Understanding serverless computing for beginners

When we talk about “serverless” computing, many people assume that this model has no servers to facilitate code execution and other development tasks. That’s a clear misunderstanding.

After busting this misconception, you may be wondering what the logic behind the name “serverless” is.

Let me give you a hint. Rather than “no server”, “serverless” requires how servers are managed and implemented.

Don’t you think it’s difficult to understand?

Well, to clear your doubts, let’s learn all about serverless and other terms related to it. First of all, serverless is becoming famous as we speak. In fact, the serverless market is expected to reach $7.7 billion by 2021, up from $1.9 billion in 2016.

So, let’s talk about serverless and consider the reasons behind its popularity.

What is serverless computing?

Serverless or serverless computing is a cloud-based execution model in which cloud service providers provision on-demand machine resources and manage servers themselves on behalf of customers or developers. It’s a way to combine services, strategies, and practices to help developers build cloud-based apps by allowing them to focus on code rather than server management.

Cloud service providers (such as AWS and Google Cloud Platform) take over all responsibility for managing common infrastructure tasks, from resource allocation, capacity planning, management, configuration, and scaling to patching, updates, scheduling, and maintenance. I will bear it. As a result, developers can focus their efforts and time on the processes and business logic of the application.

This serverless computing architecture does not keep computing resources in volatile memory. Instead, computing is done in short pieces. If an application is not in use, no resources are allocated to it. Therefore, you pay for the resources that your app actually consumes.

The main purpose of serverless modeling is to simplify the process of deploying code to production environments. In many cases, traditional styles such as microservices will also work. Once Serverless is deployed, the applications it runs begin responding quickly to requests and automatically scale up or down as needed.

Serverless computing uses an event-driven model to determine scaling requirements. Therefore, developers no longer need to predict application usage to determine the number of servers and bandwidth required. You can add servers and bandwidth based on your growing needs, without prior reservations, or scale down at any time without any hassle.

How has serverless evolved?

Traditional systems have challenges related to scalability and agility in the app development process and deployment. As time to market decreases and demand for high-quality apps increases, the need for better systems that can provide more scalability and agility begins to surface. As a result, cloud computing and serverless models have evolved.

The serverless model has evolved through various stages, from monolithic to microservices to serverless architecture or Function-as-a-Service (FaaS).

• Monolithic architecture is a traditional unified approach to software development. This is a tightly coupled model where each component and its subcomponents compile or execute code. If a service is defective, it can bring down the entire application server and the services running on it.
• A microservices architecture is a collection of smaller services within a single larger application that are independently deployed to perform specific functions. This enables rapid delivery of apps at scale and gives developers the flexibility to use Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). However, this model makes it difficult to choose between PaaS and IaaS.
• Serverless architectures evolve with cloud computing to provide greater scalability and business agility. Instead of IaaS and PaaS, use FaaS and Backend-as-a-Service (BaaS). Here, the app and its resources are deployed as needed. You don’t have to manage servers, and you can stop payments once your code is finished running.

Characteristics of serverless computing

Some of the attributes of serverless computing are:

• Most applications using serverless consist of a single function and small unit of code.
• Code runs only on demand, typically in stateless software containers, and scales seamlessly based on demand.
• No server management is required by the customer.
• It has event-based execution capabilities, creating a computer environment when a function is triggered or receives an event to execute a request.
• Flexible scalability allows you to easily scale up or down. Infrastructure execution stops once the code is executed, saving you money. Similarly, if a function continues to execute, it can scale up indefinitely if needed.
• Managed cloud services let you handle complex tasks such as file storage, queuing, and databases.

How does serverless work?

Serverless architecture combines two main ideas: Function-as-a-Service (FaaS) and Backend-as-a-Service (BaaS). It is based on FaaS and allows you to run your code on a cloud service without requiring a fully provisioned instance. FaaS consists of stateless, event-driven, scalable server-side functionality that is fully managed by a cloud service.

