How To Use Serverless Architecture

Serverless architecture is becoming increasingly popular for fintech developers and CTOs looking to simplify their tech stack. The technology offers many benefits, including reduced server management complexity and lower costs due to its pay-as-you-go model.  

But how exactly do you implement serverless technology? In this article, I provide a comprehensive, step-by-step guide to using serverless architecture, with practical tips and real-world use cases.

Understanding Serverless Architecture

Serverless architecture, despite its name, still involves servers but shifts the responsibility of managing them from developers to cloud service providers. It’s a bit like using a fully managed service for a task rather than managing it in-house.

Imagine an application as being composed of two parts: the frontend, which users interact with, and the backend, which powers the frontend. In serverless architectures, this backend code runs on the infrastructure provided by the cloud service, removing the need for businesses to worry about managing physical servers.

While this does simplify things significantly, it doesn’t entirely remove responsibility from the business owner or the developer. There’s still the need to ensure the security of your code, and initial setup is necessary, albeit less time-consuming than traditional server setups.

Serverless architectures are also event-driven. When certain events or triggers happen (like an HTTP request or database event, for example), your application responds. While this shifts the security of the physical servers onto the cloud provider, the responsibility for securing your code still lies with you.

The building blocks of serverless applications are functions—small pieces of code, each doing a specific task. When an event triggers a function, the cloud service provider allocates resources for this function, executes it, and shuts down once the task is complete. This approach, known as Function as a Service (FaaS), is the core of serverless computing.

One of the primary benefits of serverless architecture is its pay-as-you-go model. You’re billed only for the computation time and resources used when your functions are running. If no functions are executed, there are no charges, making it a cost-effective option compared to traditional models where payment for server capacity is required regardless of usage.

In terms of scaling, serverless architecture works differently from traditional auto-scaling. As the demand for your application increases or decreases, the cloud provider adjusts resources accordingly, ensuring you only pay for what you use.

Pros Of Serverless Architecture

A serverless environment brings numerous advantages to businesses, primarily due to its cost-effectiveness, infrastructure management, and reduced operational responsibilities. Here are the key benefits of serverless containers in detail.

Reduced Operational Costs

With a serverless computing service, you only pay for the computed time you consume. There are no charges when your application code isn’t running. Unlike traditional hosting, where you’re charged based on the server size and duration, in serverless computing, you’re billed for the compute resources consumed by your application down to the millisecond. This pricing model can save significant costs, especially for applications with variable or unpredictable workloads.

Reduced Operational Responsibilities

With serverless architecture, the cloud provider takes on many operational responsibilities. With serverless technologies, the cloud provider also handles management tasks such as external services, managing processes, capacity planning, patching, maintenance, and administration, freeing up your IT team to focus on building and improving applications. This can accelerate the development process and improve your company’s agility.

Positive Environmental Impact

An often overlooked advantage of serverless computing is its potential environmental benefits. With traditional servers, a significant amount of computational power constantly needs to be used, which can lead to energy waste. In contrast, serverless computing’s pay-per-use model encourages more efficient use of server resources, which could result in a lower carbon footprint.

While these benefits make a compelling case for serverless architecture, it’s not without its challenges. It’s essential to understand the potential drawbacks to serverless workloads and hardware to make an informed decision.

Cons Of Serverless Architecture

While serverless apps offer several compelling advantages, they’re not a panacea for all computing needs. There are also potential drawbacks that businesses need to consider before moving towards using serverless app platforms.

Cold Start

“Cold start” refers to the scenario where an idle serverless function or service is invoked. This term captures the latency incurred when the service provider is allocating the necessary resources for the function or simple storage service to operate.

Such latency can indeed pose a challenge to serverless applications that require instantaneous responses. However, several strategies are available to counteract this issue. One effective method is ‘warming,’ which triggers serverless services or functions periodically to keep them ready for immediate action.

This “cold start” latency usually falls between 20-40 seconds, contingent on the technologies used and the time taken to assign resources to your request. For example, if a function hasn’t been invoked over the past 30 minutes, the initial startup may necessitate a 20-40 second wait before it begins to execute.

The choice of programming language can significantly influence the duration of a “cold start.” In this respect, Python and JavaScript emerge as the most recommended languages for serverless architecture. Their advantage lies in an optimal combination of startup time, cost, and a readily available pool of developers. Both languages facilitate quicker startup times, enabling more efficient handling of “cold starts” and enhancing the overall efficiency of your serverless application.

