The cloud computing model has been around for a while now and is gaining ground over traditional application development systems. As traditional models need application developers to manage, maintain and scale their server setups as per need, they create an unnecessary overhead for smaller companies that is sometimes difficult to deal with, especially with tight deadlines. To counter this problem, most major application development platform providers like Microsoft, IBM, and many others have gone the cloud way by offering cloud-based application development services. Serverless apps are the newest kid on the block. With every major cloud provider offering serverless applications, and major campaigns being run around the simplicity of these offerings, one starts to wonder what these applications really are.
What is a serverless application?
Serverless is a cloud computing execution model where the pricing is based on the number of executions and not on pre-purchased compute capacity. In a serverless model, the cloud provider will manage the allocation and provisioning of servers dynamically. Here, the application will run in stateless compute containers that are triggered by events and last for only one invocation or call. The entire system is fully managed by the service provider on the cloud.
A serverless application is an event-driven cloud-based system where the application relies on a combination of third-party services, client-side logic and cloud-hosted RPCs (Functions as a Service).
What makes a cloud offering serverless?
Here’s what is required for a service to be considered as a serverless service or platform:
- Provider managed servers – Developers do not have to add or maintain any servers. All software and runtimes are installed, maintained, and administered by the provider.
- Scalability – Applications can be scaled automatically or by adjusting their capacity by switching the units of consumption (for example, throughput, memory) rather than units of individual servers.
- High availability – As serverless applications come with built-in availability and fault tolerance by default, developers do not need to architect them.
- No idle capacity – Serverless applications ensure that you are only charged when your code runs and not otherwise. There is no charge for computation and storage.
What can you do with a serverless application? Is it right for me?
Smaller organizations might find the whole idea of building a serverless application a little daunting, but with the correct understanding and the right tools, they can create an entire application with just some lines of code and achieve an unparalleled time to market. Using a service like Amazon Lambda as the logic layer of your serverless application can enhance development speeds and encourage higher levels of innovation and experimentation compared to traditional server-based platforms. Although you can create nearly any type of serverless application or service, here are few examples of use cases where serverless applications would be a good fit:
Backend applications for IoT
Serverless backend services for highly scalable and secure IoT applications are a great fit for these application types. Many service providers like AWS Lambda, Microsoft Azure Functions, and others have direct integration capabilities that allow device messages to be routed and processed by serverless functions. Services like AWS Lambda functions can easily handle these messaging services for scalable applications like intelligent manufacturing facilities and online appliances for consumers.
Web and mobile backend services
Amazon API methods provide a way to integrate user-facing content in an S3 bucket and integrate this front-end content with the Amazon API Gateway as a backend service API. This can then trigger the business logic created for each of the API Gateway Methods in the backend API using Lambda functions. This ensures that fully serverless mobile applications and web applications can be built without much being done outside the Amazon serverless ecosystem.
Virtual Assistants and Chatbots
Intelligent responses to natural language inputs and user voice inputs on Social media pages for customer engagement can easily be accomplished on most serverless platforms. On Amazon, the Alexa Skills Kit and Lex can apply natural language recognition to freeform text and voice input by users. This can further trigger a Lambda function that can respond and engage with customers.
What are the benefits of a serverless application?
There are many benefits of a serverless application that range from reduced development time to”
No fixed cost
With free tiers in most providers like Amazon and Google, the reduction in cost here directly affects your application’s fixed or recurring cost. Also, as these services and their related storage is usage-based, you will not be charged when the application is in the resting stage. For applications with light usage and those that are used to showcase prototypes.
DevOps overhead reduction
With most of the developer’s time is spent on development and lesser time being spent creating a dev environment, resources are used better and efficiently. As programmers now spend their time writing code that is near-production, they get increasingly confident about the quality of code and the time they used to spend planning and setting up services is now spent developing.
Using microservices for sundry tasks
If you are building a service that must be run constantly, then you should think of outsourcing it to a pre-existing service that can let your app connect to it via an API. A serverless application will restrict you to build true microservices. If your app has a functionality that does not suit the functions of AWS Lambda, you can build it as an external microservice and connect your app to it.
Limitations of serverless applications
Although everything about serverless applications sounds great until now, there are some constraints that we should be aware of before we start building our serverless app. As the functions we build are going to be anonymous, our backend is limited to independent, singular function calls. Also, as our only resources are storage and cloud services, they can constrain our app that a usual full-featured server might not have problems with. Some of these constraints include:
Execution time limitations
Lambda functions currently have a 5-minute time limit. This makes it challenging for tasks that might require long execution times like streaming data services. For tasks that require more than 5 minutes, these must be split, and these batches and data clocks must be tracked externally. Ideally, tasks like these that have long execution times must be built as an independent service that can be connected to using external APIs.
Execution latency and cold starts
Unused lambda functions can often be spun down by the provider, and the container for these applications must be spun up before the function is executed. This will add to the initial execution time for a function. Ensuring that the user is satisfied when the client is initially loaded at the front end will enhance user satisfaction. To counter this, a ping would be good before the user loads the client so that the functions have warmed up when the user invokes them. This, however, is not an issue with background and housekeeping tasks.
As the functions of AWS Lambda are stateless and driven solely by events, these events the storage of states is then delegated to a database or to a server memory like Redis. If we opt for a fully could-based mechanism, we can opt for a serverless database like DynamoDB for quick storage and response times. Also, developers need to note that their functions must be designed to work with single and independent functions that are stateless.
Although Lambda handles any horizontal scaling, multiple functions run in their own separate container and that adds overheads that will be associated with the creation of each container. If you split your Lambda function to counter this, the split will further increase the overhead.
Lambda functions are not local to a server as they are on the cloud. These functions keep passing state back and forth through the cloud, which can cause latencies for the end-user if there are several dependent functions on the client-side.
If you have built functions that require chaining, you should explore using Amazon SNS or other services like AWS Step Functions.
Development using Lambda
Lambda offers testing the functions that you have created locally instead of uploading them to the cloud. Functions can be debugged on the cloud itself, reducing fix times. You can also find logs and stats for each deployed function, for each relevant version. If you wish to track the request that was causing production errors, you can do that using Cloudwatch.
Serverless technology has grown exponentially in the last year or so. Showcasing itself as a way to develop and deploy services and web applications in a cost-effective and quick way, serverless technology continues to grow and improve by the day. As latencies and performance costs associated with this architecture reduce in time, these services are being adopted more and more by companies around the globe.