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Ah “serverless”... the promise of running applications without worrying about servers! The term "serverless" often sparks skepticism among those rooted in traditional software development practices. The idea of handing over control over infrastructure may seem daunting, and developers might wonder if serverless is even right for their use case. My goal in this blog is to demystify serverless computing (in particular, serverless deployment) without unnecessary complexity.
The software development landscape has witnessed a fundamental transformation through the lens of abstraction. The rise of Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) marked a pivotal shift, freeing engineering teams from the nitty-gritty of infrastructure concerns with the advent of Software as a Service (SaaS).
The massive adoption and growth of Kubernetes, a powerful container orchestrator, redefined how the underlying infrastructure can be abstracted away from engineers who build and deploy containerized applications. In a concise analogy, Kelsey Hightower tweeted: "Kubernetes is not the kernel; it's systemd." This emphasizes its role as a higher-level orchestrator, adept at handling the deployment, scaling, and management of containerized applications.
As we delve into Serverless computing, it represents the apex of abstraction, pushing the boundaries even further. Beyond Software as a Service (SaaS), Serverless encapsulates Functions as a Service (FaaS), providing a powerful tool for engineers to zero in on their code. It simplifies by abstracting away server management complexities, embracing a dynamic, event-driven model for resource efficiency.
In the realm of FaaS, a function acts as "glue code," seamlessly connecting and extending existing services. This approach utilizes a runtime framework where you deploy a compact snippet of code, not an entire container. Within this snippet, you implement a single function or override a method, specifically designed to handle incoming requests or events. Importantly, there's no need to start an HTTP Server manually.
The beauty of FaaS lies in its serverless nature, offering a straightforward developer experience where concerns about the runtime of your code fade away. Scaling is inherently built in, ensuring a seamless and hassle-free experience.
It's crucial to note that Serverless extends beyond the handling of HTTP requests. You can think of FaaS as a subset of Serverless but Serverless is not FaaS.
Using Serverless Computing comes with some great advantages that make a difference on cost, scalability, overhead, and more in how software is delivered.
With Serverless, you only pay for what you use, like paying for the energy you use at home. No big upfront costs for infrastructure – it's a flexible and budget-friendly way to handle computing resources.
Serverless adjusts automatically to handle more or fewer tasks. When your app gets busy, it scales up. When things slow down, it scales down. This flexibility keeps your app running smoothly without wasting resources.
For developers, Serverless means less hassle with servers. You can concentrate on writing code, and when it's time to put it into action, Serverless takes care of the technical details. The burden of setting up compute infrastructure is abstracted away, letting you focus on your code without dealing with the nitty-gritty of server management.
Serverless computing is a flexible approach that can be applied to many different areas. Let's explore key use cases where serverless computing proves to be a valuable solution.
Serverless computing is tailor-made for dynamically changing workloads. For websites and APIs with fluctuating traffic, serverless allows automatic scaling up or down based on demand. This ensures optimal performance without the need for manual intervention, making it an ideal solution for handling varying user loads.
In event-driven architectures, serverless excels at processing and responding to events in real-time. By leveraging serverless capabilities, organizations can effortlessly manage event streaming, reacting promptly to changes and ensuring seamless communication between services.
Serverless is a natural fit for processing events, especially in scenarios where events trigger specific actions. Integrating with Software as a Service (SaaS) applications becomes more streamlined, allowing organizations to automate tasks, synchronize data, and enhance overall workflow efficiency.
Serverless computing seamlessly integrates with hybrid cloud models, where applications span both on-premises and cloud environments. This flexibility ensures that organizations can deploy and manage applications without being constrained by the limitations of a single hosting environment.
The scalability and event-driven nature of serverless make it an excellent choice for IoT applications. Handling data from numerous devices and responding to events in real-time is simplified, allowing for efficient processing and analysis in IoT ecosystems.
In the fast-paced landscape of software development, the ability to iterate rapidly is more crucial than ever. CI/CD pipelines play a pivotal role in enabling organizations to ship code in small, incremental updates, ensuring that bug fixes and other enhancements can be seamlessly delivered on a daily basis.
Serverless computing amplifies the power of CI/CD by automating key processes in the software development lifecycle. Code check-ins can trigger the automatic building and redeployment of websites, while pull requests (PRs) can initiate the execution of automated tests, ensuring thorough code testing before human review. This automation not only accelerates the delivery pipeline but also enhances the reliability and quality of the software being deployed.
When exploring the automation possibilities within Serverless Applications, the potential to eliminate manual tasks from the workflow becomes apparent. From triggering builds and tests to orchestrating seamless deployments, serverless computing empowers development teams to focus on coding and innovation rather than getting bogged down by manual, time-consuming tasks. This shift toward automation not only increases efficiency but also reduces the risk of human errors, ultimately contributing to a more agile and responsive development process.