Statelessness

Serverless functions are stateless, meaning they don’t store data from one execution of function code to the next. Suppose your server hardware or application requires persistent data storage or state between two running server-side functions. In that case, you must use an external database or storage system, which could add to the complexity and cost.

Limitations of Execution Time

Serverless providers typically set a maximum limit on the execution time for a single function’s code execution. If you have an existing application with long-running processes, a serverless architecture might not be the most suitable solution.

The execution time limit for a function is generally around 15 minutes. Therefore, a function designed to run for an hour will simply be cut off after reaching this limit. Unfortunately, the results will not be saved, and the function won’t be removed from the processing queue, leading to a non-functioning system.

However, a solution does exist. You can design your function to decompose larger tasks into smaller, more manageable pieces and process them separately. In this case, you are not charged for the function’s execution time but for the number of function invocations, making this approach both practical and cost-effective.

Steps To Implement Serverless Architecture

Adopting serverless architecture can be a game-changer for your tech infrastructure. Here is a step-by-step guide on how to implement a serverless framework.

Step 1: Identify Use Cases

Serverless architecture might not be the right fit for all types of applications. However, certain types of workloads and tasks can greatly benefit from this model. Here are a few prime candidates for serverless computing:

• Non-Real-Time Processing: If your application doesn’t require immediate responses, serverless could be a good fit. This includes workloads such as data analysis, batch processing, or tasks that can be performed in the background.
• File Processing: Serverless is an excellent choice for applications that need to process files, especially when these tasks are sporadic or unpredictable. Examples might include resizing uploaded images, extracting text from uploaded documents, or analyzing uploaded files’ content.
• Data Transformation: Tasks such as data cleaning, validation, transformation, or aggregation, often required in data pipelines, can be effectively handled using serverless architecture.

In many projects, a combination of architectures is used. For instance, a primarily cloud-based architecture might use serverless for specific stateless functions. This hybrid approach allows you to leverage the best aspects of different architectures based on your needs.

Moreover, entirely serverless architectures are also used where latency is not a critical factor. Since serverless can introduce some delay (referred to as “cold start”), it’s not suitable for applications requiring immediate, real-time responses. However, for applications where some delay is acceptable, going fully serverless can provide the benefits of lower operational overhead, cost efficiency, and scalability.

Step 2: Choose the Right Serverless Provider

While several serverless providers are available, your choice should be guided by your specific needs and preferences. Here’s a high-level comparison of three popular serverless providers:

• Google Cloud Functions: Google Cloud is renowned for its cost-effectiveness. If your primary concern is budget, Google Cloud offers a competitive pricing structure that makes it an attractive option, especially for startups and small businesses.
• Microsoft Azure Functions: Microsoft Azure is recognized for its enterprise-grade capabilities. Although it tends to be pricier than Google Cloud, it provides robustness, integration with other Microsoft products, and an extensive suite of services that could be invaluable for large-scale or enterprise-level applications.
• AWS Lambda: Amazon Web Services (AWS) is known for its cutting-edge technologies. AWS is typically chosen for its comprehensive set of services, scalability, and security. They constantly innovate and are often the first to introduce new features and services.

These are generalizations, and each provider also offers unique features and benefits. Therefore, you should consider the specifics of your project, the skills of your team, and your business needs when making a decision.

Step 3: Design Your Serverless Architecture

Correctly designing your serverless architecture is crucial. Given its distinct features, such as statelessness and brief execution times, you should tailor your application accordingly. The core principle is to break down your application into small, single-purpose functions that can operate independently when triggered. This way, each function performs its task effectively, enhancing your application’s overall performance and scalability.

Step 4: Develop and Test Your Functions

When developing serverless functions, follow serverless best practices rather than specific recommendations from your provider. The main guidelines are to ensure your functions are stateless, idempotent, and single-purpose.

It’s crucial to meticulously test your functions to verify they perform as expected under various conditions. For this, employ local development tools to mimic the serverless environment during testing.

Additionally, remember that your system will require constant adjustments due to its stateless nature. Hence, strive for minimal configurations to reduce complexity. Ultimately, the aim is to create a robust, flexible, and efficient serverless system.

