Todayâs modern world is witnessing a significant change in how businesses and organizations work. Everything is getting digitized, and the introduction of cloud and cloud computing platforms have been a major driving force behind this growth. Today, most businesses are using or are planning to use cloud computing for many of their operations, which consequently has led to a massive surge in the need for cloud professionals.Â
If you are interested in a career in the cloud industry, your chance has arrived. With cloud computing platforms like AWS taking the present business scenarios by storm, getting trained and certified in that particular platform can provide you with great career prospects.Â
But in order to get your AWS career started, you need to set up some AWS interviews and ace them. In the spirit of doing that, here are some AWS interview questions and answers that will help you with the interview process. There are a number of different AWS-related questions covered in this article, ranging from basic to advanced, and scenario-based questions as well.
AWS MLOps Interview Questions and Answers
How can you use Amazon SageMaker to assess machine learning models and analyze data?
You can analyze data and assess machine learning models using Amazon SageMaker Processing. You can run data processing tasks on SageMaker in a simple, managed environment with SageMaker Processing, including feature engineering, data validation, model evaluation, and model interpretation. Additionally, you can use the Amazon SageMaker Processing APIs to track performance before and after the code is implemented.
Is AWS SageMaker a serverless platform?
SageMaker is built on top of AWS Lambda, which is a serverless compute service that allows users to run code without the need to manage infrastructure. This means that AWS SageMaker can be considered a serverless platform, as it leverages the serverless capabilities of AWS Lambda to provide a fully-managed machine learning platform.
How does SageMaker support task scheduling?
SageMaker allows us to schedule tasks by using Cloud Watch events:
AWS SageMaker allows users to schedule tasks using Amazon CloudWatch Events. CloudWatch Events is a service that will enable you to respond to events in your AWS account programmatically. You can use CloudWatch Events to schedule tasks in SageMaker by creating rules that trigger a specific action in response to a specified event.
For example, you can use CloudWatch Events to schedule a training job in SageMaker to run at a specific time every day. You can also use CloudWatch Events to trigger the deployment of a trained model when a new data set becomes available or to run a batch transform job when a new file is added to an S3 bucket.
To set up task scheduling in SageMaker using CloudWatch Events, you will need to create a CloudWatch Events rule and specify the desired SageMaker action as the rules target. You can then use the CloudWatch Events console or API to manage your rules and schedule tasks in SageMaker.
How does AWS SageMaker perform inference?
AWS SageMaker uses inference to create predictions based on fresh data using a trained machine-learning model. To do this, new data points must be fed into the model, which will then utilize them to make predictions.
How can you develop a machine learning pipeline for classification using SageMaker?
The SageMaker Classification Algorithm allows you to develop an classification machine learning pipeline in SageMaker. This algorithm can be used to label s with labels that you supply automatically.
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3 What Are Some of the Security Best Practices for Amazon EC2?
Security best practices for Amazon EC2 include using Identity and Access Management (IAM) to control access to AWS resources; restricting access by only allowing trusted hosts or networks to access ports on an instance; only opening up those permissions you require, and disabling password-based logins for instances launched from your AMI.
10 A company needs to monitor the read and write IOPS for their AWS MySQL RDS instance and send real-time alerts to their operations team. Which AWS services can accomplish this?
Explanation: Amazon CloudWatch is a cloud monitoring tool and hence this is the right service for the mentioned use case. The other options listed here are used for other purposes for example route 53 is used for DNS services, therefore CloudWatch will be the apt choice.