite experiences, and improves the effectiveness of our sales department. When used in conjunction with our current data systems, there is seemingly no question about our customers that cannot be answered. It’s that powerful.”
How serverless impacts marketing tech
The interest in serverless comes from a paradigm shift in client-server computing architecture. Computer terminals connected to a server was once — and in a basic sense, still is — the standard model. Over time smaller portable devices, combined with faster networks, raised the demand for servers to provide information — be it code or data –quickly.
Programming frameworks like Node.JS, which allows frameworks to operate as an integrated client-and-server application, increased options for data delivery, data storage, and more dynamic software like chatbots. All of this is meant to manage the various data types that are analyzed or generated.
The outcome for cloud providers is a need to design cloud resources that adjust to these tech factors. Indeed, dynamic capability is appearing in many of the latest tech stacks, such as on server-to-server header bidding, which I discussed in this post.
“As-a-service’ categories are at the heart of serverless tech. The most relevant category with respect to analytics is Backend-as-a-Service (BaaS), a platform that links web and mobile applications to back end data storage and resources. BaaSs is meant to expose back end APIs to applications, while providing collaboration features such as user management, push notifications, and analytics. A virtual program meant to hold a custom code is usually considered a Managed-Function-as-a- Service (or Function-as-a-Service). It serves as a container platform from which a code can execute a task.
How marketers ultimately benefit
The downstream impact to marketers or marketing ops professionals considering serverless cloud services is an opportunity to establish resource efficiency. McGowen explained that value further:
“Serverless tools can help marketers in two ways: First, for groups that are building technical solutions, serverless tools may result in teams being more efficient in both engineering staff (due to offloading many operations concerns to the cloud provider), and in cost (due to pay-per-use economics). Secondly, serverless tools like BigQuery remove a layer of technical complexity which can create opportunities for subject matter experts to write code or run queries without having to necessarily go through an IT staff member.”
Removing that layer can quicken the pace at which apps and microservices can be delivered to production. Full stack developer capability within a team would not be required. That arrangement can be significant for small teams that have limited developer support for debugging.
Serverless options can enhance DataOps initiatives as well. DataOps is a developer-influenced methodology to improve data analytics quality. Serverless cloud services can enhance how organizations orchestrate data, tools, and code changes among teams. Thus an enterprise coordinating teams with event-driven cloud activity gains a competitive advantage.
The commitment to serverless architecture across the major cloud players ensures that the serverless trend will continue. Marketers seeking new ways to explore data should look at how serverless architecture can ease that exploration.
