In the fast-evolving growing world of technology, the choice of the best architecture to adopt is an unfinished battle between the stake holders, developers and architects. This relies on several factors which we are to recall in another section. Talking about the type of architecture and factors influencing it. Recently there has been a high demand for scalable, cost-effective and agile solutions. Serverless architecture has emerged as a compelling paradigm, empowering organizations to build and deploy application with unprecedented flexibility and efficiency leading to innovative applications and operational efficiencies. But navigating the decision of "when to adopt serverless" requires careful consideration.
Understanding serverless architecture
At its core, serverless architecture eliminates the burden of server management and provisioning. This abstraction provided by serverless architecture makes it possible for developers to solely focus on the code, instead of thinking about scaling and infrastructure. Serverless functions execute on demand, triggered by events like HTTP requests, database changes, or scheduled invocations. This "pay-as-you-go" model scales seamlessly based on demand, avoiding overprovisioning and associated costs. In this architecture, irrespective of your stack of development, your code gets deployed. The essence of serverless lies in its ability to automatically manage the allocation and provisioning of compute resources, scaling up or down in real-time as demand changes.
When to Consider Going Serverless
Although serverless is suitable for a lot of use cases and scenarios, we have some scenarios which best matches the use of this innovative technology. Below are some best fit cases for serverless architecture.
To Support Microservices Architecture:: Break down monolithic applications into small, independent functions that communicate through events. This microservices approach improves modularity, maintainability, and scalability.
Companies like Netflix have popularized microservices, but serverless takes it a step further by offering an easy way to deploy and manage these services. It allows each function or service to scale independently, optimizing resources and costs. Zynga's migration to Google Cloud Functions for its gaming backend demonstrates the scalability and cost benefits of adopting a serverless approach in a microservices ecosystem.Event-Driven Applications:
Serverless excels in situations where applications respond to events. Whether it's processing files uploaded to cloud storage, responding to web requests, or handling IoT device signals, serverless functions can be triggered by specific events, making them ideal for such tasks. The Coca-Cola Company leveraged AWS Lambda for vending machine management, showcasing how serverless can streamline operations and reduce costs.For Applications with Variable Workloads:
Serverless architecture shines in handling applications with unpredictable or variable traffic and workloads. Its ability to automatically scale means that you only pay for what you use, avoiding overprovisioning or underutilizing resources. This model supported Bustle, a digital media company, in efficiently managing their backend services for a platform that receives billions of requests per month.To Accelerate Development and Deployment:
The simplicity of serverless allows for rapid development and deployment. By eliminating the need to manage infrastructure, developers can focus on creating value through their code. A Cloud Guru utilized the Serverless Framework on AWS to build an entire platform dedicated to cloud computing education, demonstrating how serverless can facilitate a lean and efficient development process.For Cost Efficiency in Sporadic Usage:
Serverless is particularly cost-effective for applications that do not require constant compute power. Since billing is based on actual usage, applications with sporadic activity levels can benefit significantly. This pricing model was a key factor for iRobot, which uses AWS Lambda to manage communication between its robots and the cloud, ensuring cost efficiency as the number of connected devices grows.
Real-World Success Stories for Serverless architecture
The Coca-Cola Company
By integrating AWS Lambda for tasks like vending machine management, The Coca-Cola Company showcases serverless's potential to transform traditional operational models, leading to significant cost savings and operational efficiency.Zynga
Zynga's adoption of Google Cloud Functions underscores the impact of serverless on the gaming industry, enabling scalable, cost-effective solutions for managing game backend services.Bustle
Bustle's success with AWS Lambda illustrates how digital media platforms can leverage serverless to handle vast amounts of web traffic, reducing operational overhead while ensuring scalability.
When Serverless Might Not Be the Best Fit
We spoke in the lines above when serverless can be the best fit, what about when serverless should not be used. Despite its advantages, serverless architecture might not suit every scenario. Applications requiring long-running processes, those with complex local state dependencies, or cases where cold start latency is a concern, may find serverless challenging. Furthermore, companies with specific regulatory or compliance requirements that necessitate tight control over the environment might need to evaluate serverless carefully. Some scenarios where serverless might fall short include some of the following:
Long-Running Processes: Serverless functions are designed for short bursts of activity, typically under 15 minutes. Tasks exceeding this limit can incur cold start penalties and higher costs due to continuous billing. If your application involves lengthy computations or background jobs, traditional containerized or virtualized options might be more suitable.
