A new report from data dog has found that serverless computing could become commonplace with more than half of all organizations using serverless on one of the three main clouds: Amazon, Microsoft and Google.
The company found in a 2020 report that while some customers were using Lambda, Amazon’s function as a service (FaaS), the other clouds lagged behind. This year’s report found that Datadog users were using serverless technology across all three clouds, with Amazon leading the way at more than 70% and Microsoft and Google each by more than 50%, demonstrating its boom in business. all major cloud platforms.
Another key point in the report was that companies often used serverless technology in combination with containers, two technologies that seems very appropriate to each other. Containers often have a limited shelf to deploy for as long as needed, while serverless offers the beauty of automated resource deployment.
In fact, the report found that 20% of Lambda users implemented Lambda functions through a Docker container. That’s a marriage of serverless and containers that we may not have envisioned, but it comes into its own. When the report looked at the growth in adoption of this approach, it found that it grew from 0% of Lambda users using this implementation method in January 2021 to 20% in January 2022, a trend that is on a significant upward trajectory. .
While the report revealed other interesting tidbits, it also found that the vast majority of Lambda functions coming through its systems were used to call a single API gateway and nothing more, something consistent. is with what Gabe Monroy of DigitalOcean told us on the launch of his company’s FaaS product last month.
“A developer can run a Django application or Ruby on Rails application in containers on our platform, then augment that with some function-oriented APIs that run alongside that same application and connect to the same datastores they need,” Monroy told us. . at the time.
The great thing about serverless in general is that developers don’t have to worry about provisioning at all and can just code, says Ilan Rabinovitch, SVP of product and community at Datadog.
“Each of the cloud providers is starting to offer ways that you can run your containers as a serverless mechanism where you don’t have to worry about that infrastructure, and even on the functional side they allow you to use push containers as a deployment mechanism. So instead of uploading a zip file to run a Lambda function, you upload a Docker container, and they will run that for you too,” explains Rabinovitch.
Alex Cuoci, product manager for serverless at Datadog, says the proliferation of tooling across platforms is making serverless more accessible, which is why they’re seeing more use. “What we’ve heard from our customers, and we’ve tried to emphasize this in the report, is that these new technologies reduce the time and resources for teams to go serverless for the first time, opening up much more to organizations and teams.” ”, said Cuoci.
Serverless represents the ideal state of cloud computing, where you use only the exact resources you need and no more. That’s because the cloud provider only provides those resources when a specific event occurs and shuts them down when the event is over. It’s not a lack of servers, but it’s that you don’t have to deploy the servers because the provider handles that for you in an automated way.
When people started talking about cloud computing around 2008, one of the benefits was elastic computing, or using only what you need, scaling up or down as needed. In reality, developers don’t know what they need, so they will often overprovision to keep the application running.
The company created the report based on data running through its monitoring service. While it only represents the activity of its clients, Rabinovitch considers it quality data given the wide range of clients it has using its services.
“We think we are well represented across the industry, and we believe we are representative of the real production workloads,” he said. That means people are most likely not monitoring workloads where they’re just serverless, adding even more value to the data.