Serverless vs. Containers: Which is Right for You?
It’s worth taking the time to fully understand and compare Serverless vs. Containers technologies from a day-2 operations perspective. Discover more with Control Plane.
Serverless architectures make application infrastructure almost infinitely scalable, fast at runtime, cost-effective, and most importantly – someone else’s job. It’s no wonder cloud-native businesses and developers choose serverless almost by default. Nearly 75 percent of AWS users employ serverless architectures. So why are we still comparing serverless vs. containers in 2023?
Earlier this year, the Amazon Prime Video tech team announced that they have effectively scaled up the Prime Video audio/video monitoring service while reducing costs by 90%. How did they do it? By switching from a serverless architecture to a containerized application on the Amazon Elastic Container Service application.
Even the champions of serverless, Amazon, admit that in some cases, containers are a more suitable choice for cloud-native applications. So it’s worth taking the time to fully understand and compare the two cloud technologies from a day-2 operations perspective before adopting one.
What are containers?
A container is an isolated software package for a service or an application developed and bundled for cloud deployment, execution, and portability.
Your typical container bundle will contain the application and its dependencies, along with runtime and system tools, libraries, and settings, encapsulating them into a single, self-contained portable package that can be executed in any environment.
A containerized architecture enables you to create applications composed of multiple function-specific containers. For example, your web server, backend, and database can each reside in a container.
The most popular containerization platforms in 2023 include Docker, Kubernetes, GCP Autopilot, and Amazon ECS.
How do containers work?
Developers create container images to include instructions on how to run the container. The container engine can then use these instructions to spin up the container into a server that will run the application in an isolated and stable environment on demand.
Containerization – Pros and Cons
The benefits of containers
- Streamlined deployment processes – Since the container can be deployed to virtually any type of infrastructure and contains the application code and the software resources and dependencies needed to run it, it expedites the process of code-to-cloud.
- Scalable, lightweight, and resource-efficient – You can spin up a container in moments, run multiple containers on a single cloud instance or virtual machine, and scale on the fly. You can employ the same infrastructure to distribute and operate various applications according to your business needs and resources, scaling up and down as needed.
- Cross-vendor portability – Containers are CSP agnostic and can run on local servers and public, private, and hybrid clouds, making migration easier and enabling multi-cloud platform support.
- Extensive ecosystem and community – The ecosystem around containers has evolved to offer a broad range of services and tools to set up, monitor, debug, and optimize your containerized infrastructure at scale.
The cons of containers
- DevOps overhead and complexity – What puts the con in containers is, first and foremost, the human resources they require to set up and efficiently scale a containerized app architecture. Containers don’t scale automatically, so you must employ (and learn) the tools necessary to orchestrate all the moving parts of your containerized infrastructure.
- Unlimited resource consumption by default – This may sound like an advantage rather than a drawback. However, neglecting to specify resource limitations at runtime can lead to a world of trouble in resource-intensive scenarios. If your container consumes as many resources as the host system allows, it can result in performance issues, system failures, or exacerbated costs in cloud-native applications.
- Security – To ensure the safety of containers, you will need to implement strict policies and protocols, as a vulnerability in one container can make other containers hosted on the same infrastructure just as vulnerable to attacks.
What is serverless?
Serverless application architectures are an extension of the cloud computing model and a further abstraction of the containerized application architecture and model. Unlike containers, serverless functions do not require developers to spend time manufacturing bundled virtual machines.
The term “serverless” doesn’t mean your application doesn’t run on a server, but rather that you don’t have to set up or manage a server to run functions or services – the cloud provider does it for you.
With serverless, runtime events can trigger the execution of units of code (functions) on demand, scaling infrastructure requirements as needed and freeing developers to focus on application development rather than DevOps overhead.
All major cloud providers offer their framework for serverless software architectures – Amazon Web Services (AWS) features Lambda, Microsoft Azure has Azure Function, and Google Cloud Platform (GCP) offers Cloud Functions.
How does serverless computing work?
With serverless, developers are freed from building, managing, and scaling the infrastructure needed to run their code. When you call a serverless function, the cloud service provider (CSP) will spin up a container to run the applications and libraries to execute the process, with all the underlying infrastructure creation and management transparent to the developer.
