With serverless architecture, developers can create and operate services without the hassle of managing any of the underlying infrastructure. With this, developers can write and deploy code while a cloud provider manages the provisioning of servers to operate their applications, databases, and storage systems, irrespective of scale. We will explore how serverless architecture functions, its pros and cons, and some ways in which a business can go about implementing serverless technology smartly.
Managing servers requires significant time and resources, even though they allow users to communicate with an application and access its business logic. Teams must maintain server hardware, handle software and security updates, and create backups in the event of a failure. Developers can relieve themselves of these responsibilities by adopting serverless architecture, allowing them to focus solely on writing application code.
One popular form of serverless architecture is Function as a Service (FaaS), where developers write their application code as individual functions that perform specific tasks when triggered by an event. After testing, developers deploy their functions and triggers to a cloud provider account, where the provider executes the function on a running server when invoked. If no server is available, the cloud provider spins up a new one to handle the function execution, completely abstracting this process from the view of developers.
Although serverless architecture has existed for over a decade, Amazon launched the first mainstream FaaS platform, AWS Lambda, in 2014. Today, the majority of developers continue to use AWS Lambda to build serverless applications, although Google and Microsoft also provide their own FaaS offerings called Google Cloud Functions (GCF) and Azure Functions, respectively.
The Fundamentals of Serverless architecture
Although serverless architecture eliminates the need for server management, mastering its intricacies, especially when bringing together multiple functions to create complex workflows in an application, can be quite a task. Therefore, it is essential to familiarize teams with these basic terms:
- Invocation: A single function execution.
- Duration: The time it takes for a serverless function to execute.
- Cold Start: The latency that occurs when a function is triggered for the first time or after a period of inactivity.
- Concurrency Limit: The maximum number of function instances that can run simultaneously in one region, as determined by the cloud provider. If this limit is exceeded, a function will be throttled.
- Timeout: The duration that a cloud provider allows a function to run before terminating it. Most providers set both a default and a maximum timeout.
Keep in mind that every Cloud provider may use their own specific terminology and may also set varying limits on serverless functions.
Kinds of Serverless Systems
Serverless systems are fast becoming popular as they ensure that developers can deploy code without worrying about infrastructure. Here is a look at the most common types of serverless systems and their primary functions:
Compute: Serverless compute systems like AWS Lambda give developers the ability to run code and not look into the infrastructure needed. Developers can work this on-demand or based on a schedule. Developers can also choose a preferred runtime and set aside memory for their code. Such systems are used to manage tasks like user authentication and interaction, particularly with external APIs and databases.
Queue/Message Buffer: Queuing or messaging services help with moving data from one part of an application to another. They can separate coupled services or control the volume of data coming in. AWS SQS is one such queuing service commonly used.
Stream Processing: Stream processing systems analyze and process data flow in real-time. They are especially useful in analyzing video and data streams. AWS Kinesis is an example of such a stream processing system.
Event Bus: An event bus delivers messages from multiple sources to several destinations. It brings down service coupling and can be configured with customized rules to ensure that each message is delivered to the right subscriber. AWS EventBridge is a great example.
Database: Serverless database systems range from SQL to NoSQL, Graph, and Analytics. AWS Aurora Serverless is perfect for small data that needs a mix of transactional and analytical access patterns. AWS DynamoDB is ideal for projects that require scaling and for large datasets or write-intensive applications. Graph databases like AWS CloudDirectory are best suited to complex data relationships.
Blob Storage: This system stores objects like text files, images, or videos. AWS S3 is commonly used and is a well-tested serverless blob storage system that easily integrates with other AWS services such as Lambda and Athena for big data analysis.
API Endpoints: API endpoints are implemented via two models, REST and Graph. REST leverages HTTP methods and needs data consumers to know its endpoints and parameters. Graph API supports more flexible queries from data consumers and is used in Facebook.
Benefits and Challenges of Serverless architecture
Serverless architecture has become increasingly popular in recent times, with several companies, right from small start-ups to international corporations, adopting it. One significant benefit of serverless is cost savings, as cloud providers charge on a per-invocation basis, removing the need to pay for unused servers or virtual machines. Additionally, serverless architectures offer scalability, as function instances can be automatically created or removed based on traffic variations within specified concurrency limits. Also, serverless architecture can improve productivity, as developers can focus solely on writing and deploying code without having to manage any servers.
However, some challenges are associated with serverless architecture. One is the loss of control over the software stack, as developers have to rely on the Cloud provider to fix issues of a hardware fault or data centre outage. Security is also a concern, as multiple customers’ codes may run on the same server, potentially exposing application data. Another challenge is the performance impact of cold starts, which can add latency to code execution. Integration testing can also be challenging in a serverless environment.
Serverless architecture can also come with vendor lock-in, as large Cloud providers offer several services that work seamlessly together. This can make it difficult to mix and match elements from different providers.
While serverless architecture is suitable for building scalable and lightweight applications with short-running processes, virtual machines or containers may be more appropriate for long-running processes. Developers may consider using hybrid infrastructure, where containers or virtual machines handle most requests, but certain short-running tasks, such as database storage, are offloaded to serverless functions.
Serverless architecture Use Cases
Serverless architecture has gained popularity due to its ability to reduce operational overhead and scale applications automatically. Here is a look at some of its use cases:
Trigger-based tasks: One use case for serverless architecture is trigger-based tasks. Any form of activity that sets off an event or a series of related events makes is ideally suited to a serverless architecture. For example, a user signing up on a website may trigger a database change, which may, in turn, trigger a welcome email. This kind of work can be handled via a chain of serverless functions.
