Serverless Computing: A Comprehensive Guide

Developers choose serverless computing over traditional approaches to building infrastructure, as it allows them to increase a system’s capability to handle increased workload and save costs. Unlike cloud-based or host-based infrastructure, it expedites the release and facilitates achieving higher flexibility. Enterprises no longer need to purchase backend servers and ensure their consistent performance, as they can entrust the task to reputable providers. In this guide, we will consider how the approach streamlines scalability and makes application development cycles shorter, making it suited for those who build applications with uneven traffic flow.

What is Serverless Computing?

This method allows users to create code without considering the backend services. Vendors charge clients depending on their computing needs. A provider keeps the infrastructure in working condition.

FaaS serverless models facilitate code execution prompted by events. Users do not need to purchase a certain bandwidth amount or number of servers. While hosts are still a part of every infrastructure, clients do not have to consider them when building apps.

Until recently, everyone who wanted to develop an app had to buy hardware and run a node. However, the approach became too costly and convoluted. Cloud computing became a possible solution, as it allowed app builders to rent remote servers and storage space. Nonetheless, businesses still had to acquire fixed amounts of resources that were fully used only during traffic spikes. The introduction of auto-scaling models helped partially address the issue and avoid unnecessary resource wastage.

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Serverless Computing vs PaaS

When comparing both models, one will instantly notice that Platform-as-a-Service backend architecture also has high transparency. However, these approaches are applied in different situations and are hardly equal in terms of scalability, pricing, tools, and startup time.

Apps scale automatically without delays. They don’t require programmers or vendors to take any extra steps to configure them, as resources are provided on demand. PaaS-hosted apps don’t scale by default. Developers need to predict potential resource usage.

FaaS pricing is more affordable, as one buys only the resources they consume. PaaS vendors rely on a similar approach, but they still may overcharge their customers, as they set a monthly fee.

What are the Key Benefits of Serverless Computing?

On-demand architecture streamlined automated resource consumption adjustment depending on current demand and helped firms to entrust vendors with configuration and management tasks. It has multiple notable benefits:

Higher developer productivity. Teams prioritize writing code and work without being distracted by management concerns. It permits them to come up with new ideas and build more advanced front-end solutions.
Lower expenses. One buys the resources they need after making a request until execution finishes. Serverless architecture is more cost-effective than the IaaS approach.
Multi-language environment. Coders can use any language and framework without considering compatibility issues.
Expedited DevOps cycles. Firms utilize the approach to streamline deployment. Developers spend less effort on integration, testing, and other production stages.
Low latency. Code runs close to an app user, making delays virtually non-existent.
Enhanced control. Programmers oversee the processes within a system due to its higher transparency and understand how users utilize the app better.

Despite the numerous upsides to switching to the model, one should be aware of the fact that they entrust a lot of tasks to a cloud service provider (CSP). A company no longer controls hardware or execution environments, which introduces some limitations. Besides, each vendor offers specific capabilities and tools that might not be supported by other CSPs. Furthermore, debugging becomes more complex, as developers don’t have access to back-end processes. Finally, such models are hardly suitable for prolonged execution, as they become more expensive during extended periods of use.

How to Use Serverless

The architecture is preferred by those who utilize microservices, rely on APIs, and focus on data processing. It allows firms to pay less and minimize downtime.

Microservices

The approach is all about creating specific services designed to perform a single task and communicate with others via APIs. Even though one can develop and operate microservices via PaaS or use containers, the model is more convenient to utilize due to its auto scaling capabilities, quick resource provisioning, and flexible pricing.

API Backends

Coders can turn any action or feature in a system into a web endpoint to make it accessible to clients. They deploy web actions to build a full-fledged API with a gateway for additional protection, bandwidth limiting, and custom domain support.

Serverless Computing: A Comprehensive Guide

Data Handling

On-demand computing streamlines working with organized text, audio, and visual data. It facilitates enhancing the value of collected information, validating it to achieve improved accuracy, and deleting outdated information. Coders utilize serverless to process PDFs, improve sound quality, enhance pictures, convert images to text using OCR, and convert videos in various formats.

Artificial Intelligence

The method enables one to run AI and ML workloads without delays. The architecture is often utilized by the creators of apps with smart features. It expedites innovation, enabling developers to achieve optimal performance.

Serverless Real-World Examples

This innovative architecture is used in many projects. Below, we have outlined the most successful cases of applying the approach.

IOT-Based Vending Machines

Coca-Cola was the first major corporation to switch to serverless to make its VMs more efficient. The decision helped it save thousands annually. Clients utilize smart solutions to place orders and pay online. They receive notifications on their phones via an app. Coca-Cola reduced its expenses on each machine by 66% and succeeded at handling 80 million queries monthly.

Equinox Media’s Fitness Solutions

The company launched VARIS and offered SoulCycle services to its clients to improve their indoor cycling experience. It relied on Amazon Kinesis to streamline data streaming, used AWS Lambda to deploy serverless architecture, and implemented AWS Glue solutions to expedite data loading. The strategy enables it to achieve better scalability while reducing costs. Recognizing dynamic usage patterns, on-demand systems make it unnecessary to develop useless infrastructure. ML suggestions and recommendations contribute to an augmented user experience.

Major League Baseball Advanced Media

MLBAM released its Statcast product to provide clients with quick access to detailed sports stats updated in real time. It’s widely considered one of the best serverless computing examples, as it permits users to analyze accurate data and utilize advanced search tools. It enables clients to consider such variables as pitch type and velocity, season, and player names. The solution simplifies analyzing baseball games.

BMW Event-Driven Analysis

Like other major companies, BMW was looking for an optimal way to store and organize the data it collects. Its ConnectedDrive backend server processes 1 billion requests daily. The company decided to build a centralized Cloud Data Hub to collect, manage, and analyze information. The developers built a multi-tiered account structure, where each client and data producer has a dedicated AWS account. It simplifies creating new use cases and ML models.

Autodesk App Development Solutions

The company creates advanced software for clients from design, construction, engineering, and other industries. It released Tailor to enable enterprises to create custom accounts with the specs and configurations they need. The AWS platform helped it minimize expenses and upgrade security. Tailor reduced the cost of account provisioning by almost 10 times. Lambda enabled the venture to diminish the price of installing security upgrades.

Slack Chatbots

Virtual assistants often receive too many requests simultaneously and have to solve complex tasks. Serverless approaches facilitate dealing with unpredictable increases in messages and scaling bandwidth consumption. Slack deploys cloud-based solutions powered by Lambda to ensure its chatbots will remain responsive.

Netflix On-Demand Libraries

The company was one of the first to adopt serverless computing. It deployed its first solutions back in 2017 when it developed a platform designed to withstand thousands of modifications daily. Its Dynamic Scripting Platform simplifies provisioning and end-user delivery. Publishers send hundreds of video files to the platform daily. Netflix needed a solution capable of encoding and categorizing them quickly.

The platform built a system designed to break every file into 5-minute segments and encode them into the 60 parallel streams. It enables Netflix to aggregate and disassemble each video to meet streaming demands. The company also utilizes Lambda to build backups and guarantee that its products are built in accordance with existing rules.

These applications highlight the impressive potential of serverless computing across various spheres. The fast-paced adoption of this architecture demonstrates increasing interest in solutions, enabling ventures to build and deploy apps without excessive expenses. Global Cloud Team assists customers with AI software development and helps them deploy advanced AI models to achieve their business goals. Its professionals specialize in a range of cloud services. They use their expertise to help SMBs, large ventures, and organizations achieve sustainable growth.