Akash Kaintura

Akash Kendra. I've been working as a software professional for five plus years. I've worked as a back-end developer, a full-stack developer, and also on the front-end side. I've worked with technologies such as React and Blurr. On the back-end side, I worked with Node.js with the updated framework, Nest.js, and also with Express.js. I worked with some other tools for key messaging queue settings using RabbitMQ. Also, with one of the projects I've worked on, Elasticsearch, for the project, and also worked with C# as well. And, also, I've worked mostly on the AWS cloud services, including CloudWatch, Lambda, DynamoDB, and also with MK 5 as well because it's a new one. So, I haven't played with it much, but I've done those creating step functions, so that can automatically deploy whatever is being pushed from our end. That will be at the time of our end. And, also, I can work with Git as a version control system. And with the CICD thing, I've worked with most like, mostly with GitLab, Bitbucket, and GitHub. And on the database side, I've worked with MongoDB, and on the SQL RDBMS thing, it's PostgreSQL. And, I will be using Mocha for testing. And, the testing tools, I've mostly worked on the TDD thing. So, I have to work on, like, test-driven development first. So, I created using Jest. And on the agenda technology, I've worked always with Scrum tools following the Kanban part. And, the tool which I mainly worked with is Jira, throughout my career. I've worked with Jira as well as mostly Jira 7. So, that is about me. Thank you.

In React, what method would you say is essential for properly mounting components that involve ongoing API requests? So it's. So, basically, that can be done, like, properly unmounting the component, which involves the ongoing API request is basically we can do one thing because once that is the thing is rendering, like, the component after it's mounted, will need to update all the things so it will render. So we do one thing. We can use that with the help of the abort controller, to cancel the fetch API request. And that can be done, using we can, like, create a new controller or in the existing controller, and then, whatever we're fetching, using the thing, so we can, with signal that, oh, okay. The controller got the signal that it needs to be stopped or it needs to be unmounted. So we can, like, the thing is that how it should be done is basically, like, whenever we create an instance of our controller to handle request cancellation. So, like, once that controller is ready, so it will pass the controller's signal to the fetch request, and that will, be linked to the fetch request. So, it can allow it to abort the calling, using the controller's abort method will work there. So, once after that is done, we can clean up with controller's abort and whatever the thing is here, we unmount it. So that's how we can, do the unmounting using, while we are involving in the API request.

Describe a scenario where an atomic operation in MongoDB is critical within a Node.js application, and how would you achieve it? The asset property has been basically an asset property. So I'm supposed to manage asset properties for the company with transactions made. Transactions made. Transaction made with the payment. So, okay. So, let me think. Situation: The scenario will be something in the payment-related thing. Suppose I'm an end-user, and I'm searching for my product online, and another user is doing the same thing. Multiple users are doing the same thing. So, like, whenever this suppose there is a 100 stock quantity. At a time, there are 50 people logged in searching for the same product. So, there comes the scenario of atomic operations being done. The item count at 1 once I've added to the cart should be decreased from the available quantity. And so it's the same thing. We can do this with the use of a multi-document transaction in MongoDB. Suppose I have created a session. I created a session that starts a transaction and then performs the operation. Like, whatever the product data find and update it with the same thing, and update the order status as well with the same transaction context. Once that is done, I can commit the transaction using the session. And after that, I can use that session to check the transaction result. This can be achieved using the map-reduce approach in MongoDB.

You are building a dashboard that needs to be displayed with a large dataset, 10,000 rows. How do you ensure smooth rendering and efficient performance in React? Yes, we have a 10,000 data set. Pagination is used to paginate the data. So, for a 10,000 data set, I can do this either with multiple inbuilt features or external libraries. One library is React Virtualization, which basically provides virtualized rendering. It makes it easy to implement windowed rendering. Once that's implemented, only a small subset of rows are rendered based on the visible window. When I scroll, it renders until the window, and then when I scroll again, it renders more. For smooth rendering and user experience, I can also use pagination to fetch data in chunks, such as 100, 400, or 300 at a time. When I scroll up, it fetches again and again, which prevents it from looking awkward for the user. This can also be achieved through lazy loading or infinite scrolling. I can use inbuilt features with memoization using React memo or use memo hooks in React to avoid rerendering when the page is reloaded. While doing the searching part or fetching the data, I can also use debounce for this purpose.

