Presenting the D in DSP, Digital Platforms and Services

First there was the virtualization of network functions (NFV), which detached network functions such as load balancing, routing, firewalling or encryption from wired devices and placed them on increasingly powerful server hardware. It worked, but only, and as a result, NFV seemed to reach a certain level of adoption in telco land, after which initial enthusiasm waned and the industry pinned its hopes on cloud native instead. That resolved key NFV drawbacks by adding orchestration, microservices, containers, and continuous delivery, providing a well-rounded and flexible virtualization framework for further developing network services and cloud applications in general. It also marked the moment when it seemed likely that the hyperscalers would eventually hit the telecom market.

One of those further developments was the idea of ​​serverless computing, which can be seen as a logical step forward for the cloud-native brigade. Serverless essentially “abstracts” the lower levels of the stack, theoretically allowing the developer to focus on the creative, value-added piece of an application rather than spend time organizing the underlying infrastructure to manage the data storage, scheduling, scaling and other requirements. In this sense, a serverless environment not only deprecates servers and all their tasks, but assigns the low-level tasks to a third party (probably the cloud provider) who provides the necessary storage and processing. It’s no wonder, then, that several studies show that the serverless approach appeals to application developers, but also more broadly to business users because of its potential cost and flexibility benefits, especially with regard to edge computing developments.

According to IDC’s IaaSView Buyer Survey, about 25% of cloud infrastructure as a service (IaaS) buyers plan to adopt serverless capabilities in the next year, while a recent report from data dog claims that serverless computing “entered the mainstream” with more than half of all organizations already using serverless on AWS Lambda, Azure Functions, or Google Cloud Functions. Of particular concern to telcos here is the high serverless adoption rate that has clocked in for edge developers, which in turn should be encouraging for telcos looking for business opportunities aligned with their edge strategies – more relevant applications will be the arouse corporate interest in what the telcos have to offer.

The Cloud Native Computing Foundation will report in early 2021 on: The state of cloud native developmentwhich meticulously charts the software usage trends of the developer community, calculates that about 48% of edge developers are currently serverless compared to just 33% of all back-end developers, and it claims that the “lightweight nature of a serverless architecture is particularly attractive to edge developers because they don’t have to manage the underlying infrastructure.”

However, the report also notes that serverless usage rates have grown more slowly than Kubernetes and even recently experienced a small unexpected drop — the cause of which isn’t fully understood, it claims. That drop could be the result of shifting developer loyalty within the serverless category that continues to grow, just not as much as Kubernetes, for example.

AWS Lambda, the first serverless cloud product, continues to lead the segment with 53% of serverless developers using it. More recently, Google’s serverless computing platform with built-in Kubernetes containers has progressed remarkably, the CNCF says, “up 8 percentage points over the past six months, while Google Cloud Functions (the original serverless offering) experienced a 3% drop.” presumably due to cannibalization. In any case, the CNCF claims that Google’s serverless plus Kubernetes offering brings “the best of both worlds” together.

Serverless Benefits

With serverless, the cloud provider can enable all the necessary provisioning, planning, scaling and back-end operations tasks from the cloud, and as a result developers have the time to proceed with front-end development – all the grunt work is taken care of . Needless to say, users pay for the processing and storage tasks assigned by the serverless application, but the point is that usage is meticulously measured and users only pay for what they use. Among other things, this provides an ongoing incentive to develop applications that use less data center resources (good for those sustainability goals), but usually serverless helps keep an edge application “light” in terms of its ongoing complexity.

An added attraction for developers is the ability to use any of the popular programming languages, so there is no requirement to learn what Anshu Agarwal vice president general manager of serverless at DigitalOcean, describes it as “complex infrastructure-focused concepts, such as containers and Kubernetes”. This brings related benefits, such as a shorter time to market and because functions only run in response to events, the associated costs are lower. Ditto with infrastructure component scaling, which is handled automatically by the serverless application provider.

The serverless landscape

As things stand now, serverless usage has increased significantly, with data dog reports that serverless options have been used by more than half of users on all three major hypersale platforms. Each platform has a range of serverless options:

AWS: AWS Lambda, AWS App Runner, ECS Fargate, EKS Fargate

Azure: Azure Functions, AKS running on Azure Container Instances

Google Cloud: Google Cloud Features, Google App Engine, Google Cloud Run

The technical change – and the sentiment – ​​is so rapid that enthusiasm for a particular network scheme or approach can peak and fall faster during a financial crisis than a digital currency. This volatility is greatly supported by the technology itself. Instead of research companies creating carefully formulated survey questionnaires to examine companies’ future plans and current implementations, some, like Datadog, rely instead on network telemetry. That provides data straight from the source about who has adopted what and how much they are using it. There’s no room to hide or obscure and it means small changes in adoption become apparent almost immediately.

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