This model allows DevOps teams to write code that focuses on business logic. Next, define an event that can trigger the execution of a function, such as an HTTP request. As a result, the cloud provider runs the function and sends the results to an app where the user can view them.

In this way, the serverless model offers cost efficiency and convenience with autoscaling, on-demand, and pay-as-you-go capabilities. That’s why many companies and DevOps teams are moving toward serverless these days.

Who uses serverless and why?

Serverless is one of the newest technologies in software development. In the future, the need for infrastructure management and provisioning may be eliminated.

This is useful if:

• Organizations that want increased scalability and flexibility with better app testability can go serverless.
• Developers who want to build agile, high-performance apps to reduce time to market
• Companies that do not need servers to be running all the time. To save costs, your application can call module-based functions as needed.
• Organizations looking to build efficient cloud-based apps and simplify migration to the cloud
• Developers are looking for ways to reduce latency so they can provide users with access to some features and apps.
• Businesses that don’t have enough resources to deal with the maintenance and complexity of their IT infrastructure can adopt serverless computing, which automatically solves problems and requires no maintenance on their part.

Prominent users of the serverless model include Slack , Coca-Cola , and NetFlix .

The serverless model’s unique attributes make it suitable for many use cases, including:

• Web applications : You can use this model to build fast, scalable web applications that respond quickly to user requests. Ideal for building stateless apps that can get started quickly and apps that can handle unpredictable and infrequent spikes in user requests.
• API backend : Serverless platforms make it easy to convert any functionality into an HTTP endpoint that clients can consume. When these features or actions are enabled on the web, they are called web actions. Enabling these makes it easy to assemble functions into full-fledged APIs. You can also enhance security, domain support, rate limiting, and OAuth support with a suitable API gateway.
• Microservices : Serverless is widely used in a microservices model that focuses on building small services that perform a single function and can communicate with each other using APIs.
  Microservices can be created using software containers or PaaS, but serverless is more efficient. This facilitates short lines of code that do one thing, providing rapid provisioning, autoscaling, and flexible pricing that doesn’t charge customers when resources aren’t being used.
• Data processing : Serverless is ideal for processing data including video, audio, images, and structured text. It is also suitable for various tasks such as data validation, transformation, enrichment, cleansing, audio normalization, and PDF processing. It can be used for image processing such as sharpening, rotation, thumbnail generation, and noise reduction. Other uses of serverless in data processing include video transcoding and optical character recognition (OCR).
• Stream/Batch Processing : Create powerful streaming apps and data pipelines using FaaS and Apache Kafka databases. The serverless model is suitable for ingesting a variety of streams, including app logs, IoT sensors, business logic, and financial market data.
• Parallel computing : Serverless is ideal for tasks involving parallel computing, where each task runs in parallel to accomplish a specific task. This may include data retrieval, processing, map manipulation, web scraping, genomic processing, hyperparameter tuning, etc.
• Other uses : Serverless is also used for a variety of applications, including customer relationship management (CRM), finance, chatbots, and business intelligence and analytics, to name a few.

Note: Serverless may not be ideal in some cases. For example, large apps with predictable and near-constant workloads may benefit more from traditional system architectures. You can use managed or self-managed dedicated servers. Also, if your organization has a completely traditional setup with legacy systems and applications, moving to a completely new and different architecture can be expensive and difficult.

Advantages and disadvantages of serverless computing

There are two sides to every coin, and serverless architecture is no different. It also has some advantages and disadvantages based on various parameters. Therefore, it is important to understand both aspects and decide whether it is better for your organization before proceeding.

Advantages 👍

Here are some of the benefits of serverless architecture:

cost efficient

Serverless is more cost-effective than buying or renting servers, where you pay for resources even if you don’t use them.

Serverless uses a pay-as-you-go model where you only pay for the resources you consume. Serverless providers only charge for allocated memory and code execution time. Idle time has no cost.