While Serverless computing offers a multitude of benefits and has a number of use cases, it's crucial to acknowledge that it's not a one-size-fits-all solution. Like any technology, Serverless has its own set of challenges.
With rapid autoscaling comes unpredictable billing. Just as you consider factors like performance, security, and scalability, now, costs are an essential aspect of your code in serverless architecture. It's crucial for you as a developer to be aware of these costs and, importantly, to have control over them.
Serverless platforms may not offer the portability freedom you imagine. While your code is portable, the triggers and scaling mechanisms are often specific to each cloud provider. For instance, the supported versions of languages may vary, impacting the migration of code across different platforms. Solutions like Kubernetes-based offerings provide some relief but come with their own set of choices and opinions.
Despite the promise of abstraction, many Serverless implementations still involve choices in infrastructure. Options like Apache OpenWhisk, Open FaaS, or KNative offer more generic serverless infrastructure but require maintenance. The rapid and sometimes unpredictable scaling of functions demands careful cluster capacity management, introducing complexities of its own.
Serverless shifts complexity, especially in short-lived and rapidly scaling functions. While it simplifies certain aspects, the management of state becomes critical as functions may need to interact with external systems to maintain continuity. However, these challenges don't have to be insurmountable. Leveraging tools like the Serverless Framework can provide a solution by abstracting away some of the complexities.
With the ease of invoking serverless functions, there's a risk of falling into the Big Ball of Mud antipattern. The rapid instantiation of "serverless containers" can lead to the inclusion of excessive logic in a single function. Advanced tools like Amazon Step Functions make orchestrating multiple functions easier but require careful design to avoid complexity pitfalls.
Unlike traditional systems, Serverless introduces the concept of cold starts, where every request triggers the instantiation of a new serverless container. This is particularly critical in languages like JAVA, demanding thoughtful design and infrastructure considerations.
To mitigate this challenge, hyperscalers like AWS have introduced solutions to enhance the performance of serverless functions. For instance, AWS has introduced SnapStart for AWS Lambda functions running on Java Corretto 11. This feature significantly improves function startup performance, providing up to 10x faster initialization, without incurring additional costs.
The principles that govern traditional production controls also apply to serverless deployment. While modifying or patching a Lambda is remarkably straightforward, similar to a traditional system, it's essential to maintain disciplined practices. Hot patching in production, even if it's relatively easy for serverless functions, raises concerns about maintaining control and adhering to Software Development Life Cycle (SDLC) principles.
Enterprises employ production controls to prevent unauthorized modifications and ensure a structured approach to changes. This discipline is equally applicable to serverless functions, and while it's tempting to make in-line modifications using tools like the AWS Lambda editor, it's crucial to integrate serverless deployment into a robust CI/CD pipeline.
A well-orchestrated CI/CD pipeline that incorporates serverless functions offers several advantages. Firstly, it extends the same level of diligence and confidence established by the SDLC and Continuous Delivery processes to serverless workloads. This ensures that modifications to serverless functions follow a systematic approach, aligning with established organizational standards.
Moreover, integrating serverless deployment into your CI/CD pipeline enhances early defect detection, increases productivity, and promotes faster release cycles. Advanced deployment strategies become feasible within a comprehensive CI/CD pipeline, including canary releases, blue-green deployments, and feature toggles, allowing for controlled testing and gradual rollouts.
By extending the CI/CD pipeline to encompass both serverless and non-serverless workloads, organizations can achieve consistency and efficiency across their entire application landscape. Utilizing a CI/CD increases early defect detection, increases productivity, and enables faster release cycles, reflecting the agility and efficiency that serverless computing promises within a disciplined development and deployment framework. This approach not only streamlines the management of serverless functions but also aligns with best practices in software delivery, promoting reliability and maintainability.
Now that we've explored the fundamentals and nuances of serverless deployment, it's time to put theory into practice. Harness Continuous Delivery (CD) empowers you to seamlessly integrate serverless deployment into your CI/CD pipeline, ensuring a disciplined and controlled approach to managing your serverless functions.
To begin your hands-on journey and unlock the potential of Harness CD for serverless deployment, delve into our tutorials:
These comprehensive guides will walk you through the process of deploying sample functions seamlessly using Harness pipelines.
Sign up for our free plan, start building and deploying with Harness, take your software delivery to the next level.
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Learn intelligent software delivery at your own pace. Step-by-step tutorials, videos, and reference docs to help you deliver customer happiness.
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