Top benefits and disadvantages of serverless computing

Advantages of serverless computing

With an innovative approach to deploying applications and services, serverless computing offers several compelling advantages that drive its adoption across various industries. Here are some of the key benefits.

Cost efficiency

Serverless computing charges for the resources used rather than pre-purchased capacity. You don't pay for idle capacity or manage servers, and you avoid wastage during off-peak times expected in traditional server-based architectures. This pay-per-use model results in cost savings for variable workloads.

Operational efficiency

The serverless model simplifies the infrastructure management tasks, such as server provisioning, patching and maintenance, which enables developers to focus on building application features. It optimizes the workflow and makes deployment and updates faster because the cloud provider handles server management complexities.

Scalability

The automatic scaling feature is advantageous for handling unpredictable or fluctuating traffic patterns, as it ensures that the application remains responsive without manual intervention. Additionally, serverless computing can dynamically adjust to sudden spikes in traffic, such as during major events or sales, to ensure consistent performance.

Simplified back-end code

Simplified back-end code enables developers to concentrate on their core product, often leading to better quality and more innovative features. Serverless architectures are also microservices-friendly, which makes it easier to develop, deploy and manage small, independent and modular pieces of code in complement with microservices patterns.

Ecosystem and community

Major cloud providers provide integrated services that work seamlessly with serverless computing, including databases and machine learning capabilities. This enables the creation of feature-rich applications.

Disadvantages of serverless computing

Understanding the drawbacks of serverless computing is essential for organizations considering serverless architectures for their applications. Here are some of the key disadvantages.

Performance issues

When a function remains unused for a certain period, it enters a dormant state. As a result, subsequent requests after this period may experience a delay in response time -- referred to as a cold start -- since the server needs to allocate resources and start the function from scratch. There may be better choices than serverless computing in applications with critical response time. Latency variability, especially in cold starts and resource allocation, can cause issues.

Vendor lock-in

Serverless architectures often rely on the services and tools that a single cloud provider offers. This can result in vendor lock-in, which makes it challenging and potentially expensive to migrate to a different provider in the future. Additionally, many serverless platforms offer proprietary services that may need more equivalent options on other platforms, which can further complicate potential migration efforts.

Limited control and flexibility

When using a serverless approach, you may have limited control over the underlying infrastructure, including the OS and hardware. This can become a problem if your application requires specific environmental configurations. Additionally, serverless platforms often have restrictions on runtime execution, such as maximum execution time for a function, and the available execution environments, such as supported programming languages and versions.

Security

Serverless applications can potentially increase the risk of cyberattacks because each function can serve as a potential attack entry point. Additionally, a serverless application's security largely depends on the security measures implemented by the cloud provider. While providers generally have extensive security measures, the application owner is responsible for securing the application code and data per the shared responsibility model.

Monitoring and debugging challenges

Monitoring and logging can pose challenges due to the application's distributed nature of serverless functions. Debugging serverless applications can be difficult, especially when attempting to reproduce the exact conditions that led to an issue, given the stateless and ephemeral nature of serverless functions.

Serverless readiness assessment

Determining if an organization is ready for serverless computing requires a comprehensive analysis of various factors, including the following:

• Current workloads and goals.
• Cloud operations and cost management impact.
• Application architecture.
• Skill set requirements.
• Staff training considerations.

Transitioning to serverless computing affects cloud operations teams and cost management strategies. Assess how serverless integrates with existing processes and the potential impact on operational workflows.

Serverless computing often necessitates a shift toward microservices and event-driven architectures. Enterprises need to assess their current applications' architectures and determine the feasibility and benefits of restructuring for serverless. They also need to understand how serverless functions integrate with existing systems and services, including compatibility with current APIs, databases and other cloud services.

Additionally, assess the current skill levels of development teams in cloud-native technologies. Serverless computing often requires proficiency in cloud services, API integration and event-driven programming. Training for staff to work with serverless technologies effectively is necessary and may include workshops, online courses and hands-on projects focusing on serverless architectures and cloud services.

Everyday serverless use cases

As serverless gains popularity, there are several everyday scenarios demonstrating the use of serverless computing. In each case, serverless computing offers a flexible, scalable and cost-effective solution, enabling businesses to focus on application logic rather than infrastructure management.

