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  4. Serverless Computing vs. Containers

Serverless Computing vs. Containers

As the two most emergent cloud technologies on the market, is it necessary that they be pit against each other, or can they work together?

Ankit Kumar user avatar by
Ankit Kumar
CORE ·
May. 06, 19 · Analysis
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Technology has never ceased to amaze! Of course, not all technologies are accepted popularly by enterprises the world over. But, two amazing breakthroughs have proven their mettle and continue to rule the IT industry. Containers and Serverless computing both are the technologies that have to impress developers with their inherent features.

Are they similar? Do they have any dissimilarity? Which one is better? Which one to be chosen and when and why? There are many questions popping up as these advancements garner increasing popularity.

What is observed and known openly is both have a lot of things in common, yet there is a gap between the two that may not be able to cross over. Both have their own set of success stories to tell and certain pain areas too. Here are common features of both:

  • Both provide productive, machine-agnostic abstractions for IT engineers

  • Both offer a modern, future proof architecture

  • They leverage the newest modernization in distributed systems and large-scale software development

  • They both build a slick, robust and scalable architecture

  • Both enhance the productivity level of developers to a great extent

On a usual note, we see enterprises adapting to revolutionary technologies at a slow pace. But, looking at the popularity charts of the two, Serverless and Containers, it is an obvious fact that both have had their share of acceptance by end users.

Now that we know what is common in both, let us study each one in detail to understand them in-depth.

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Serverless And Container Technology – An Introduction

Serverless Computing

46 percent of IT decision makers are using and evaluating serverless, while 35 percent alone are evaluating serverless computing, a ten-point increase year over year.

Serverless Computing is a robust development methodology that substitutes virtual machines with compute power as and when required and moves away after the usage is over.

Serverless does not mean there is no server involved. There are servers included but they are managed by the cloud service provider like AWS, Azure, or Google Cloud Platform. It is a cloud-based computing service and like all functionalities in the cloud, it runs on servers when needed.

You can go in for event configuration like API requests or file uploads triggering your serverless function and as soon as the event is complete, the server will go idle until the next action. The serverless computing service provider takes care of everything on the server side. You just need to do code writing and deployment.

Assumed to be a Function-as-a-Service (FaaS), serverless is reliable if there are unexpected traffic spikes that need to be immediately handled. In an absence of traffic, there is no work done on the application and it turns out quite cost effective.

There are certain characteristics of a serverless architecture like auto-scaling, nil administration, event-driven workflow, stateless functions and pay as per usage that increases its demand amongst users.

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Examples:

  • Code execution without server management with Lambda

  • Host static websites on S3 with serverless databases like DynamoDB

  • Cron jobs where there is regular scheduling of functions at a specific time

  • Ideal for short-running processes, Microservices architecture, data stream/image processing, web APIs

Container Technology

Gartner predicts that by 2022, more than 75% of global organizations will be running containerized applications in production, which is a significant increase from fewer than 30% today

The container technology focuses towards remote stateless environments that help in extracting away variances in OS distributions and basic infrastructures. Containers are lightweight, independent, executable packages of software that encompass all elements needed to run it like code, libraries, system tools, and runtime.

It is like a virtual machine, simulating a real machine with many similarities, but significant architectural variations. Containers execute on a unified OS kernel isolating itself from the environment when moved from a single computing background to another.

Image title

Image Courtesy: Container-Technology-Adoption-Statics

Example:

  • Moving software solution from development to staging to production smoothly irrespective of environmental differences

  • Refactoring existing monolithic apps to container-based setups

  • Ideal for Web APIs, machine learning calculations, long-running progressions

How Does Serverless Computing And Container Technology Work?

How Does Serverless Work?

  • Write code in different languages like Java, Go, C#, Python, Ruby, etc.

  • Set basic configuration parameters

  • Upload all that is needed with dependent parameters

  • Execute the function by calling it from an app running on the service

  • Deploy the function in a container that works until your job is done

  • Serverless works in the background taking care of everything except for providing the code

  • It is in charge of provision, deployment and managing the container that is being used

How Does Container Technology Work?

