How can you build a web application that can handle any traffic?

Scalability Requirements: services need the ability to scale resources quickly for varying levels of demand. High availability SQL clusters must be designed to handle dynamic scaling, which might involve adding or removing nodes to manage increased traffic effectively. Security and Compliance: services that handle sensitive customer information such as payment information, making security a top priority. Any infrastructure setup must adhere security best practices and compliance requirements such POPI Act to prevent data breaches and ensure data privacy.

Think of cloud computing as your reliable IT buddy in distance, ready to offer you services anytime! Here are why it is true: Flexibility at Your Fingertips: Cloud computing gives you the power to adjust resources like a pro. No fuss, just results! Scalability Made Simple: Expanding your app's resources is as easy as selecting a local street food - effortless and satisfying! Budget-Savvy Choice: Cloud computing keeps your wallet happy by ensuring you only pay for what you need. Reliability always on: With cloud computing, your app is a true warrior. It stands strong, even if your hardware or software takes a hit. Managed Cloud Services: Like having your IT tasks outsourced to experts, freeing you to focus on your core business.

Dynamic Scalability: Clouds like AWS auto-scale resources to meet web traffic demands. Cost-Efficiency: Only pay for resources used, ideal for unpredictable traffic spikes. Reliability: Cloud providers' multiple data centers ensure consistent application availability. Managed Services: They optimize app performance with services like managed databases. Security: Leading cloud platforms prioritize app protection with encryption and firewalls. Simplified Deployment: Tools offered make deployment and monitoring seamless. Cloud computing is vital for ensuring scalability, efficiency, and resilience of high-traffic web applications.

Functional programming as foundation principle: Software architecture determines how the lower layers perform when handling parallel requests. Functional programming has been shown to better fit to stateless applications. As stateless applications require less memory consumption, the hardware limitations (even in cloud environments - costs - ) becomes a smaller problem, so we can better scale horizontaly.

Careful planning, architecture design, and implementation of multiple technologies and best practices are necessary for web application to handle any traffic. Building a highly scalable and resilient application requires the use of cloud services like AWS, GCP, or Microsoft Azure, as well as the implementation of load balancing, auto-scaling, caching, a content delivery network, database scaling, asynchronous processing, fault tolerance, monitoring and analytics, performance optimization, security considerations, continuous deployment, scalable infrastructure components, and performance testing. A system should be expand both horizontally and vertically for handling realistic traffic volumes while maintaining performance and dependability

Centralized Configuration Management is among the most underrated aspects of a reliable and flexible distributed platform. Having a highly configurable platform and the ability to dynamically change configuration during runtime makes a huge difference, especially in environments where requirements are dynamic or customer behaviour or system KPIs are always changing.

A few things regarding distributed systems: Keep it modular - in the modular approach it is easier to keep the whole web app up and running if there is a bug or a break in the system. Enable regular backups in order to keep the system up to date in case of any untoward case. Spend time in creating and maintaining CI/CD, the more distributed the system is, it is essential to have a CI and CD pipelines which can enable you to make changes seamlessly.

To handle the large number of requests we need to have microservice architecture and these microservices need to have independent databases not relying on the database that uses other services. We need to have very heavy usage of queues, and events so it is very easy to communicate with each other in a system.

I will add the vale of running a system in parallel or mirror instances. This is extremely useful when the service you provide to the customer is expected to be up 24/7. With this solution, if one instance is down, the balancer redirects all traffic to the working one, keeping service up meanwhile the issue is detected and solved.

Horizontal Scaling: Distribute load across multiple servers for seamless scaling. Fault Tolerance: Distributed systems ensure high uptime, continuing even when components fail. Load Balancing: Distribute traffic evenly, preventing server overload and optimizing uptime. Data Consistency: Replication maintains updated data across nodes, ensuring user experience consistency. Microservices: Independent services offer easier management and precise scaling. Service Discovery: Tracks nodes, facilitating effective inter-service communication. Caching & Replication: Store frequent data for quick access and replicate for reliability. By harnessing distributed systems, web-app gain resilience and scalability, handling varying traffic demands

Performance testing is the most crucial part on finding any issue regarding web application performance. We cannot assume what causes the slowness in our application, whether it is network, upstream/downstream response or our own application. The first thing to do is to test our application's performance in a controlled environment in which no other developers or users accessing it. As an example, we use JMeter to simulate hundreds of users using our application, and monitor our database's performance using TKPROF. In parallel, we also monitor the server's resources via NMON. As it turns out, we had insufficient RAM in our server which bottlenecks the traffic. In this way, we have a solid proof to back us on areas that needs to be improved.

You also need a scalable and robust DB that can handle huge traffic from the users. Take for instance in MySQL we have transaction which can help to speed something up when you have large users base. Caching is very important in order to have a fast response when there are huge request and you can as well use third party caching system like memached or redis

Essential for Retention: Swift apps keep users engaged, affecting retention. Use Analytic Tools: Lighthouse pinpoints inefficiencies, guiding improvement. Beyond Code: Consider content delivery and server responses. Frameworks Matter: React, for instance, offers an efficient foundation. Strategies: Limit resource requests, reuse components, and use caching. Ongoing Process: Tech evolves; our optimization strategies should too. Optimized web apps enhance user experience, SEO rankings, and engagement.