Real-time file processing

Industries such as media, entertainment and online education often require the processing of large volumes of images and videos. These tasks may involve resizing images, converting video formats or applying filters. To automate and scale these operations, you can use serverless functions.

For instance, when a user uploads a video, a serverless function can automatically transcode it into various formats suitable for different devices. This approach is cost-effective, as the function runs only when necessary and can handle fluctuating volumes of media files. The advantages of this approach include the following:

• Reduced processing time.
• Scalability to handle peak loads.
• Cost savings due to the pay-per-use model.

Web applications

Web applications, like e-commerce or promotional campaign sites, often experience fluctuating traffic levels with sudden spikes during sales or marketing events. These applications can dynamically scale to accommodate traffic fluctuations by implementing a serverless architecture. For example, a serverless API gateway can manage incoming requests and scale up during high-traffic periods, ensuring the website remains responsive. This implementation has several benefits, including the following:

• Improved UX due to consistent performance.
• No overprovisioning of resources.
• Reduced operational costs.

IoT applications

IoT applications, like smart home systems or industrial IoT, generate data from various sensors and devices. Serverless functions can process incoming data in real time. These functions can perform actions, such as data aggregation, anomaly detection or alert triggering, based on specific criteria.

Unlike traditional servers, serverless functions do not run continuously, and data processing can occur as soon as the data is received. This approach offers several benefits, such as the following:

• Immediate data processing.
• Scalability to handle data from thousands of devices.
• Reduced infrastructure costs.

Choose the right serverless service

When choosing the right serverless service, several factors are needed to ensure that the service aligns with your application requirements, technical capabilities and budget constraints.

When choosing a serverless platform, there are three key factors to consider:

1. Programming language. Evaluate whether the platform supports the programming language you intend to use and whether it integrates well with other tools and services you already have or plan to use.
2. Pricing. Serverless platforms differ in pricing structures. Some offer a certain number of free requests before charging, while others have different pricing tiers based on usage. Consider the performance aspects, such as execution speed, cold start times and overall reliability, to ensure the most value.
3. Support. A strong community and support system can be invaluable when troubleshooting issues or seeking advice on best practices. Some platforms have more active communities than others. This can be crucial in a decision-making process. Research the available support resources and user communities to determine which platform best suits your needs.

Many providers offer comprehensive services. The following are some of the major offerings.

AWS Lambda

AWS Lambda is one of the original serverless computing services. Lambda automatically scales applications by running code in response to each trigger. It supports multiple programming languages and integrates seamlessly with other AWS services.

Lambda functions are a great fit for applications that need to respond to specific events, such as changes in data, system state or user actions. They are particularly efficient for processing real-time data, such as image recognition, file processing and stream processing. You can use Lambda functions as back-end services for API requests triggered via Amazon API Gateway.

Microsoft Azure Functions

Azure Functions is a platform that enables event-driven serverless computing, can help with complex orchestration tasks and is compatible with various programming languages. It also integrates with other Azure services for added functionality.

You can use Azure Functions to build HTTP-based services that respond to web requests, and it can handle real-time stream processing with data from IoT devices or other sources. Additionally, it can automate tasks like running scheduled jobs for routine tasks, such as database cleanup or backups.

Google Cloud Functions

Cloud Functions integrates with Google's machine learning and data analytics capabilities, enabling smart applications with intelligent behavior. It can also handle and process data generated from other Google Cloud services, like Cloud Storage and BigQuery.

It is ideal for creating scalable API endpoints for web and mobile applications. It can also provide serverless endpoints that can automatically scale up or down based on the number of requests received.

Other serverless offerings

Some vendors, like IBM, Oracle, Alibaba and Cloudflare, offer serverless computing services as an alternative to the big three. These third-party services often prioritize easy integration with existing cloud services or offer unique features, like edge computing capabilities.

They may also provide competitive pricing or performance benefits for specific use cases. Some providers specialize in niche areas, such as AI or IoT. Or they may specialize in specific industries, offering tailored functionalities that differ from mainstream providers.

Liam Cleary runs his own consulting company that helps customers work with Microsoft 365 and Azure-based technologies. He specializes in internal and external collaboration, document and records management, business process automation and security measure implementation.