Building RESTful APIs: Another use case for serverless architecture is building RESTful APIs. For example, Amazon API Gateway with its serverless functions can be used to build RESTful APIs. These APIs can be scaled on demand.
Asynchronous processing: With serverless functions, all background application-related tasks can be handled without disturbing the functioning of the application or introducing any latency that the user may see. Providing product-related information or transcoding videos once uploaded can easily be taken care of.
Security checks: Serverless architecture can also be used for security checks. For example, when a new container is being brought up, a function can be triggered to look for any non-conformity in configurations. It can also check for vulnerabilities. Some functions also help enhance security by providing SSH verification and two-factor authentication.
Continuous Integration (CI) and Continuous Delivery (CD): Serverless architectures can be utilized to automate multiple stages in the CI/CD pipelines. For example, a function to create a build can be triggered by a code commit and similarly automated texts can be triggered with a pull request. With this, developers work on migrating to serverless architecture gradually and in stages, moving some parts, while the rest stay on traditional servers. The benefit of serverless architecture is that they are easily extensible.
Tools That Support Serverless architecture
To smoothen the transition to serverless architecture and ensure optimal application performance for users, it is important to use the appropriate tools. A serverless deployment framework like Serverless Framework or Amazon’s Serverless Application Model (SAM) can interact with the Cloud provider’s platform via API, allowing you to define functions, triggers, and permissions. Additionally, some providers like AWS offer serverless testing and security tools to test for vulnerabilities, block code injections and unauthorized executables at runtime.
After building a serverless application, it is crucial to monitor its health and performance as serverless functions can navigate through a complex web of micro-services, resulting in cold starts, misconfigurations, and other errors that occur at any node and cause ripple effects through the environment. Real-time visibility into how each function performs, both individually and in relation to other functions and infrastructure components, is essential to troubleshoot issues effectively.
Datadog Serverless Monitoring is all-encompassing application monitoring solution that ensures a business has real-time visibility of its performance of serverless functions and infrastructure components. This tool collects metrics, traces, and logs from all invocations, and supports several deployment frameworks and languages. This makes it simple to monitor serverless architecture in as short a time frame as minutes.
Six Things to Know Before Migrating an Existing Service to Serverless
If you are planning to migrate to serverless architecture, here are six key things to keep in mind for your business.
Determine the Problems to Be Solved: This is the most fundamental requirement. What are the challenges that serverless resolves for you that your current system does not? For example, if your company is looking to reduce operational costs and replace a set of monolithic systems with a small team, these are problems that can be solved. AWS Lambda may be the ideal solution to serve as a bridge between different AWS-managed services.
Train Your Team: Once you have identified the issues, it is simpler to determine what set of technologies best works for your business. Your in-house developers will be familiar with your business logic and service requirements, making it more practical to train them than to outsource. If your existing team is unfamiliar with serverless, this would be the ideal time to train them. To facilitate learning, encourage your developers to attend meet-ups and conferences and ensure they spend time experimenting with new technologies during work hours. You could also consider hiring a serverless consultant to teach them how to think in an event-driven way and ensure best practices are followed.
Create a Proof of Concept for Validation of Your Hypothesis: Once you have identified the key problems you are looking to address, you can ensure your team’s buy-in with a strong proof of concept. Your team will already be aware of the hypothesis you have been working on and know what is required. The proof of concept will help them verify this hypothesis. It can be used to place the focus on your issue and then can be done away with.
Optimize the Solution to Leverage Cloud Benefits: This step is critical and linked to the previous one. When considering your proofs of concept and new architecture, it is essential to take full advantage of the cloud. Do not just take your instances and decompose them into AWS Lambdas and API Gateways using DynamoDB; think about how to leverage cloud-managed services like queues and caches.
Additionally, remember that migrating everything to serverless transforms your system’s architecture into an event-driven architecture, where events move around your system, and all services are decoupled from each other. AWS provides many services to manage event communication, such as queues and streams.
Automate Your Continuous Integration/Continuous Deployment Pipeline: Serverless architectures involves deploying many resources into various environments in this manner. Automate everything you can when you have several moving parts to simplify things.
What To Keep In Mind
To help ease the transition to a serverless architecture, there are several key tips to keep in mind. First, it is crucial to recognize the limitations of serverless and evaluate if it is the right solution for your application. Those applications that require high-compute or long-running processes may not be ideally suited to serverless. Therefore, it is important to assess your use case beforehand.
Secondly, establishing a robust plan for monitoring and debugging in a serverless environment is essential. Since serverless functions are event-driven, conventional monitoring and debugging methods may not be effective. Tools like CloudWatch Logs can help, but it is vital to have a strategy in place for identifying and resolving issues.
Breaking down monolithic applications into smaller functions is also recommended. This approach allows for more straightforward deployment and scaling of individual components, potentially enhancing security by reducing the attack surface. It is also beneficial to design functions in a “stateless” way, so they can be scaled horizontally and are not influenced by previous events.
Finally, a good testing strategy is essential in a serverless environment, as functions are event-driven. Unit testing before deployment, end-to-end tests on the real deployed infrastructure with automatic rollbacks in place, and performance testing to assess production-level traffic are all critical components of a comprehensive testing strategy.
To summarize, adopting a serverless architecture can offer numerous benefits, including increased innovation, developer velocity, and cost reduction. However, transitioning to a serverless architecture can be challenging. By understanding the limitations of serverless, having a plan in place for monitoring and debugging, breaking down monolithic applications into smaller functions, and creating a thorough testing strategy, a business can make the transition smoother and enjoy a full range of benefits.
