Datadog finds serverless computing going mainstream – TechCrunch

A new report of Datadog found that serverless computing could enter the mainstream with more than half of all organizations using serverless on one of the three major 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), other clouds were lagging behind. This year’s report showed that Datadog users were using serverless technology across all three clouds, with Amazon leading with over 70% and Microsoft and Google each over 50%, showing that it has widely used in all major clouds. platforms.

Another key point from the report was that companies often use serverless technology in conjunction with containers, two technologies that seem to be a good fit for each other. Containers often have a limited shelf deployed for as long as needed, while serverless offers the beauty of automated resource deployment.

In fact, the report found that 20% of Lambda users deploy Lambda functions through a Docker container. It’s a marriage of serverless and containers that we may not have envisioned, but that makes perfect sense. When the report looked at the growth in the use of this approach, it found that it went from 0% of Lambda users using this deployment method in January 2021 to 20% in January 2022, a trend that is on a significant upward trajectory.

Picture credits: Datadog

While the report revealed some other interesting insights, it also found that the vast majority of Lambda functions passing through its systems were used to call a single API gateway and nothing more, which is consistent with what Gabe Monroy from DigitalOcean told us at launch. of his company’s FaaS product last month.

“A developer can run a Django app or a Ruby on Rails app running in containers on our platform, and then augment it with function-oriented APIs running alongside that same app connecting to the same data stores whose they need,” Monroy told us. at the time.

The beauty of serverless as a whole is that developers don’t have to worry about provisioning at all and can just code, says Ilan Rabinovitch, vice president of product and community at Datadog.

“Each of the cloud providers are starting to come up with ways to run your containers as a serverless mechanism where you don’t have to worry about that infrastructure, and even on the feature side they allow you to push containers as a mechanism so instead of downloading a zip file to run a Lambda function, you download a Docker container, and they will also run it for you,” Rabinovitch explained.

Alex Cuoci, product manager for serverless at Datadog, says the increase in tooling across all platforms is making serverless more accessible, and that’s why they’re being used more and more. “What we’ve heard from our customers, and we’ve tried to highlight this in the report, is that these new technologies reduce the time and resources for teams to adopt serverless for the first time, which opened up a lot more to organizations and teams,” Cuoci said.

Serverless represents the ideal state of cloud computing, where you use exactly the resources you need and no more. This is because the cloud provider only provides these resources when a specific event occurs and shuts it down when the event is over. It’s not a lack of servers, as much as not having 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 will need, so they often overprovision to ensure the app stays up and running.

The company created the report based on data received from its monitoring service. While it only represents the activity of its clients, Rabinovitch sees it as quality data given the wide range of clients who use its services.

“We think we’re well represented across the industry as a whole, and we think we’re representative of actual production workloads,” he said. This means that people are probably not monitoring workloads where they are just trying their hand at serverless which adds even more value to the data.

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