Krati Chaturvedi

Hi. My name is. I have been working in the IT industry for the last 9 years. Currently, my position is a senior software engineer, and I work on the tech stack of Python, Django, MySQL, SQL, and MS SQL. And I designed web app backends for web applications or SaaS products.

Okay. So, monolithic Flask application into a microservice considering both pass API, make mega migration and so, translating a Flask application into a FastAPI application is not that difficult. But then, creating a monolithic application into a microservice application, in that, we need to identify the key modules that we need to separate out and which can stand alone, that is, they can exist on their own, should be made as microservices. For example, in an ecommerce application, certain modules like products, payment, order, and order management, payment service, these can be made as microservices. Dockerization. Dockerization. I will suggest Dockerizing the entire application, Dockerizing individual microservices as a standalone service.

Contemplating a legal legacy Flask application, migrating it to Xamarin and AWS ECS. So, basically, ECS cluster is the elastic container service. ECS will provide us a mechanism for fault tolerance. For example, if a service goes down, it can easily spin up a new container and provide fault tolerance. These are the things that can be achieved by using an AWS ECS cluster.

I think by using Kinesis, real-time data processing with minimal latency. Techniques for using past APIs and folder SQL click together to handle real-time data processing with minimal latency. I'm not able to understand the question completely. If I had been given a scenario, I would have explained it better.

Those optimizing SQL queries against the post list. They always use a NumPy array when retrieving data. So, basically, using a NumPy array by number means that we have a large amount of data. So, in fetching a large amount of data from a PostgreSQL database can be a bit tricky, but then optimizing the database using indexes can help in retrieving the queries faster. And, also, caching the data may help in making the queries faster. For example, there are joins, caching the data may help.

I would choose FastAPI for a complex project where I need high performance, scalability, and a robust set of features. FastAPI is last, in my opinion, because it is even lighter than Flask. And FastAPI also has certain mechanisms made for connection to the database.

Give you the following Python function return. Okay. So give you the following Python GPU function code that will imports icon g 2. Connection equals icon g 2 connect user ID. We use the password host. Personally, push to pound out person. Some more database applications, pound out commit. I think connection to DB should be hidden. And in connection to DB, the database operation should not be included. The code should be divided so that one module is responsible for connecting to the database, other responsible for executing the query, and third one, they're responsible for, closing the connection.

Examining the code block, testing of glass combination, identify what has been tested and if any improvements have been seen, Last name, eLab. I just make sure. Okay. So, any API with the endpoint as slash is being tested here. And as soon as the data is received, the message should be the date received data should be equal to "hello, world", which is what is being tested here.

So my understanding of a Docker container is basically containerizing the OS, making a runtime environment for the application, and replicating the same environment within the Docker container so that whenever the Docker container is up, the all the relevant libraries and everything is up, and using management AWS ECS. ECS can also help in fault tolerance, and issues can also help in fault tolerance. That's it.

I'm not sure either.

Describe a method for implementing rolling updates with Jenkins and Docker to a flash based application, minimizing service interface interruptions.