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container deployment vs serverless

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Hamish Lister

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Hamish is a senior content manager at Ostride Labs. Hamish’s diverse background in technical research, analysis and market demand are the main drivers behind the topics he enjoys exploring and writing about.

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Container Deployment vs Serverless

Updated 28 Jul 2022

Container deployment and serverless computing are two of today’s hottest technologies for application deployment. They both assist DevOps teams in building and deploying applications more quickly, with greater flexibility, and for less money when utilized properly.

Despite certain similarities in their characteristics, serverless frameworks and containers are two different types of technology. For some use cases, containers perform better, while for others, serverless is the way to go. Depending on the requirements of the application, a developer should choose a certain architectural style.

This article compares and contrasts container deployment with serverless computing services and shows why, based on their requirements, a DevOps team might pick one technology over the other.

What is ‘Serverless’?

An execution architecture known as serverless computing allows application code to be run as needed. From the user’s point of view, uploading the code and setting an execution time are the only tasks required to run it. Because there is no server to maintain within a serverless framework, this technology is known as serverless.

The key benefit of serverless is that it frees users from ongoing host environment maintenance by enabling them to run programmes whenever they need to. When running resource-intensive code, in particular, this can help you save money.

What are Containers?

Containers are a lightweight virtualization architecture, to put it simply. In portable, isolated settings, you can use them to deploy particular apps (or, in some situations, entire operating systems). Deployment meaning in work and business situations can be sumerized as moving software from one controlled environment to another.

Containers are more effective than virtual machines because they share system resources with the host server rather than simulating a virtual operating system.

Additionally, containers offer frictionless application deployment by separating an application from the external host environment. You can deploy containerized applications on your host server without worrying about fiddling with the application set-up or battling with environment variables as long as your host server supports the container runtime you use. The same logic applies to moving containerized applications between hosts.

Similarities Between Containers and Serverless Computing

Serverless frameworks and containers are not the same technology. They do, however, offer some functionality that overlaps:

  • You can deploy application code using both.
  • Both are cloud-based. 
  • Compared to virtual machines, both are more effective.
  • Both drastically cut down on infrastructure costs.
  • Both insulate the host environment from the applications.
  • To be used efficiently at scale, both require orchestration tools.

Differences between Serverless and Containers

Apart from the few similarities listed above (and in the table at the bottom), serverless and container deployment are very different technologies.

  • Supported host environments: Windows and some current Linux servers are both capable of running containers. Serverless, in contrast, operates on certain host systems, the majority of which are based in the public cloud, such as AWS Lambda.

 

  • Statefulness. Stateless workloads are supported by the majority of serverless platforms. Although serverless solutions allow connections to external storage services (such as S3 on AWS), the functions themselves cannot be stateful. Although containers have their own persistent storage issues, it is still possible to build stateful containerized apps.

 

  • Time of deployment: Setting up containers initially takes longer than setting up serverless functions since system settings, libraries, and other things need to be configured. Containers deploy quickly once they have been configured. However, serverless functions only require a few milliseconds to install because they are system independent and smaller than container microservices. Applications that don’t use servers can go live as soon as the code is uploaded.

 

  • Costs: You must pay to use serverless environments because they are hosted in the cloud. In contrast, you can create a container environment on your own for nothing using open source technology (although, of course, maintenance expenses will still apply).

 

  • Physical machines – Although “serverless” computing is actually executed on servers, no particular machines are designated for a given function or application; instead, it is up to the serverless vendor to offer server space as needed by the application. However, each container only exists on one machine at a time and uses that machine’s operating system, but they can be readily relocated to another machine if needed.

 

  • Self-servicing ability: Because of the aforementioned factors, using serverless operations typically necessitates using a public cloud. (On-premises serverless frameworks exist; Fn is one; however, they are not yet commonly used.) You can create your own on-premises host environment using containers, or you can use a public cloud service like ECS.

 

  • Availability. The lifespan of serverless functions is often limited to a few hundred milliseconds before they expire. The duration of a container’s operation is up to you.

 

Use Cases

Serverless and containers are designed for different use cases as a result of the distinctions mentioned above.

Containers are useful in the following circumstances:

  • As application code flows down the delivery chain, it maintains environment parity.
  • The ability to transfer workloads between on-premises and the cloud.
  • Quickly switch between multiple host servers while moving apps.
  • Makes services continuously accessible.

Serverless is fantastic when you want to:

  • Without needing to set up a virtual server or pay for continuing cloud resources, run limited amounts of application code in the cloud.
  • Swiftly run resource-intensive programmes on an individual basis. For instance, serverless can be a terrific method to execute code to resize photographs whenever users upload them. 

How should DevOps decide between serverless architecture and container deployment?

A serverless architecture will allow developers to swiftly release and iterate new applications without worrying about the applications’ scalability. Serverless computing will also be more economical than containers if an application does not experience consistent traffic or usage because the code does not need to be running all the time.

Containers provide developers more control over the language and library used, as well as the environment the application runs in (although this also requires more maintenance). Because it is feasible to more nearly mimic the application’s original running environment, containers are very helpful for moving legacy applications to the cloud.

Finally, a hybrid architecture that deploys some serverless functions and other containerized functions is an option. A hybrid architecture enables developers to take advantage of serverless while continuing to use containers for the functions serverless cannot support, for example, if an application function requires more memory than the serverless vendor has allotted, if a function is too large, or if some functions but not others need to be long-running.

Conclusion

It is preferable to consider containers and serverless frameworks as complementary technologies rather than as alternatives to each other. Not one or the other, but both are likely to be used by the majority of organizations. In fact, you might even deploy the same application with the help of both technologies.

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