  • Disseminates a large and complex monolithic app into container based microservices

  • Tailors the novel architecture based on the requirements of the new system

  • Offers total control over distinct containers, the entire system, and the virtualized infrastructure on which it executes

  • It sets policies, performs resource management and marks high-end security over the entire setup

  • It optimizes the usage of container management and migration offerings

The Good And The Bad – Serverless And Container

Pros And Cons Of Serverless

Advantages Of Serverless

  • You pay for the time when the server is executing the action thereby saving big time, i.e. pay per execution

  • Facilitates the app's flexibility and scales up and down up to multiple concurrent users, thereby increasing app performance

  • Saves on time spent in server management

  • The cloud service provider takes care of everything about provisioning infrastructure and managing downtime

  • Faster go-to-market time

  • Reduces development time

  • Adjusts well with microservices and helps developers build their own instances

  • No need to offer specific cloud servers, giving it more availability

  • Serverless functions are small, simple and have little overhead

  • They are low in maintenance, offer automatic scaling, manual scaling as needed, i.e. autoscaling

  • Zero administration

  • Pointedly condensed administration and maintenance load

  • No security patches, no OS updates to handle as the provider does it all

Disadvantages Of Serverless

  • Not many third-party tools available for observability

  • May take some time for the container to spin up, cold startup or latency could be experienced

  • Fixed limits for processing power and memory

  • Functions may get overloaded and hence needs better coding

  • Vendor lock-in is a matter of concern

  • Not fit for long executing apps as it has time limits prior to termination

  • Less control over the server and hence tough to build complex apps

  • Needs a lot of coordination and dependency management within all serverless functions

Pros And Cons Of Containers

Advantages Of Containers

  • Highly portable, can combine apps and their dependencies and execute it anywhere

  • Total control over your application and virtualized infrastructure

  • Easy to manage security policies, container environment, resources, and deployment

  • Can be as large and complex as needed without any restriction on memory or time

  • Effective and inclusive debugging and testing with a wide range of resources

  • Performance fine tuning can be easily done on a microservice level

  • Complete analytics can be implemented in detail at a drill down level

  • Vendor-agnostic, flexible and has an easier migration strategy

Disadvantages Of Containers

  • No auto-scaling available, so you need to set it up and manage yourself. 

  • Has a certain amount of complexity since more manual intervention is needed

  • Could lead to increased costs, time and efforts because of the extra efforts put in

  • Running costs could be higher because of payment for server resources even when not needed

  • Development process could be slower due to the self-management of containers

  • Monitoring of scattered and constantly changing containers is a challenge

  • Tough to ensure data and storage scalability

Which To Choose And When?

Serverless Computing Is Recommended When:

  • You need apps that are all set to perform tasks but don’t need to be running all the time

  • You have IoT-based applications that get activated only in certain situations

  • Development speed and cost optimization are of prime importance

  • There is a need for auto-scaling

  • There is a requirement for tying into legacy systems that handle specific business logic

  • You need to handle high-volume backend tasks for websites and mobile apps

  • There are resource intensive real-time procedures, data streaming, and uploads

  • There is a need to move data to long-term storage and perform detailed analytics over it

Container Technology Is Recommended When:

  • There are complex and long-executing applications and you require a high level of environment control

  • You need to migrate monolithic legacy apps to the cloud (Kubernetes and Docker Swarm are useful for this) or into a containerized environment

  • You need to work for an eCommerce website which needs container wises packaging of services with no time or memory limits

  • There is a need for flexibility and total control over the system

  • You wish to have the chance to choose your OS and the programming language

  • You want the system to automatically handle the traffic hassles

Can Serverless And Container Technology Work Together? An Unbiased Analysis

Serverless and containers can complement each other to offer a rewarding experience to users. Serverless computing can work with containers, rather than replacing them, since it cannot be a substitute for container deployment and management. There could also be a huge complex application with container-based architecture in which there could be some backend tasks like data transfer and backup that can be performed with the serverless mechanism.

There are tools which can combine the portable nature of containers with the ease of use that serverless offers. In the case of large complex systems, containers can offload background/outside tasks to serverless without binding their own resources. In the same way, serverless can offer services to disparate clients and can be managed independently without any container intervention

For work areas that are long-executing, need more resilience and execute at a uniform level constantly, containers could do the job, and for all other work areas, serverless could chip in to do the rest.

Wrapping It Up

Being constantly compared, Serverless and containers are inseparable from each other now and as we read, have turned out to be mutual supportive technologies. In the continuously-evolving technological era, both these methodologies are proving their worth and bringing out the best in each other.

Our article has attempted to highlight detailed nuances of each, the pros and cons of each, when to use what, and what they can go together. What is needed is a balanced equilibrium between the two based on project needs. You can choose either or both, depending upon the various factors as discussed above. If statistics are to be believed globally, a hybrid approach would turn out best. But then, to each its own!

Docker (software) Serverless computing Computing

Published at DZone with permission of Ankit Kumar. See the original article here.

Opinions expressed by DZone contributors are their own.

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