The result is operational cost savings on tasks such as installation, licensing, maintenance, patching, and support. You also save on labor costs because you don’t need server hardware.

Scalability

Serverless systems offer a high level of scalability as they can be scaled up or down at any time based on demand. For this reason, it is also called “elastic”.

Here, developers do not have to spend dedicated time configuring and tuning autoscaling systems and policies. The cloud provider you choose is responsible for managing all of this. Additionally, small teams of developers can also run the code themselves without the need for support engineers or infrastructure.

Reduced waiting time

Your app is not hosted on a single origin server, so you can run your code from anywhere. If your cloud provider of choice supports it, you can run your app’s functionality on servers closer to your end users. Therefore, the distance between the user’s request and the server is reduced, resulting in lower latency.

productivity

Serverless models help developers be more productive because they don’t have to manage servers. You also don’t have to worry about managing HTTP requests or multithreading directly in your code.

As a result, backend development is simplified thanks to FaaS, where the exposed code is an event-driven function. All of this saves you time spent improving your code and applications.

Accelerate app deployment

With serverless, developers don’t need to perform backend configuration or upload code to a server to deploy versions of their app. You can also quickly upload bits of code and release new products.

It also has a non-monolithic architecture, giving you the flexibility to deploy code all at once or function one after the other. Plus, you can quickly patch, update, add features, and fix errors to your apps.

Other benefits include green computing by reducing energy consumption with on-demand servers, easier app building with built-in integrations, faster time to market, and more.

Disadvantages👎

Now let’s look at the drawbacks of serverless computing.

performance

In some cases, serverless code that is used infrequently can have longer response latencies than code that runs continuously on a dedicated server, software container, or virtual machine (VM). This is because it will take more time to redo it and may cause extra latency.

Difficult to debug and test

After you deploy your code, you need to know how it will run. This requires testing, which is difficult in a serverless environment. It also makes debugging more complex as developers lose visibility into each backend process and the app is split into smaller functions.

security issues

New and advanced cybersecurity concerns are growing. However, it is impossible to fully understand or measure a cloud provider’s security. Therefore, there is a risk when dealing with the entire backend containing sensitive data stored in the application.

Not suitable for long running application processes

Although serverless is cost-effective, it is not suitable for all types of applications. If you have an application with long-running processes, the cost of execution based on time and allocated resources can be very high. For now, we recommend proceeding with dedicated server hosting.

Other disadvantages of serverless include difficulty switching between vendors and privacy concerns.

Important terms in serverless architecture

Serverless would not be complete without explaining some important terms associated with it. FaaS and BaaS are two of the most prominent ideas that led to the evolution of serverless as we know it today. Building a serverless system also requires databases, storage systems, technology stacks, frameworks, and more. So let’s talk a little bit about them.

Function as a Service (FaaS)

FaaS is the core idea of ​​serverless and works like a subset of it. This event-driven code execution model (apps that run in response to requests) allows you to create logic that is deployed into software containers and executed on demand, and the cloud platform manages it for you.

Compared to BaaS, FaaS gives developers more control when creating custom apps rather than relying on libraries with ready-made code.

The software container in which the code is deployed is stateless to simplify data integration, reducing code execution time. Additionally, developers can call serverless applications through APIs using FaaS, which is managed by cloud providers through API gateways.

Backend as a Service (BaaS)

BaaS is similar to FaaS because both require a third-party service provider. In this model, the cloud provider provides backend services such as data storage, allowing developers to focus on writing the frontend code. However, BaaS applications may not be event-driven or run at the edge like serverless applications.

A good example of BaaS is AWS Lambda. Developers use serverless code in containers using Lambda, which provides guidelines to follow when submitting code. We also automate the process of entering code into software containers and provide managed services.

serverless stack

Like any other software technology, serverless architecture also comes with a technology stack. It brings together various components essential to creating a serverless system or application.

