There's a lot to love about serverless computing. It's scalable. It's cost-efficient. It minimizes effort required from engineers to set up and deploy software.
But serverless comes with some distinct downsides, too — and they're easy to overlook during discussions of all of the benefits that serverless has the potential to offer.
With that reality in mind, let's take a sober look at the reasons why serverless computing isn't always the right way to deploy software. As you'll learn below, although serverless functions certainly have their benefits, understanding their limitations is critical for making informed decisions about whether serverless is actually the right way to go.
What Is Serverless Computing?
Serverless computing is an approach to application deployment where engineers can run apps on-demand without having to configure or manage host servers themselves. It's called "serverless" because from the user's perspective, there are no servers to deal with; instead, the servers are provisioned and managed by the serverless computing provider.
Since Amazon's release of its Lambda serverless computing service in 2014, more and more businesses have turned to serverless to meet their application deployment needs. Today, all of the major cloud providers offer a serverless computing solution, and it's also possible to configure serverless environments in on-premises servers or private data centers.
As of 2023, serverless computing adoption rates were as high as 70%, at least for organizations using AWS. (Serverless usage on other clouds is lower.)
The widespread adoption of serverless computing reflects the ability of serverless architectures to deliver benefits such as the following:
- Simplified workload deployment: Engineers can simply upload the code they want to run and configure when it should run, without having to manage the host server environment.
- Scalability: In most cases, there is no practical limit on the number of serverless functions you can deploy at once, which means serverless can scale up and down easily based on workload requirements.
- Cost-efficiency: Typically, you only pay for serverless functions when they are actually running. This makes serverless a cost-effective model compared with running workloads on VMs and paying continuously to operate them, even if the workloads are not continuously active.
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