Fine-Grained Control: Serverless architectures often abstract away underlying infrastructure aspects like memory allocation and CPU core limitations. For applications requiring granular control over resources or specific security configurations, containerized or virtualized approaches offer more flexibility.
Debugging and Monitoring: Tracing the execution of serverless functions can be more complex compared to traditional environments. While cloud providers offer monitoring tools, they might not fully address debugging needs, especially for intricate applications.
Vendor Lock-In: While portability options are emerging, certain serverless functions might rely heavily on specific cloud provider features. If vendor neutrality is crucial for your project, consider the potential challenges of switching providers later. You can look after some providers like AWS, Google cloud and Azure Cloud.
State Management: Serverless functions are inherently stateless, meaning data persists elsewhere. Handling complex state management within stateless functions can add complexity and introduce synchronization challenges. Consider serverless databases or specialized state management solutions if your application requires significant state retention.
Limited Offline Functionality: Serverless functions typically rely on cloud infrastructure for execution. If your application needs to function offline or in intermittent connectivity scenarios, containerized or virtualized approaches can provide greater autonomy.
Pros and Cons
Let look at some goodies and baddies serverless architecture comes alongside with.
| Pros | Cons |
|---|---|
| Cost Efficiency | Cold Start |
| Only pay for compute time used, leading to potential cost savings for variable traffic applications. | Initial invocation can take longer, especially after inactivity periods. |
| Scalability | Runtime Limitations |
| Functions automatically scale with demand, handling peak loads efficiently. | Execution time limits may not suit long-running processes. |
| Development Speed | Vendor Lock-in |
| Focus on code rather than managing servers, speeding up development and deployment. | Migrating to another provider may require significant changes due to differing tools and services. |
| Operational Management | Complexity in Monitoring and Debugging |
| Cloud providers manage infrastructure, reducing operational burden. | Distributed nature can make monitoring and debugging more challenging. |
| Improved Latency | Security Concerns |
| Deploying in multiple regions can reduce latency by serving users from the nearest data center. | Responsibility for application code security and access management remains, despite infrastructure security being managed. |
| Networking Limitations | |
| Potential restrictions on networking aspects, affecting certain applications. | |
| Cost Predictability | |
| Predicting costs can be challenging for applications with unpredictable workloads. | |
| State Management | |
| Managing state across stateless functions can be complex and might require additional services. |
Conclusion
Serverless architecture offers a compelling model for many use cases, particularly for event-driven applications, microservices, variable workloads, rapid development needs, and cost-efficiency goals. The success stories of companies like The Coca-Cola Company, Zynga, and Bustle highlight the transformative potential of serverless across various industries. However, understanding when and how to adopt serverless is crucial, as its benefits are most pronounced when aligned with specific business and technical requirements. As serverless continues to evolve, it promises to play a significant role in shaping the future of cloud computing, offering a path towards more efficient, scalable, and cost-effective software development.
Top comments (3)
Thank you, this was very helpful
You're welcome.
This is a great article, and I really appreciate how you've included real-life examples! I wanted to share two additional scenarios: working with both server-based and serverless simultaneously, and transitioning from serverless to a more server-based architecture.
First, depending on your application and the type of load balancer you use (whether it's a web load balancer or a queue-based one), you can leverage a hybrid approach by combining traditional cloud instances like EC2 with Lambda functions. For instance, EC2 could handle your regular daily load, while Lambda functions kick in during peak times when traffic spikes. This allows you to run both architectures at the same time, optimizing cost and performance.
Is it possible to start serverless and then move to a server-based model?
Yes, it is. With today’s container technology, early preparation is key. The first step is making your application stateless. Next, you need to establish a common ground to translate whatever event triggers your application, whether it’s an HTTP request, a Lambda invocation, or a queue event. This flexibility helps you avoid vendor lock-in and makes your application portable across different platforms.
When it’s time to switch vendors or technologies, you can create a new translation layer that aligns with the new vendor's software. From there, you can build a Dockerfile with the required software for that vendor, and run tests to ensure smooth migration. The same method applies if you need to transition back to a more server-based model—just pack a Dockerfile with the necessary HTTP server or queue software and deploy it to your servers.
For more insights on serverless computing, I recommend this article by my colleague Vin Souza, Senior Software Developer / DevOps Engineer: Serverless Architecture.