Enhance app performance through a Content Delivery Network (CDN) like Cloudflare, utilize Edge Computing platforms such as AWS Lambda, incorporate Client-Side Rendering frameworks like Next.js, and implement edge caching with tools like Varnish. Employ latency testing tools such as Pingdom and monitoring solutions like New Relic to ensure optimal user experiences.

Performance optimization is an ongoing process and IMO, it's very important to keep this in mind throughout the whole development process. Since I experienced performance bottlenecks and I spent few weeks to fix them, there are rules of thumbs that I follow blindly. - Every line of code matters - Do not start too early with optimization process - Make a good scalability plan for future scalability by designing the system to scale easily when demand increases - Properly architecture the project - Follow the best practices for the language / frameworks you are using - Use packages wisely - Provide automated performance tests and perform load and performance testing - Use CI/CD so the code is constantly updated

I think it is better to mention "deployment management" and "tracing". --- I don't know why but LinkedIn says contributions must be at least 125 characters long.

The fact that cloud computing should always be orchestrated by experts not just hobbyists, a cloud engineer must have a clear understanding of what are the risks of disruption and what to give in return. Also how to handle complexity and components orchestration and how to make the systems fault tolerant. Many systems do not need to be distributed at all. It is just a use case of computing that may be followed on demand. So, still there is a need always to other computing models.

Reliability is the bedrock of user trust in web applications. By anticipating failures, we can design apps to withstand them. Leveraging automated tests and comprehensive logging, we can preemptively address vulnerabilities and expedite issue resolution. Clear error messages maintain user trust during unforeseen hiccups, while robust backup systems minimize downtime. Prioritizing reliability is paramount to ensuring user engagement and faith in our applications.

Reliability engineering also ensures scalability and security. As for what the job of a reliability engineer involves, I believe we could sum it as "systems engineering best practices" and leave it as abstract as the actual job is per organisation.

-- One thing I've found helpful about Reliability is its pragmatic approach to fortifying web applications. For instance, incorporating redundancy in server setups. By having multiple servers, if one fails, traffic is automatically redirected, ensuring uninterrupted service. -- We can foster innovation. By automating repetitive tasks through scripting, developers have more time to experiment with new features. -- An example I've seen vividly. Imagine an online streaming service experiencing sudden spikes in viewership due to a viral video. Without proper load balancing, the service could crash but by utilizing scalability tools, like auto-scaling on cloud, the system dynamically adjusts resources to match demands.

We can look at security at following levels 1. Is my data secure during transit? Here is where ssl encryption comes into picture. We have HTTPS where the data is encrypted using a key which only sender and receiver knows. 2. Who can the access data? 2.1 Authentication First we need who is really accessing the data. Here is where authentication comes into picture. We provide something like username-password, apikeys, OAuth tokens etc. These 'secrets' help us identify the person (or more technically the principal) trying to access the data. 2.2 Authorization A server could have various kinds of data. Once we know the principal through authentication, we can check whether this principal really has the access to a specific data.

Security is the cornerstone of any robust web application. In an age of increasing cyber threats, hardening defenses is not just recommended but essential. It's not just about implementing tools like SSL or firewalls but understanding their significance in the larger security landscape. While these tools fortify our applications externally, frequent audits and updates handle latent vulnerabilities. Using OAuth ensures controlled access. Yet, it's a relentless journey – the cyber landscape evolves, so must our security practices. Staying updated with the latest trends and proactively seeking feedback is how we stay a step ahead in the security game.

Investing in SecOps and establishing a specialized team enhances web app security. Through OS hardening, vulnerabilities are minimized. Firewalls, including Web Application Firewalls (WAFs) like Palo Alto, thwart threats. Robust user management ensures controlled access. This proactive defense, coupled with continuous monitoring, safeguards against breaches. A SecOps team ensures timely threat detection, patching, and adherence to best practices, fortifying your web app against evolving cyber risks.

One important thing to note while building distributed systems are tradeoffs. You can never have the perfect system. This is illustrated by the CAP Theorem that shows a distributed system can only guarantee two of three properties: consistency, availability, and partition tolerance. The CAP theorem was invented by Eric Brewer in 2000.

Create a Pizza Team of 7 - 8 pods. Each Pod is a specialized skill that works to complete a Team. Consider DevSecOps, SuperEngineering (DevSecOps,SRE, Infra Engineering) as the core. A Cloud Center of Excellence optimizes cloud infrastructure and operations, ensuring scalability, efficiency, and security. A Red Team conducts proactive security testing, simulating real-world attacks to identify vulnerabilities. Together, they guarantee web app success by maintaining top-notch performance and fortified defenses against emerging threats. Automate! Automate! Automate everything! ... including your morning coffee! ;)