Aravind Kumar

Hello, I'm Alvin Kumar. I'm a full stack developer with 4 years of experience. Yeah, I think my face is looking clear now. So I'm a full stack developer with 4 years of experience, especially in the MERN stack. The MERN stack involves handling MongoDB, Express, React, and Node.js. In addition to this, I can work with Next.js and Nest.js. Nest is a back-end framework, similar to Express, but built with TypeScript. Next.js is also an added framework to React.js, which is useful for server-side rendering. This allows me to work with different front-end and back-end frameworks, as well as different databases like PostgreSQL and MongoDB. I have experience working on various applications, including one that allows users to fetch and process data, perform OCR processing, and convert data into a user-friendly format. I also worked on a front-end project where I created responsive web designs with good-looking UIs that are cross-browser compatible. So, this is some introduction about me.

This is in React application architecture to efficiently handle the highest volume of state changes. So, the highest volume of state changes. Yeah. So, basically, state changes Using Redux, we can use. And another state management tool, we have in Hooks, we are able to do with custom APIs. And, also, we have a separate hook, like the UseReducer hook. So, with compared to this, I guess, RedX, I mean, the RedX toolkit. So, this thing is, RedX is the best tool for state management, where we can get all the state that has been given to reusable components or combination components. So, we can access the state in any place. And, also, we can use the state in different stages in applications. So, that can effectively improve our application performance also. In the architecture level, in a React application, that could mean less time for loading. So, after that, we can add help with lazy loading and all. We can use it in different styles of state components also.

How do you approach error handling in Node GCP to make it robust and developer friendly? So error handling is a quite interesting topic. Error handling can be handled by generally using try-catch blocks. And if it's a promise, we can use the resolve and reject methods. And also, asynchronous calls have been maintained in callbacks, promises, and async/await. So, like this, we can handle this. So error handling is a good thing. Why? Because it means we can catch different kinds of errors. For example, if our input is giving us a different kind of information, that could make a side effect in our DB queries or any third-party integration. So, that might go wrong. It's good to handle this kind of situation with error handlers. This might not break the whole application, and which will not close this. This will help us to run the application without any breakages. So, that will create a robust and developer-friendly application. Not only in Node.js apps, we can do error handling in backend coding. Also, we can use it in frontend also, wherever we are making async calls. So, based on that, we'll have some status codes from the backend server. We can show the message to the user, like the server is busy or server is closed, because that is so mandatory. If something is broken, we need to show it as a message, not that the app is broke or app is stale and functional. Our app could be maintained different kinds of errors, it needs to handle. So, that's why this is a crucial thing. We need to do it here. Yeah, thank you.

During peak hours, a specific database query is causing slowdowns. How would you identify and optimize the bottleneck? So during peak hours, a specific database query is causing slowdown. How would you identify and optimize the bottleneck? So specific data, database queries slow down. What we can do is debug the thing, which base or which table is causing the exact issue. And based on that, we need to debug it. We can add log statements to it, and we'll check which query is creating the latency. So based on that, we will check. Most of the time, it will fail if we maintain some complex queries. Otherwise, if the server connection, the HTTP connection between the database instance to the server is quite unresponsive or might give a latency. So we will check where the exact problem is arising. And we will handle that case differently. If the queries in query side are failed to give a latency, we need to reduce it. Like for example, in SQL queries, if we have big queries, we will use joins and subqueries. We are looping around joining two tables, and making it as a sorting or ascending or descending thing. So we will check which processes continue continuously, and we'll find that. We need to find that. And based on that, we can find whether we can separate the queries or handle that particular situation. Whether it is through throwing an alarm at particular rows that might restart the things and all. So we will need to look into that deeply. And after that, we need to solve it accordingly.

