Datadog believes serverless computing is going mainstream

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New report from DataDog found that serverless computing could go mainstream, with more than half of all organizations using serverless computing in one of the three major clouds – Amazon, Microsoft, or Google.

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The company found in a 2020 report that while some customers used lambda, Amazon’s function as a service, other clouds have lagged behind. This year’s report found that DataDog users were using serverless technologies across all three clouds, with Amazon leading at over 70% and Microsoft and Google at over 50%, indicating they have become widespread across all major cloud platforms. . .

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Another key takeaway from the report was that companies often used serverless technologies in combination with containers, two technologies. that seem to fit well each other. Containers often have a limited shelf deployed for as long as needed, while serverless solutions offer the beauty of automatic resource deployment.

In fact, the report showed that 20% of Lambda users deployed Lambda functions through a Docker container. It’s a combination of serverless and containers that we may not have envisioned, but it’s becoming a matter of course. When the report looked at the growth in usage of this approach, it was found that it had grown from 0% of Lambda users using this deployment method in January 2021 to 20% by January 2022, and the trend is on a significant upward trajectory.

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Image Credits: DataDog

While the report found other interesting facts, it also found that the vast majority of the Lambda functions flowing through its systems were used to call a single API gateway and nothing else, which is in line with what DigitalOcean’s Gabe Monroy told us in launch of his company’s Functions as a Service 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 some function-oriented APIs that work alongside the same app, connecting to the same datastores they need,” said us Monroy. at that time.

The benefit of serverless technologies in general is that developers don’t have to worry about provisioning resources at all and can just write code,” says Ilan Rabinovitch, senior vice president of product and community at DataDog.

“Every one of the cloud providers is starting to offer ways to run your containers as a serverless mechanism where you don’t have to worry about that infrastructure, and even in terms of features they allow you to push containers as a deployment mechanism. So instead of downloading a zip file to run a Lambda function, you download a Docker container and they will run it for you as well,” Rabinowitz explained.

Alex Kuochi, serverless product manager at DataDog, says the increase in tools across platforms is making serverless solutions more accessible, and so they’re being used more and more. “What we heard from our customers, and we tried to highlight it in the report, is that these new technologies reduce the time and resources for teams to adopt serverless technologies for the first time, which opens them up a lot more for organizations and the team,” said Kuochi.

Serverless computing represents the ideal state of cloud computing where you use only the resources you need and nothing more. This is because the cloud provider only provides these resources when a certain event occurs and disables it when the event ends. The point is not the lack of servers, but the fact that they do not need to be deployed, because the provider will do it for you automatically.

When people started talking about cloud computing around 2008, one of the benefits was elastic computing, or only using what you need, scaling up or down as needed. The developers don’t really know what they need, so they often allocate too many resources to keep the app running.

The company created a report based on the data passed through its monitoring service. While it only represents the activity of its clients, Rabinovitch views it as qualitative data given the wide range of clients that use its services.

“We really think we’re well represented in the industry and we think we’re representative of real-life manufacturing workloads,” he said. This means that most likely people aren’t monitoring workloads but are only dabbling in serverless tasks, and this adds value to the data.

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