Podcast Summary
Front-end vs Back-end evolution: The need for more interactive applications led to the distinction and separation of front-end and back-end technologies in software development.
The evolution of software development has led to a clear distinction between front-end and back-end technologies. Gishan Manandar, a senior staff engineer at Simply Wall Street, shared his origin story, starting with HTML, CSS, and JavaScript in the early 2000s. He then progressed to formal studies in C++ and Java before moving into PHP, Node.js, and JavaScript for professional work. Gishan's career has taken him across three continents, and he's witnessed the shift from monolithic applications to the SOA and microservices architecture, which introduced the concept of front-end and back-end engineers. In the early days, PHP was the primary tool for building both front-end and back-end, but as interactivity became a priority, the need for separate front-end and back-end technologies emerged. Gishan's experience mirrors this trend. He started using Node.js and TypeScript for back-end development around 2015, while older applications remained in PHP. The shift from having everything in one place to having separate front-end and back-end technologies was driven by the need for more interactive applications and the ability to update parts of the page without requiring a full page refresh.
Backend evolution: Backend engineers need to adapt to new technologies and expand their skillset beyond server-side logic to keep up with the evolving web development landscape, while also maintaining a balance between specialization and generalization for effective collaboration in the DevOps environment.
The role of backend engineers has evolved beyond just handling server-side logic, with the increasing complexity of infrastructure requiring a broader skill set. JavaScript frameworks have emerged to enable dynamic web pages by adding and removing elements without refreshing the page. These frameworks, including early Ajax implementations and modern ones like React and Angular, all aim to streamline the user experience. While this can be a good thing for engineers looking to expand their knowledge, it also necessitates a balance between specialization and generalization. The DevOps movement further emphasizes this need for collaboration and communication between teams, as the code written by software engineers eventually runs on intricate systems like Kubernetes.
Incident response in distributed systems: Testing, logging, monitoring, and observability are crucial for identifying and solving issues in distributed systems. Shared responsibility and balanced escalation procedures are essential for effective incident response.
As a software engineer, being responsible for the software you build and its incident response is crucial for ensuring its resilience. The distributed nature of backend systems can make incident reporting and response more challenging due to the complexity involved. However, it also provides opportunities for learning about other parts of the system and collaborating with other teams. The importance of testing, logging, monitoring, and observability cannot be overstated, as they help in identifying issues and solving problems. Incident response should ideally be a shared responsibility, with a balanced approach to on-call rotations and escalation procedures. The goal is to build and run software with a focus on resilience, ensuring that incidents are minimized and effectively handled when they do occur.
Prioritizing precautions: When dealing with complex backend systems, prioritize precautions over immediate solutions. Use post-mortem discussions, follow a blameless process, and understand system size and dependencies. Choose the right tools based on requirements and ensure a blameless post-mortem process.
While dealing with complex backend systems and releases, it's crucial to prioritize precautions over immediate solutions. Post-mortem discussions, following a blameless process, and having a clear understanding of the system's size and dependencies are essential. The choice of language or tool for a task depends on the specific requirements, such as latency sensitivity. Kubernetes, as infrastructure as code, can be complex but also offers benefits, such as creating and managing infrastructure through code execution. It's essential to separate the concepts of infrastructure as code and Kubernetes as a system for container orchestration. Ultimately, the focus should be on using the right tools for the job and ensuring a blameless post-mortem process when issues arise.
Docker vs Serverless: For smaller apps with fewer users, traditional VMs may be suitable. For larger apps with complex systems and high traffic, consider Docker, Kubernetes, or serverless platforms based on resources and team expertise.
Docker containers and the related technologies like Kubernetes, serverless, and serverless containers, offer significant benefits for managing complex systems at large scales. However, these technologies come with their own complexity and require dedicated teams and resources. Serverless infrastructure, such as function-as-a-service (FaaS), offers the advantages of no infrastructure management, high availability, and pay-per-usage. Containers, on the other hand, provide the flexibility and control of packaging your application and dependencies into a single unit. When considering the use of these technologies, it's important to assess the size and complexity of your user base. For smaller applications with fewer than 100 users a day, traditional virtual machines may still be the most suitable option. However, for larger applications with thousands or even millions of users, container orchestration tools like Kubernetes, serverless platforms, and serverless containers can offer significant benefits. In summary, the decision to adopt container technologies like Docker, Kubernetes, and serverless containers depends on the scale and complexity of your application and the resources available to manage the associated complexity.
Serverless containers advantages: Serverless containers offer automatic scaling, minimal configuration, and cost efficiency, making them suitable for web apps and smaller teams. Google Cloud Run is an example of a serverless container platform that allows users to configure resources and pay nothing when their app doesn't receive traffic.
Serverless containers offer advantages such as automatic scaling, minimal configuration, and cost efficiency. They are particularly suitable for web apps and smaller teams, as they eliminate the need for managing infrastructure. Google Cloud Run is an example of a serverless container platform, which allows users to configure CPU, memory, minimum instances, and maximum instances. With serverless containers, users pay nothing when their app doesn't receive traffic, making it a cost-effective solution. The difference between serverless containers and a fully managed Kubernetes platform lies in the level of flexibility and team size. For most apps, serverless containers are sufficient, and they offer the benefits of being highly available and scalable. Nick from Halfbrick Studios, for instance, reported that Cloud Run eliminated the need for an additional DevOps engineer. Furthermore, Google Cloud Run offers jobs for long-running tasks, making it a versatile solution for various use cases. A notable individual who shared valuable knowledge on Stack Overflow was Matthew Reed, who provided an answer to a question about case-sensitive code search on GitHub, earning a populist badge. If you have thoughts, feedback, or show ideas, or if you'd like to be a guest on the podcast, email podcast@stackoverflow.com.