Given the following JavaScript function, I didn't feel the potential issue considering the same nature of JavaScript. What could be the undetected behavior? So function fetch data and process, like, fetch data, assume fetch data is in as operation process data. Explain how would you rectify this error. Process data. Okay. And this code is that's That's it. given the following JavaScript function, identify the potential issue, Considering the async nature of asynchronous nature. So what I'm saying is an Unintentional behavior means so, obviously, fetch data function, Which data function, fit inside the function, fetch data and process. So let data call to fetch data. it's in a synchronous function, which might give some, give us some data from any third party or any API, e d a p. So, obviously, we will, so that status of the status should be, not come correctly if we didn't make this as an await. So if we make that await where, obviously, we need to make the function The fetch data and process function should be an asynchronous function. Async, we need to, prefix the function with the async keyword. And after that, it awaits only. we will get the data, and we will, we will get the data and put to let data. And let data holds hold some value. And processed data will, process the data, what we'll get from the fresh data. So in QuickChart, fetch data, we need to, prefixed with the wait and function, we need to prefix with async. So that's it. Thank

Real time data updates can be implemented efficiently in React JS using various options. There are several choices for real time data, including a TCP connection, which can be established using a circuit or socket, both of which are similar. Another option is to use RPC or gRPC. For front-end real time data updates, the need is mostly for applications such as stock tracking, where data streams in and needs to be updated quickly. Chat applications also rely heavily on real time data updates. In such cases, WebSocket is a suitable choice. It requires creating a socket connection between the front-end and back-end, with the front-end acting as an emitter and the back-end handling events based on different statuses. When a single device or multiple devices connect to the socket, broadcasting different types of data becomes necessary. This can include broadcasting to different systems that have connected to the broadcast. This is the end of the explanation.

Consider the following API creation code. Consider the following API creation code using Node. Js. What would be the security concern in this code snippet, and how could you improve it to other best practices. So best practices, authenticate a user. User is authenticated. It's in session ID for not on user. Discuss what the security risk here and how you mitigate it. Security. Authenticate user. The security concern. So what I'm thinking is a security connection here. So the password the password we are sending, through the through the request, through the request body. So in the request body, we are sending the password. And, so we need to so, obviously, whenever we'll check it, if any third party is included, like, OAuth or Cognito, we need to connect to that. Otherwise, we can simply, pass this and check with this. And this authenticated session ID Session ID, we can not directly, send it via session ID. SS, it's like an SSL token, I guess. SSR loss as an ID, which will, just give me a second. I'm having. Yeah. Sure. Yeah. So session ID yeah. This is looking like in, we can't, have a session ID. Username. Username. So means security means we can, Add a multifactor authentication over here. Otherwise, user.sessionid is, like, User transition ID. Yeah. I guess this is fine. if we Add the MFA multi factor authentication, then we can have it. So other than that is authenticated, this session sending the session over the response. And whether it is not, we are considering with the 4 not, 4 not Traged user. Yeah. This is looking fine. We can able to, use the MFA, I guess. Thank you.

So, when React component life cycle method snippet, that's a common anti-pattern that can lead to multiple rate renders. This is an issue because, whenever we are setting the state, the state is not updated in a synchronous manner. So after quite a long time, only the state will update. Whenever we need to update state is in true. After that only, it is going and updating the need to update to false and fetching the data. So after this, need to update is false, then also, it will come to the component update method. Because of some component is updating. This will come to the lifecycle method. And again, this will be a possibility of multiple re-enters. So how can I fix this? I can maintain need to update through a different state. Otherwise, I can handle with different lifecycle methods. So, different lifecycle methods can handle that will work after the updates. So, before component update will work as a before thing. So this will be on a loop. I can change shouldComponentUpdate to a lifecycle method. I can able to get this from good, get this stopped from multiple rate renders.