Step 5: Deploy Your Serverless Application

After thoroughly testing your functions, the next step is deployment onto the serverless environment. Mentioned serverless providers offer various tools and services to streamline this process:

• Amazon AWS Lambda: AWS provides several tools to deploy your serverless applications, including AWS Serverless Application Model (SAM), AWS CodeStar, and AWS Elastic Beanstalk. AWS SAM is an open-source framework for building serverless applications. It allows you to define your serverless applications in simple YAML or JSON syntax. AWS CodeStar provides a unified user interface, enabling you to easily manage your software development activities in one place. AWS Elastic Beanstalk is an easy-to-use service for deploying and scaling web applications and services.
• Microsoft Azure Functions: Azure DevOps provides a complete set of modern dev services for deploying serverless applications. It’s a unified suite of tools that includes Azure Pipelines, Azure Repos, Azure Test Plans, and Azure Boards. Azure Pipelines is a CI/CD (Continuous Integration/Continuous Delivery) platform that lets you automate and streamline your build and release workflows.
• Google Cloud Functions: Google Cloud offers the Cloud SDK (Software Development Kit), which provides a command-line interface for Google Cloud products and services. It also offers Cloud Build, a service that executes your builds on Google Cloud’s infrastructure. With Cloud Build, you can quickly create, test, and deploy your serverless applications. Google Cloud’s Firebase platform also offers Firebase CLI (Command Line Interface), a tool that helps you manage and deploy your Google Cloud Functions.

Remember, the tooling and services for serverless deployment are continually evolving, and providers frequently update their offerings. Therefore, always review the latest documentation and best practices from your chosen provider.

Step 6: Monitor and Optimize

Upon deploying your serverless application, ongoing monitoring is crucial to ensure optimal performance, cost-effectiveness, and system health. The monitoring helps detect any performance bottlenecks, unexpected costs, and potential system errors.

Most serverless service providers offer built-in monitoring and debugging tools. For instance:

• AWS Lambda: AWS CloudWatch collects monitoring and operational data in the form of logs, metrics, and events, providing a unified view of AWS resources and applications. AWS X-Ray helps developers analyze and debug distributed applications, such as those built using a microservices architecture.
• Azure Functions: Azure Monitor collects, analyzes, and acts on telemetry from your cloud and on-premises environments. Azure Application Insights provides insights into the performance and usage of your applications.
• Google Cloud Functions: Google Cloud’s Operations suite (formerly Stackdriver) provides monitoring, logging, and diagnostics.

Using these tools, you can track key metrics like function execution time, memory usage, error rates, and more.

Based on your monitoring, strive to continually optimize your functions with these objectives:

• Reducing execution time: Write efficient code and minimize the dependencies of your functions. A function that finishes quickly consumes less resources and, therefore, costs less.
• Optimizing resource usage: Appropriately allocate the resources (e.g., memory) your functions need. Over-provisioning wastes resources and increases cost, while under-provisioning can lead to performance issues.
• Atomic function design: Break your application into smaller, single-purpose functions. Atomic functions are easier to manage, debug, and scale.
• Fault tolerance and stability: Design your functions to handle failures gracefully and retry operations that are likely to fail transiently.

Transitioning to a serverless architecture is a substantial shift that demands a thorough understanding of the serverless model. But with thoughtful application design, continuous monitoring, and diligent optimization, you can harness the power of serverless technology to simplify your infrastructure management, enhance performance, and curb costs.

Real-World Use Cases

The real power of serverless architecture shines when applied to practical, real-world scenarios. Let’s explore a few examples.

Case 1: Chat Bots

While serverless architecture provides exceptional scalability, using it to manage real-time chat applications for long-running conversations can be challenging due to its stateless nature and function execution time limits (typically around 15 minutes). This means a serverless function doesn’t store any data about the user or conversation history between invocations, making it impractical for ongoing chat sessions.

However, this doesn’t mean serverless can’t be used for chat-related services. A perfect use case for serverless in this context is chatbots. Chatbots, like those found on platforms such as Viber and Telegram, often operate in a stateless manner and don’t require keeping a conversation’s state over an extended period.

In a typical chatbot interaction, the bot responds to a user’s input without needing to remember previous interactions. When a user sends a message to the chatbot, it triggers a serverless function. This function processes the user’s message and sends back a response; then, it is shut down. When the user sends another message, the process repeats.

Each chatbot interaction is handled as a separate event, making serverless architecture an excellent fit for this kind of workload. It allows the chatbot to scale effortlessly, handling thousands of simultaneous interactions without requiring a server to be continuously running.

So, while serverless might not be suited for maintaining long-lasting, stateful chat sessions, it’s an incredibly powerful and scalable solution for stateless chatbots.