Increment count here, increment down here, increment plus. Increments at 1 plus. So the potential is in the rise. Potentially your work should pass this to this combo increment or each of any code. So set the state of set state compare. This dot set the stage. But it's not in a slice, and it's basically working as a sync. It's in a sync part. This dot is state. Okay. So I'm going to request the issues. Like, how I pass this make issue the command with the binding, there is one issue which I can see is a binding issue in the increment counterpart. State this dot state dot count plus 1. And it will automatically start with 1 then 2 then go on. But one increment part of the binding thing is there for sure because you've been incrementing. And then, okay. So we're using class components. So right now, it's not good to use class-based components. So two things I found that can be improved. So one, we can use function-based components. And other than that, we can bind the increment counter, like creating a constructor, and then we can bind the increment counter, and then use that this dot increment count dot bind dot this. So whenever we can use so we directly in the increment count function, we can use that values. So those things, function components and bind the increment count method properly. And other than that, not the pushing here. Yeah. We can go with these two, or we can use other hooks. There are multiple ways to do that. So we can use hooks also. But most firmly, we can use a functional component and bind the counter increment thing with this method. So yes.

Your React app's performance has degraded significantly as data volume grew. What steps would you take using React DevTools and MongoDB profiling to identify and solve the issue? To identify and solve the issue, I would take the following steps using React DevTools and MongoDB profiling. First, I would use MongoDB profiling. MongoDB profiling allows us to profile production grouping, aggregation, and projection aggregation. Additionally, I would use the MongoDB profiling production feature to enable profiling at a specific level. When profiling at the slow level, MongoDB can log queries taking longer than 100 milliseconds. I can also use the `db.system.profile.find()` method to find slow queries and sort them in increasing or decreasing order based on the time taken. To overcome performance issues, I would use indexing in the database. Indexing can significantly improve query performance by allowing the database to quickly locate the data it needs. For the React app's performance using React DevTools, I would use the React library, the virtualized library, or the React window library. I would also use lazy loading and pagination to improve performance when dealing with large data sets.

I have a function that is intended to return a new array. Yes, I have a function. I reckon the password of the app is my first. Okay, this comes through the function, which is intended to turn you where with this limit is what can you find any logic? They call it a logical error in this. Logic error. I've zero, I'm less than error. error. I plus increment to a logical error loop, I'm less than error rate. basically, got it. Which are added in here, added plus. So we have the added length as of now. So the valid index, like, is at zero index. So the valid index should be, like, added or length minus 1, which can be done here. And okay, so we can remove the equal to, like, I less than array dot length because we do not have the length of that as of now. Because as it should be, if we are using equal to, we can use the array dot length minus 1. But as of now, we are not, so we can remove the equal to, like, I less than array dot length only. And, okay, so we are instead using block scope. So block scope part, we can use let, which can be later used anywhere in the function. So instead of that, we can use let, like, scope related issues, so we can do that also. So these two things, which need to be fixed. Other than that, it's good to go.

We can do with the bulk right using grouping, like, grouping groups or, aggregation methods, basically. So first, we have to match whether the status, about the status, matches the proper attribute or grouping or sorting or limiting the fetching values getting. Or we can do with the bulk operations, or the bulk operations. We can do that using, like, suppose I need to update only one or delete one or insert one. So we can do that with the bulk writing part, whatever the ID given. And for the bulk, we also have to set a set, like, dollar dot set. So that can work for an efficient transaction. The third one is basically using atomicity. So, like, a session starts and once that starts. Whatever the collection is there, commit the transaction when the transaction is committed. If not, then abort the transaction. And once that's done, the transaction is also done. And efficiently executing also comes under indexation. So, like, if we are using index optimization for faster query execution, that can be also done.

We identify and prevent potential security threats in web applications built with Node.js and React by relying on loggers and queries. We use modeling to detect security threats and implement CSRF, or cross-site request forgery, protection. Additionally, we deal with trouble caused by dependencies, such as SQL injection, cross-site scripting, and dependency vulnerabilities. We follow best practices for cross-site scripting and CSRF, and also focus on SQL injection prevention. We ensure input validation and sanitization in HTML documents, especially when using React, which renders components and forms. We avoid using user input in our HTML part to prevent cross-site scripting vulnerabilities. For sensitive information in dotenv files, we either ignore the file using.gitignore or process it using dotenv packages, which store sensitive data securely. We also have authentication and authorization already in place, which helps identify and prevent potential security threats.

You are tasked with creating a feature that allows user to upload and process large data files on a taxi fleet management system. Describe your approach to handle the file processing in a scalable way utilizing Node. Js and React. Let's get over. Like, we can do with the describe a pro handle file processing. So file processing, if you are using AWS or other cloud services, so we definitely be using the asynchronous uploads for thinking. And, like, we are we should be handling the error handling. The error handling should be there so we can use a TRICAD block and proper implementation of, like, what is the error there in each, part. And, suppose, there is this is big file above max 20 MB. I have certain restrictions, of only 20 MB. So that can be done with the, like, chunked upload part. So, upload the file into chunks so that can be done. And, like, scalability is related while uploading the file can be fixed through the Node JS, like, on the back end part. So we can use the SDR Google Cloud storage for that. And for the temporary storage, we can use the temporary folder there. So we need to create a endpoint for that on the back end also so that can be done.

I have not done this one, so I believe I am not supposed to answer this one because I have not incorporated.