The serverless stack includes:

• Programming language: The programming language in which developers write code. Depending on the vendor, you can choose from Java, JavaScript, Python, C#, Go, Node.js, F#, and more.
• Serverless frameworks: Frameworks provide a skeleton or structure to your code. To get started with serverless frameworks, there are many serverless frameworks out there. This allows code to be built, packaged, compiled, and ultimately cloud deployed. Serverless frameworks expedite the coding process, reduce configuration time, and simplify scaling. Examples of server frameworks include Apex and the AWS serverless application model.
• Serverless database: Used to store data that your code needs to access. These are also required to interact with the trigger’s functions. These databases behave like serverless functions, but the data is stored indefinitely. Examples of serverless databases include DynamoDB, Azure Cosmos DB, Aurora Serverless, and Cloud Firestore.
• A set of triggers: Helps initiate code execution, such as an HTTP request.
• Software containers: Power your serverless model and deliver containerized microservices without the complexity. They also act as code repositories, making it easier for developers to write code for multiple platforms such as desktop and iOS.
• API Gateway: Acts as a proxy for web actions. Provides HTTP routing, rate limiting, viewing API usage and response logs, client IDs, and more.

How can I implement and optimize a serverless model?

Moving to serverless involves significant changes in applications, technology, costs, security, and benefits.

Suppose you are a start-up or small business. In this case, you can accelerate time to market and push updates faster with simplified testing, debugging, gathering feedback, and addressing issues to deliver polished applications to your users. Masu.

For large organizations, benefits such as increased scalability to meet user demands come at a significant cost investment.

Therefore, it’s best to evaluate the pros and cons of serverless, especially depending on your business type and demands, before proceeding. If you’re serious about it, start with:

• Understand your needs and identify the right serverless technology stack
• Choose a serverless vendor like Google Cloud Functions, Azure Functions, or AWS Lambda.
• Give your team powerful tools to monitor system performance and functionality. Pay attention to the total number of requests, throttling, number of errors, success rate, request duration, and latency.

serverless vendor

There are many serverless vendors and cloud providers on the market to choose from. Some of the top ones are:

• AWS Lambda: Ideal for organizations that already use AWS services. It integrates with a wide range of services such as storage, streaming, and databases.
• Microsoft Azure Functions: If you’re using Visual Studio Code, we recommend it. Works seamlessly with Azure Pipelines for DevOps and CI/CD. It also supports stateful Durable Functions and provides integrated monitoring.
• Google Cloud Functions: If you’re using Google services, that’s the way to go. It supports JS, Go, and Python apps, lets you trigger functions from Google Assistant or GCP, and offers built-in scaling.
• IBM Cloud Functions: If you prefer a serverless model based on Apache OpenWhisk, IBM Cloud Functions is the way to go. It includes powerful performance monitoring, event triggering from REST APIs or IBM cloud services, and integrates with IBM’s API Gateway to manage endpoints.
• Knative: If you’re running a service on Kubernetes, run it. Backed by Google, Red Hat, IBM, and more.
• Cloudflare Workers: Good for apps that require high responsiveness, especially JavaScript apps. It supports Workers KV for data storage and WebAssembly to help with multi-language compilation and delivery. Additionally, a highly distributed network with 193 data centers improves latency and responsiveness.

Conclusion: The future of serverless

Serverless computing is evolving with the increasing demand for highly scalable applications. It also offers many benefits that cloud computing offers, including increased convenience, increased cost efficiency, and increased productivity.

According to O’Reilly research , 40% of respondents work at companies that have adopted serverless architecture.

There are still concerns with serverless, such as delays due to cold starts, testing, debugging, etc., but cloud providers are addressing these issues. Soon, more sophisticated forms of serverless may surface with more benefits and problems solved. Therefore, the popularity and usage of serverless models is expected to increase in the future.

You may also be interested in: 7 ways serverless computing is an emerging technology