Serverless computing market set to hit $193.4B by 2035 – here's who's leading

  • Serverless computing still involves servers but allows developers to focus on development rather than managing infrastructure.

  • Google Cloud leads in the percentage of serverless customers using container-based tools.

  • Microsoft Azure lags behind Google and AWS but is rapidly gaining on them.

Serverless computing has quickly become a popular tool for developing the cloud-based applications. But don’t let the term “serverless” fool you because servers are still very much a part of the process.  

The term "serverless computing" refers to a cloud-native development model that allows developers to build and run applications without having to manage servers. Servers, basically, are hidden away from the app development. Cloud providers take care of the provisioning, maintaining and scaling of the servers so developers can focus on putting their code in containers.

Serverless computing is rapidly becoming a mainstay for app developers. A new report from cloud monitoring firm Datadog, which surveyed 20,000 of Datadog’s customers, found that serverless computing is being widely used across all major public cloud platforms. The survey found that 70% of Amazon Web Services (AWS), 60% of Google Cloud and 49% of Microsoft Azure customers currently use one or more serverless solutions.

Indeed, the serverless market is expected to expand dramatically in the next decade. According to Global Market Insights, revenue from serverless computing will grow from $12.43 billion in 2022 to $193.4 billion at the end of 2035.  The research firm attributes that dramatic growth to the expansion of Web applications, including e-commerce sites, content management systems and social media platforms, many of which are being built using serverless architectures.

Because of the appeal of serverless solutions, many cloud providers are expanding their tool sets and improving their existing serverless products. Datadog’s report noted that many companies are starting to extend their use of serverless computing beyond the traditional function-as-a-service (FaaS) such as AWS Lambda (which is the most common type of workload) and are now using serverless functions packaged as containers and fully managed container-based application platforms.

Datadog said that the use of serverless functions packaged as containers is likely growing in popularity because it simplifies the process.

Google Cloud is benefiting the most from this trend and leads AWS and Microsoft Azure when it comes to providing fully managed container-based serverless computing to its customers. According to Datadog, 66% of Google Cloud customers using serverless computing are using container-based serverless workloads such as Google Cloud’s Cloud Run, which it launched in 2019.

Datadog Chart serverless usage among hyperscalers

While AWS is far behind Google Cloud when it comes to its customers using container-based serverless workloads, it is seeing growth in this area. In 2022 Datadog found that only about 20% of AWS customers used fully managed container workloads. However, in 2023 AWS saw that grow 6% to 26% of its customer base.

Azure follows AWS with 22% of its serverless customers using container-based serverless workloads. However, Datadog noted that Azure only released Azure Container Apps in May 2022 and is catching up quickly. In fact, Azure saw the largest spike in container-based serverless platform adoption with 76% growth year-over-year.

Although the major cloud providers currently dominate the serverless market, Datadog noted that Vercel, Netlify, Cloudflare and Fastly now provide access to serverless frameworks. The report said that 7% of all organizations using Datadog to monitor their serverless workloads with major cloud companies are also using at least one of these smaller, emerging platforms.

Interestingly, the report also noted that Node.js and Python remain the dominant languages for AWS Lambda serverless functions. More than half of the programming in Datadog’s Lambda dataset are from functions written in Python or Node.js. Datadog said this was likely because these were the two earliest languages supported by AWS Lambda and both have a large community of developers supporting them.