We can go with TypeScript tags because wherever we are maintaining like, wherever we are confident about what we are sending, and we are confident about what we're getting, and we'll be confident about what we are sending. So this primary step is handled completely in a good manner in TypeScript. So we can take it as a TypeScript in Node.js. Next, NestJS is also a good scalable framework where we can start a server coding over there. And for that, Node.js, we can go with Nest or Node.js with the TypeScript. So, Nest is also a TypeScript already. TypeScript is one of the things. And added to that, we need to have a reliable database, like a reliable database, like PostgreSQL. We can use PostgreSQL, which is good for scalable applications compared to MongoDB. So with the PostgreSQL, we can add it to that. We can deploy this application to the EC2. This EC2 will run the server in a Linux system, which we can get from the AWS. After this, we need to maintain our API gateway in the same AWS services. And we can go with the Fargate, and we can go with the load balancer. So for multiple kinds of users, we can use the load balancer. Added to that, if more and millions of users are coming, we can go with containerization or orchestration steps, like Docker or Kubernetes. Whenever we are going with multiple instances, Docker and Kubernetes means, obviously, EKS in AWS. So whenever we are going with the multiple instances, and without the monolithic, we can each of them in their own space. We can use it with Kubernetes. And we can deploy in this manner with added to that load balancer and all. We can get a good redundant amount of scalability, and we can maintain in the Node.js environment. And this sounds fine. And yeah. Thank you.

Slow API response. How would you redesign the system for better scalability performance? So just give me a second to think about it. Your company, your company experiences a surge in traffic leading to slow responses. So slow responses are obviously the result of not maintaining the architecture properly and, on the code side, not managing connections and combining this with many third parties and not handling the data and synchronous responses properly. At this time, we can experience latency in API responses. To redesign, we can go with a good design pattern. Mostly, we are using the MVC pattern, so we separate the controllers and routes and services into packages for each module and schema. And after this, we need to speed up and improve API responses. We can improve this at the architecture level by using Lambdas in AWS, which can provide a quick and responsive solution. It's also serverless. Mostly, the database connection is a huge thing, so that's why most of our TB queries are giving us latency. We need to handle this situation by deploying our RDB instance in a way that is more responsive and quicker to connect to functions and all. This is how we can improve the performance of API responses.

What is your approach to testing and monitoring? It is for these technologies. So this CICD is a necessary continuous integration. That is relevant. Deployment is a necessary thing. So why is it so? Because if we handle the publication for a user for only 10 to 50 people, we can do without the CICD. But whenever we are going with multiple numbers of users, obviously, we need to have test cases. And we need to have CICD pipelines, which could be run on Jenkins and all. So, if multiple application sizes are bigger, then the team's size is also bigger. So one person's score can affect another person's code. So after they push, they only come to know. This affects person A's code, person B's code, and person C's code. Based on this, we need to maintain test cases in the TDD approach, whether in front end, we can use Jest and React testing libraries and Mocha for back end. To test different APIs and UI elements. So, whenever the CICD runs, we can run test cases to test each and every component level, component by component. This can give some basic idea. Okay. Based on our test cases, these things are not failing. So we are sure about it. So, what we are writing and what we have done, based on that consolidated finalization, we came to know that okay, this won't affect the network code in our server development server or whether it's staging or product new server. So after that, not to that, the same case for back end code also. These test cases are merged, whenever we are handling a scalable application, like a bigger application.

Any database technology to enhance the security and scalability, and how do you plan to integrate database technologies? So, integrating, enhancing security and scalability means. We can use different kinds of load balances for scalability. If we're maintaining a CACD, we can go for code build. Otherwise, if we're having the, we can go for ECS and EKS for scalability. For security, we need to go from the code level itself. We need to maintain security in such a way that if we are using AWS, we can use Cognito. It's the best tool to integrate and authenticate the user without sending the password to the DB. This is the case in the security level. And SCORs is also one of the security measures. We are not allowing cross-site origination, so that is also an added perk. And without losing our data, or if anyone hacks our DB, databases, that could be a problem. The main data we're using is confidential data, which is in an encrypted format, and that is well and good. So like this, we can look into different security and scalability in a Node.js application.