Cloud computing has changed everything. It’s made web development faster, cheaper, and more reliable. And cloud computing also makes serverless computing possible.
In this article, we’ll learn what serverless computing is, how it works, and why it’s important for developers. You will also learn about serverless architecture.
We’ll see examples of how serverless computing can help us build apps quickly and easily without worrying about servers.
What Is Serverless Computing
The first thing you need to know about serverless computing is that it involves a new type of programming model called “serverless.”
Serverless computing means your application runs on a platform that provides all the infrastructure and architecture needed to run your app.
The platform doesn’t host any services or applications; instead, it just provides the environment in which those things are hosted.
As a result, you don’t have to worry about managing servers, setting up load balancers, scaling out your app, etc. Instead, you only need to deploy your app to the platform; the platform handles everything else.
How Serverless Computing Differs from Traditional Server-Based Computing
Serverless computing differs from traditional server-based computing because:
- Your app only needs to be deployed once (to the platform).
- There’s no need to manage servers.
- No one owns the servers.
- You only pay when someone uses them.
- You get billed based on usage rather than capacity.
The implications of the differences between server-based and serverless computing are significant.
Let’s look at some of the advantages of using serverless computing.
Advantages of serverless computing
The benefits of serverless computing over conventional server-based systems are numerous:
1) Faster deployment
When you use serverless computing, you don’t have to set up servers before deploying your app.
You can deploy your app much faster than traditional server-based computing, which requires you to set up servers, configure them, and ensure they’re running correctly before you start developing.
2) Easier management
Server management is unnecessary with serverless computing. Instead, you can focus on writing code and making changes to your app. The platform handles everything else.
3) Lower costs
When employing serverless computing, costs are decoupled from consumption.
For example, when you use an AWS Lambda function, you only pay for the time it takes for your function to execute.
However, you still pay their full cost if you use other AWS resources such as S3 buckets, EC2 instances, etc.
4) Better security
Because serverless computing doesn’t involve managing servers, you don’t have access to the underlying operating system.
As a result, it will be more difficult for hackers to take over your servers.
5) More flexible
With serverless computing, you can scale your app by adding more functions or increasing the number of instances used by each function. Using custom functions, you can enhance the functionality of your program.
6) Less maintenance
Because serverless computing doesn’t require you to maintain servers, you don’t need to spend time keeping them updated or fixing problems.
7) Higher scalability
You can easily increase your app’s throughput by adding more instances of your functions.
In addition, you can scale out your app horizontally by adding more functions.
However, the switch to serverless computing presents various challenges.
The Drawbacks and Challenges of Serverless Computing
While serverless computing has a lot of benefits, it does come with some downsides as well.
Here are some of these disadvantages:
1) Increased complexity
One challenge of serverless computing is that it introduces new concepts into your development process.
For example, if you want to create a new feature in your app, you’ll first have to write a function that will handle this task.
Finally, you’ll have to deploy this function so that it can be called from your app.
2) Lack of flexibility in the code
With serverless computing, you cannot customize how your functions work.
As a result, you may have to rewrite parts of your code when you want to change how your functions behave.
3) Limited availability
You do not have direct access to the underlying infrastructure when you use serverless computing to run your app.
Not having direct access means you won’t always know exactly where your app is hosted.
4) Security concerns
If you decide to host your app using serverless computing, you must consider whether you should expose your data publicly. Because you’re not hosting your own servers, you don’t get any protection against attacks.
5) Reduced performance
If you choose to use serverless computing to host your app, you might experience slower response times than you would if you were running your app on traditional servers. Although, this depends on your current server-based setup.
Using Serverless Computing in Conjunction with Traditional Server-Based Computing
One way to make the switch to serverless hosting easier is using traditional server-based computing alongside serverless computing systems.
Let’s look at five ways of using serverless computing in conjunction with traditional server-based computing.
1) Use serverless functions for your core app
As mentioned earlier, one of the main advantages of serverless computing is the ability to develop and deploy new features quickly.
However, if you only plan to use serverless computing for your core functionality, you may not benefit much from it. Instead, you could simply use traditional server-based computing to build your core application.
Once you’ve finished building your core app, you can start developing your serverless functions.
2) Use serverless functions to build new features
If you plan to use serverless functions to build new features, you must ensure they are reusable. To achieve this goal, you’ll need to separate your serverless functions from your core app.
This way, you can reuse them in other projects without worrying about deploying them again.
3) Use serverless functions as an API gateway
You can also use serverless functions as an API gateway.
In this case, you’d use them to provide an interface between your web or mobile apps and your backend services.
You can think of this as a middleman service between your users and your backend services.
4) Use serverless functions in conjunction with traditional servers
The final option is to combine serverless functions with traditional servers.
