The serverless trend has been growing in popularity for the past few years. A recently conducted IBM Survey estimates that serverless adoption is increasing, with 68% of non-users saying they are likely to adopt a serverless approach within the next two years.
For developers, serverless computing is a boon. They can write and deploy code without worrying about the underlying infrastructure. Plus, with pricing being execution-based, enterprises do not have to spend on pre-purchased computing capacity and storage, enabling them to code at a fraction of the price.
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How Does Serverless Computing Work?
Managing a server is a complex process and often involves much legwork. Setting up a server and deploying servers to your application is only the first step. You also have to monitor it, do regular maintenance, configure it, keep the servers and applications up to date, scale according to demand, etc.
In contrast, serverless divests you of all these responsibilities. Everything is abstracted away, so developers can focus on business requirements without worrying about managing any underlying infrastructure.
By using a programming language of their choice, most commonly Python and Node.js, developers use third-party resources to host applications. Thus, app-hosting becomes fast and efficient.
However, from the developer’s point of view, it is almost as if the servers are non-existent. Hence the term “serverless.” The fact is, servers are still giving you back-end services, but they are in the background with the vendor handling everything.
What are the Features of Serverless Computing?
Notable features of serverless computing include:
- Abstracts away the servers and the complexity of maintaining them.
- Offers a pay-as-you-go cost model that charges you only for the resources used, eliminating costs for idle resources or unused space.
- It rapidly and automatically scales up and down with changing demands.
- Serverless is event-driven, so it runs only when a specific event triggers it. Once an event is triggered, it executes the task and then terminates after a few minutes.
- It allows developers to focus on building code rather than wasting time maintaining infrastructure.
Benefits of Serverless Computing
Serverless computing has several advantages:
- Quicker time to market: With serverless, you don’t need to worry about setting up back-end infrastructure. Everything comes as part of a package. Your developer environments can thus be set up easily, enabling you to get to market quickly.
- No Server Management: Serverless computing runs on servers, but cloud service providers (CSPs) manage those servers. So, developers don’t have to worry about managing servers; all they are required to do is run and execute code.
- Lower Costs: With traditional systems, you usually buy servers in excess capacity to avoid downtime. But with serverless, you pay only for the resources you use and the time they are running. In addition, since it is execution-based, you pay only for the duration when the code is running. As a result, serverless computing is less expensive compared to other services where you pay for applications, even when they are not in use.
- Highly Scalable: One of the biggest advantages of serverless is that it can automatically and easily scale to accommodate demand with no intervention on your part.
Drawbacks of Serverless Computing
While serverless computing is ideal for specific use cases, it has certain demerits.
- Vendor lock-in: Serverless platforms are mostly offered by cloud vendors, so businesses invariably get locked in with one of the major CSPs. If you’re vendor-agnostic, then serverless is probably not the correct option for you.
- Runs for a limited time: One disadvantage of serverless is it runs for only a limited time. Therefore, long-running workloads are not ideal to be deployed on serverless. For instance, AWS Lambda functions run up to 15 minutes per execution, after which the function gets terminated. However, if you have long-running functions, you may be better off with other deployment methods.
- Debugging is difficult: Debugging applications are challenging in serverless because it takes place over a distributed network. Further, servers are ephemeral in nature, so you have very little time to identify the root cause of the problem. While logging helps, you need advanced tooling methods for accurate debugging.
- Higher latency: Typically, when a serverless function is idle for a long time, the vendor shuts it down. Now, the next time you call a function, you’ll experience higher latency or a cold start. Cold starts can be a major problem, especially when running a time-sensitive app.
Popular serverless platforms include AWS Lambda, Azure Functions, Google Cloud Functions, and IBM OpenWhisk. Here’s a closer look at them.
One of the biggest names in serverless computing, AWS Lambda, was launched in 2014 and is credited with making the concept of serverless mainstream. It seamlessly integrates with other AWS services, making it the first choice for those already using other AWS products.
- It natively supports languages like Node.js, Python, Ruby code, Java, Go, .Net Core, PowerShell, and C#. In addition, users can implement their own language runtimes.
- The free tier includes one million executions per month.
- Has a maximum execution time of 15 minutes.
- You can invoke functions synchronously, asynchronously, or use a poll-based invocation model.
- Used by Netflix, Asana, ZALORA, Nordstrom, and Coca Cola among others.
Azure Functions is an on-demand serverless compute service for Microsoft Azure that lets developers run event-triggered code.
- Azure Functions has three hosting plans to suit your needs. The free tier includes one million executions per month. Subsequently, it offers tiered pricing for different requirements.
- Has a maximum execution time of 10 minutes.
Google Cloud Functions
Google Cloud Functions was released in 2016 as part of the Google Cloud Platform. GCF integrates well with other offerings by Google, so it is a good choice for users already using Google products.
- It processes the first two million requests for free.
- It is cheaper compared to Azure Functions and Lambda.
- GCF supports several event-based triggers like Cloud Pub/Sub Triggers, HTTP, Cloud FireStore, Firebase Realtime Database, Firebase Authentication, etc.
IBM Cloud Functions
Based on Apache OpenWhisk, IBM Cloud Functions is an open-source serverless platform that allows you to execute code on-demand.
- It supports PHP, Swift, Node.js runtime, Java, and Python. However, you can integrate other programming languages with Docker containers.
- Has an execution time limit of 10 minutes.
- It delivers a per-region SLA (service-level agreement) of 99.95%.
- IBM Cloud Functions is integrated with the IBM Monitoring Service to deliver better insights.
- Used by The Weather Channel, ESPN Fantasy Football, and The Masters.
Future of Serverless
With the global serverless market expected to grow at a CAGR of 30% and reach USD 16 billion by 2026, serverless will continue to be a lasting and viable computing option. Serverless computing is a cost-effective option for customers who want to execute code without the additional burden of capacity planning and provisioning resources.
In addition, the event-driven approach promises to be a game-changer for companies looking for low operational costs along with faster time-to-market options. However, since it may not be ideal for all scenarios, businesses need to be wary of the pitfalls before jumping on to the serverless bandwagon.
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