Serverless architecture – Pros and Cons
The benefits of serverless
- Lower maintenance and DevOps overhead – Since infrastructure administration, maintenance, and scaling are, for the most part, the job of your CSP, you are free to focus on strategic and mission-critical tasks. This shortens the time from code to cloud, accelerating the entire cloud-native software development lifecycle.
- Increased reliability, fault tolerance, and automated scaling – Another benefit of entrusting infrastructure maintenance to your CSP is the combined level of reliability and ease of scalability it enables. Additional serverless function instances can be created depending on request load and scale automatically within predefined limits.
- Cost efficiency – Unlike containerized applications, CSPs bill for serverless functions according to used resources, so you don’t end up paying for idle time when there’s no traffic. However, serverless costs don’t increase with usage, but they can get more expensive as you scale. That happened with Amazon Prime Video and was the key reason they moved to a monolithic architecture despite being serverless champions.
- Can run as a microservice – Serverless functions can run as microservices of containerized applications to handle a specific role.
Cons of serverless
- Vendor lock-in – As mentioned above, each cloud vendor offers their vendor-specific serverless framework, making it incredibly challenging for multi-cloud application architectures and vendor migration. You can overcome this by employing Control Plane to enable a cross-vendor serverless workload execution while lowering your cloud expenses.
- Less control – The freedom from DevOps overhead is a double-edged sword. Less control also means you’re more dependent on your CSP to fix issues like misconfigurations and broken network connections. Providing highly reliable, low-latency geo-routed infrastructure while optimizing for cost-efficiency in near-real-time requires much granular and manual configuration across multiple CSP platforms. You can turn to an all-clouds-in-one internal developer platform to regain control of your serverless infrastructure without increasing DevOps overhead.
- “Cold starts” and latency – Function-as-a-Service (FaaS) is notoriously slow to load initially (“cold start”) as the first time the serverless function is called, the CSP needs to spin up a container to serve it. Cold starts could take up to several seconds, so your application will respond slower and affect user experience. Another cause for latency can be overloaded functions that have inflated due to wrong code that does not adhere to serverless best practices. Control Plane offers an intelligent DNS geo-routing that connects a customer’s request to the nearest healthy container based on their location and network, resulting in low latency and 99.999% availability.
- Added architectural complexity – Serverless functions are best suited for intermittent execution when triggered by an event – not frequent and concurrent invocations. When a function is called concurrently from multiple sources, you must balance the latency and performance by enabling provisioned concurrency. However, suppose you’re not careful about specifying serverless functions’ concurrency settings. In that case, you may find yourself with a serverless function that will likely be more expensive than running the same function from a container. Moreover, running integration tests on an application that calls many serverless functions is a painfully unpleasant experience.
Serverless vs. Containers: Key Differences and Similarities
System control & management overhead
With containers, you have much more control over the infrastructure, resources, and costs, which may provide more granular control, security, easier migration, and more streamlined testing and debugging. This can lengthen the time to market and add significant DevOps overhead.
On the other hand, serverless functions leave the infrastructure overhead to the service provider, letting developers focus on their code and significantly shortening the time from code to the cloud.
Container execution is billed according to the duration of use in a pay-as-you-run model, even when there is no traffic. The serverless pay-as-you-go model bills you for the time, memory, and computation resources the function consumes.
Containers have portability in mind and are typically built on Linux, enabling container portability across distributions. In contrast, portability with serverless is a lot more complex. Since each vendor has a unique offering and approach to handling API requests, you will need a serverless virtualization tool like Control Plane to port your workloads across vendors without complex code adaptations.
Effortless cross-vendor cloud synergy with Control Plane
Generally speaking, serverless functions are best suited for compact, event-based operations, and containers offer more portability and control over application runtime and performance. But why not both?
With Control Plane, you can get the best of containers and serverless across all cloud vendors with a single API that lets you manage your entire infrastructure in one codified infrastructure orchestration platform. Enabling cost optimization and unbreakable workloads with low latency to all users, Control Plane allows you to build your application for all clouds while minimizing spend and DevOps overhead.