Of course, you’d still use serverless functions to develop new features in this scenario.
But once you’ve built those features, you could use traditional servers to scale up your app.
5) Use serverless functions when hosting on the cloud
Finally, you can use serverless functions when hosting your app on the cloud.
For example, if you’re planning to use Amazon Web Services (AWS) as your cloud provider, you can use serverless computing to create microservices.
These microservices will allow you to easily scale your app across multiple AWS regions.
Best Practices for Using Serverless Computing
To make things straightforward, you should use only one function per path. It is recommended that you avoid utilizing dedicated proxies while you are working with HTTP.
Why? By utilizing this approach, the following objectives are not going to be met:
1) Decouple issues
It is argued that a group of routes has a loose connection to the application if the function of each route depends on a separate table.
While implementing this suggested approach could increase the amount of administrative work you have to do, doing so could assist you in more accurately determining the source of any app-related difficulties that arise as your business expands.
2) There is no reason to alter the code
Because of its higher-order capacity, JavaScript is the language of choice when developing a Serverless Framework.
Therefore, your JavaScript code ought to have the most effective performance conceivable, given how it is evaluated and carried out. It is not done by modifying the source code to improve performance.
3) Take command of the code rather than the configuration settings
You can use AWS CloudFormation to deploy Serverless Framework in your environment by assigning it a specific deployer role.
If you are trapped with “config that is mostly stored in the UI,” your only way out is to use the CloudFormation deployment role that AWS offers.
You can specify your stack by utilizing their Serverless Application Model within a YAML file that a versioning system can control.
You can assign a unique role to each team or project if you want to include the principle of least privilege in the deployment process.
4) Carry out several tests depending on the load
By subjecting your lambda functions to stress testing, you may discover the best value for the timeout parameter and the amount of RAM to allocate.
You might not be aware of the inherent limitations limiting your apps from scaling if you work in a serverless environment, which allows for the possibility of more complex programs.
For an application to be accessible at any time, load testing must allow for the detection of any potential problems.
5) Ensure the security of API gateways
Whether you choose traditional architecture or a serverless solution, your organization should prioritize application security.
It is strongly recommended that you protect API Gateway endpoints with some authentication mechanism.
You can access a wide range of choices when protecting your API’s authenticity through this Gateway.
Conclusion
There has been a rise in the use of serverless architectures in recent years. This new technology allows developers to write code without worrying about managing servers.
Instead, the cloud provider takes care of everything from provisioning resources to scaling capacity when needed.
Serverless computing also makes it easier for developers to build applications that scale automatically based on demand. And because serverless computing doesn’t require any upfront investment, it’s perfect for small teams and startups.
TelemetryHub offers powerful application monitoring at a fraction of the normal cost. And TelemetryHub does this through serverless computing. Try TelemetryHub today to enjoy a free 14-day trial.
People Also Ask
Find the answers you’re looking for about serverless computing below.
What is serverless computing?
Serverless computing refers to cloud computing platforms where users do not need to provision servers for applications running on them. The advantage of using serverless computing is that users no longer need to worry about managing servers, which makes it easier to scale up and down quickly.
What is an example of serverless computing?
An example of serverless computing is the Amazon Web Services (AWS) Lambda service. AWS Lambda lets you run code without provisioning or managing virtual machines.
What does ‘serverless’ mean, and how does it work?
Serverless is a cloud computing model where users don’t manage infrastructure but instead focus on building applications and APIs. As a result, users pay for what they use rather than buying upfront costs.
In serverless, there’s no fixed relationship between computing power and cost. Instead, a user pays for the resources used. With serverless, the provider manages all underlying details.
What is the use of serverless computing?
The main benefit of serverless is that it provides elasticity. Serverless enables developers to easily add or remove computing power during peak times, such as immediately after launch or following a spike in traffic.
Serverless computing is also excellent for scaling out. When developers scale out, they can add additional instances to handle increased loads.
Here are some more uses for serverless computing;
- For web apps
With serverless, developers can create scalable web apps by paying only for their app’s time. They can also deploy these apps rapidly since they’re not responsible for setting up servers.
- For mobile apps
Mobile apps often involve intensive data processing, so they’re ideal candidates for serverless. As a result, developers can avoid having to set up servers, which saves money and time.
- For IoT devices
You can deploy IoT devices like smart thermostats, security cameras, and home appliances quickly and cheaply via serverless.
- For machine learning
Machine learning algorithms can be trained at scale, making them suitable for deployment in serverless environments.
- For analytics
Analytics tools can be deployed in serverless environments, allowing companies to collect real-time data.
- For API management
API management tools can be deployed in a serverless environment, providing rapid development and scalability.
- For microservices
Microservice architectures allow developers to break large projects into smaller services. You can deploy microservices in a fast and efficient manner with serverless.
