Ever feel like you’re spending more time wrestling with servers than actually building your app? This is why Serverless framework was introduced.
In this video, I’ll be guiding you through how you can use serverless frameworks to transform your business through increased reach, agility, faster time to market, and so much more.
The serverless framework is a type of framework belonging to the serverless architecture. This technology took the tech world by storm, making the development process more effective and allowing developers to build stronger applications with lesser strain on resources and time.
The serverless framework is a free, open-source command line interface (CLI) tool written in Node.js. It offers a structured way to build and manage serverless applications across different cloud providers, including AWS Lambda, Azure Functions, Google Cloud Functions, and others. The best part is that it’s not exclusive to a single process and can be applied to a range of processes like building web applications, data processing, and IoT backends.
When serverless computing first came to be, it changed application development entirely. It meant that you didn’t need Clunky, expensive, and hard-to-maintain infrastructure, and it is the sensible step forward for most companies. One of the key players in this process is the serverless framework, which abstracts away the complexities of working directly with cloud provider APIs.
So what’s the big fuss? Let’s have a look at some of the reasons why serverless frameworks are popular among developers.
Among many benefits, the first one on my list is faster to market.
When you use a serverless framework, it can free up your developers from dealing with time-consuming and boring tasks like server management and provisioning resources. Instead, they can focus on writing good code and business logic. This means the development and deployment processes are being streamlined, making way for faster testing and quicker deployment.
Another more popular perk of Serverless Frameworks is that they’re a breeze to scale. They automatically scale applications as the workload increases or decreases. Plus, with built-in cost management, you can scale confidently without breaking the bank.
Serverless frameworks generally come with a pay-per-use model, which means you just have to pay for the computing resources you actually use. While this slashes your excess costs, you won’t have to pay for maintenance as your provider will be handling it.
When you’re developing an application and launching it, you have to make sure that you have redundancy to minimize failures. Serverless frameworks give you the necessary redundancy, along with the support for multi-region deployments. So you’ll be able to serve their customers with latency and minimum downtime.
You can also read our blog about Serverless Database
A great way to understand how the Serverless Framework works is to look at a popular implementation. AWS is one of the most common platforms in which this framework is implemented.
The architecture of serverless applications using the Serverless Framework on AWS typically involves six key components. Let’s have a look at what they are.
Now let’s explore the main concepts of the Serverless Framework and how it integrates these components.
Functions
The first concept we’ll examine is functions. These are the core of any serverless application, serving as individual building blocks for specific tasks like processing HTTP requests or responding to cloud service events. In AWS implementations, these functions are typically executed using AWS Lambda.
Events
Next, we have Events. Events trigger your functions to execute. They are the actions your application responds to, such as HTTP requests via an API gateway, DynamoDB table updates, or scheduled time-based events.
Resources
Moving on to Resources. Every serverless application relies on certain cloud infrastructure components, which we refer to as resources. These might include S3 buckets, DynamoDB tables, API Gateway endpoints, IAM roles, and so much more. The Serverless Framework can use CloudFormation to automatically provision and manage these resources on AWS, ensuring consistent and reliable infrastructure.
Services
Now, let’s discuss Services. In the context of the Serverless Framework, a service is a way to organize your serverless applications. It’s essentially a project that contains both the configuration and the code for your serverless application. By organizing your application as a service, you can manage and you can deploy your service’s functions, events, and other related settings together. This modular setup makes it easier to maintain, scale, and deploy different components of your application separately.
Plugins
The final concept is Plugins. The Serverless Framework offers plugins that extend beyond basic functionalities. These plugins enable custom behaviors or integration with other tools. You can select from a variety of plugins for tasks such as deployment optimization, managing environment variables, or integrating with CI/CD pipelines. You can even develop your own plugins if you need specific functionality not provided by the existing options.
Step 1: Install and configure
First things first, you need to install and configure your serverless framework. I’m going to assume you already have Node.js and npm installed on your computer. If that’s ready, open up your terminal and run the ‘npm i serverless -g’ command. This command will basically install the Serverless Framework globally on your machine.
Next, you need to configure your AWS credentials to allow the Serverless Framework to deploy resources on your behalf. Type aws configure into your terminal and hit enter. You’ll be prompted to enter your AWS Access Key, Secret Access Key, region, and output format. Make sure to enter these details as they allow the Serverless Framework to interact with AWS services under your account.
Step 2: Create a serverless project
Now that you’ve got Serverless installed and configured, it’s time to create your first serverless service. Go back to your terminal and simply type serverless, just like that. And just press enter. You’ll see a list of templates on your screen. These templates are pre-configured setups for different use cases and programming languages.
Choose a template that aligns with your project needs and preferred programming language.
After selecting a template, you will be prompted to name your service. You’ll see a prompt that says ‘Name your service:’. Here, simply type in the name you want to give your service and then press enter.
Step 3: Sign in
Next up, let’s sign into your AWS serverless account. You’ll do this by simply running the ‘serverless login‘ command in your terminal.
This will automatically open up the Serverless Framework Dashboard right in your browser. Go ahead and enter your credentials there, and you’ll be logged in in no time.
Step 4: Deploy a service
Once you’re logged in, the next step is to deploy your service. First, you’ll need to navigate to your service directory, where your ‘serverless.yml’ file is located. Just switch to that directory using the ‘cd’ command followed by your service’s name.
Now, to deploy your service, run the ‘serverless deploy’ command. And just like that, ta-da! You’ve successfully deployed your service. It’s as simple as that!
And that’s it for the fundamentals! You now know how to set up your own Serverless Framework with some of the basic functions.
Next, we’re gonna take a look at in which cases the serverless framework works best.
One of the prime use cases for the Serverless Framework is event-driven applications. This framework is great at responding to events such as changes in data, user requests, or signals from IoT devices.
For example, you can set up automatic workflows to process files when they’re uploaded to Amazon S3. This might include tasks like resizing images, transcoding videos, or validating data formats. It also enables the processing of real-time data streams from Amazon Kinesis or DynamoDB Streams.
With the serverless framework, you can say goodbye to the hassle of maintaining dedicated servers for your automated tasks and scheduled jobs.
Take Amazon EventBridge, for instance. When you pair EventBridge with AWS Lambda, you can trigger functions at specific intervals for tasks like backups, system health checks, or periodic data aggregation. Plus, Serverless Framework empowers you to automate infrastructure management tasks like resource provisioning, monitoring changes, and updating configurations with ease.
The serverless frameworks have proven to be able to handle the creation and management of AI chatbots and voice assistants. In fact, it can do this much more efficiently with the use of Amazon Lex and Alexa.
Specifically, Amazon Lex’s natural language understanding and processing are really good. This makes them a great fit for creating AI chatbots that can understand and respond to inputs. This is supported by AWS Lambda, which will handle the backend logic.
You can use AWS Lambda with your serverless framework to extract, transform, and load data as you extract it from various sources. You can level up this functionality by combining AWS Lambda with Amazon Kinesis or AWS Glue to create real-time data processing pipelines for streaming analytics.
Read our blog Serverless vs Containers to know which one is best for your business.
We learned how serverless frameworks can help you completely revamp your businesses by adding agility, scalability, and cost efficiency. While Serverless frameworks free up developers from maintenance costs and let them focus on code, they also allow auto-scaling. We also went through the fundamental actions you would carry out when setting up your serverless framework as well as its core components and the best use cases.
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