Case 2: Know Your Customer and Know Your Business

KYC (Know Your Customer) and KYB (Know Your Business) processes are ideally suited for serverless architecture due to their event-driven, stateless, and independent nature. Here’s how it works:

KYC and KYB are critical compliance processes used in many industries, particularly in banking and financial services. They involve verifying the identity of individuals (in the case of KYC) or businesses (KYB) before establishing a business relationship.

These verification processes typically involve collecting data from the customer, verifying the information against reliable data sources, and assessing the customer’s risk level. As these tasks are mostly independent of each other, they can be broken down into small functions in a serverless architecture.

• Data Collection: This stage involves obtaining required details from the customer, such as name, address, date of birth, and more. This could be triggered by a customer filling out a form on a website, for instance.
• Data Verification: After data collection, a function can be triggered to validate the customer’s details against trusted data sources, such as government databases or credit bureaus.
• Risk Assessment: Based on the verification results, another function could assess the customer’s risk level. This could involve running the data through a machine-learning model or checking against internal and external watchlists.
• Final Decision: Finally, a function could use the results of the risk assessment to make a decision on whether to approve the customer, deny them, or require further checks.

In a serverless architecture, these functions are run only when needed - when a customer initiates the KYC or KYB process. This makes the process highly efficient as you’re only paying for the compute resources when verification is being conducted. Moreover, as these checks are event-driven and do not need to maintain a state between different functions, the serverless model is a perfect fit.

Furthermore, serverless architecture provides automatic scalability. In periods of high demand, the cloud provider can increase resources to handle more verifications simultaneously, then scale down when demand reduces. This ensures you only pay for the resources used, and your system remains responsive even under heavy load.

So, serverless architecture can significantly enhance the efficiency, cost-effectiveness, and scalability of your KYC and KYB processes, freeing you to focus more on core business activities.

Case 3: Data Parsing and Processing

A data analytics platform may need to process vast amounts of data daily. With traditional architectures, this would require large, expensive servers that sit idle when not processing data. With serverless architecture, data processing tasks can be triggered as needed, with costs based purely on the computation time. This can result in substantial cost savings and efficiency improvements.

These use cases illustrate the transformative impact of serverless architecture. By intelligently adopting this technology, organizations can improve external services’ performance, scalability, and cost-effectiveness, thereby gaining a significant competitive edge in today’s fast-paced digital world.

Case 4: SMS and Email Sending Service

A service for sending SMS messages and emails can benefit greatly from a serverless architecture. Here’s a general overview of how this could work:

• Event Triggers: This is where the process begins. An event, such as a user signing up for a newsletter or purchasing on your website, triggers the serverless function.
• Function Execution: Upon being triggered, the serverless function would execute a task, which in this case would be to send an SMS or an email. This might involve using an SMS gateway for text messages or an SMTP service for emails.
• Monitoring and Logging: Serverless platforms typically provide built-in tools for monitoring the performance of your functions and logging any issues that may occur. This can help you ensure that your service is running smoothly and troubleshoot any problems that may arise.

Because serverless functions only run when they’re triggered by an event, you only pay for the actual usage, which can be cost-effective for services like this, where the load can vary greatly. For example, you may have times of the day or certain events (like a sale) that result in a high volume of messages being sent, while at other times, the load might be much lighter.

Conclusion

Serverless architecture is an innovative solution that can simplify many aspects of tech infrastructure, enhancing performance while lowering costs. However, implementing it successfully requires an in-depth understanding of both your technological requirements and business objectives and involves continuous monitoring and optimization to ensure both performance and cost-effectiveness.

It’s important to note that one of the major advantages of serverless architecture is its cost-effectiveness. Many serverless providers offer generous free quotas, allowing you to run a substantial number of functions without incurring costs. This makes serverless a perfect choice for businesses looking to optimize their spending on cloud services.

However, the key to leveraging these benefits is the strategic use of architecture. Not all applications or functionalities need to be or should be serverless. Identifying the parts of your tech infrastructure that can be effectively and beneficially migrated to a serverless model is crucial. This might mean combining different types of architecture, traditional server-based, cloud, and serverless, to best suit your needs.

So, it’s not just about going serverless; it’s about choosing the right blend of architectural models that provide the most value to your business. As you explore the potential of serverless architecture, remember to keep your focus on what truly matters: aligning your tech decisions with your core business goals and innovation. This way, you can ensure your technology choices support your business, not the other way around.