AWS Lambda, the popular serverless computing service, has transformed the way developers build applications in the cloud. Learning AWS Lambda opens up opportunities to build serverless applications, optimize costs, achieve scalability, and integrate with other AWS services, making it an essential skill for professionals across different technical domains.
According to statistics, over 100,000 customers use AWS Lambda. This range of businesses includes startups and large enterprises.
In these AWS Lambda Interview Questions, we will explore the important aspects of AWS Lambda in a simple manner. We will cover topics such as understanding its event-driven architecture, triggers, scaling, monitoring, and security to provide you with the essential knowledge.
Whether you’re a beginner or an experienced professional, these AWS Lambda interview questions will help you showcase how AWS Lambda actively contributes to building scalable and efficient serverless applications. Get ready to succeed in your AWS Lambda interviews with confidence and show your expertise in this modern technology.
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AWS Lambda Interview Questions For Freshers
What is AWS Lambda?
AWS Lambda is a serverless computing service provided by AWS (AWS Full Form: Amazon Web Services). It helps developers deploy and run their code without the need to provision or manage servers. With AWS Lambda, you can primarily focus on writing the code for your application or service, while AWS takes care of all the underlying infrastructure and scaling requirements.
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How does AWS Lambda differ from traditional server-based architecture?
AWS Lambda differs significantly from traditional server-based architecture. In traditional server-based setups, developers are responsible for provisioning and managing servers to handle application workloads. This requires constant server monitoring, scaling, and maintenance efforts.
In contrast, AWS Lambda removes the requirement for server management. Developers can primarily focus on writing code and defining event triggers. Lambda functions automatically scale based on the incoming request volume, without any manual intervention.
“Pay as you go” is also how the AWS Lambda service works. That means you only pay for the time your code is running.
This can result in significant cost savings compared to traditional server-based computing. Overall, AWS Lambda offers developers a serverless, event-driven, scalable, and cost-effective solution to designing apps that frees them from infrastructure worries.
What programming languages are supported by AWS Lambda?
AWS Lambda supports a range of programming languages, providing developers with flexibility in their choice of language for function development.
Some Programming languages includes:
How long is the maximum execution time allowed for an AWS Lambda function?
The maximum execution time for most languages on AWS Lambda is 900 seconds (15 minutes). This means that a Lambda function will automatically time out and stop executing if it reaches this limit.
What are the triggers that can invoke an AWS Lambda function?
- API Gateway
- CloudWatch Events
- S3 Bucket
- DynamoDB Streams
- SNS (Simple Notification Service)
What is the maximum memory allocation for an AWS Lambda function?
The most memory that can be given to an AWS Lambda code relies on the running setting that is picked. The current memory allocation limits are as follows:
For Node.js, Python, Ruby, Java, and .NET Core runtimes: The maximum memory allocation is 3,008 MB (3 GB).
For Go runtime: The maximum memory allocation is 10,240 MB (10 GB).
For PowerShell Core runtime: The maximum memory allocation is 1,536 MB (1.5 GB).
What are the different deployment methods available for AWS Lambda?
- AWS Lambda offers multiple deployment methods for deploying functions.
- AWS Management Console
- AWS CLI
These methods cater to different preferences and automation needs, allowing developers to choose the most suitable approach for deploying their AWS Lambda functions.
What are the various ways to access EC2?
There are several ways to access Amazon EC2 instances:
- SSH (Secure Shell)
- Remote Desktop Protocol (RDP)
- AWS Systems Manager Session Manager
- Elastic IP Address
- Load Balancers
- Bastion Host
These are some of the common methods for accessing EC2 instances. The choice of access method depends on the operating system, security requirements, and specific use case of the EC2 instances.
Describe the scenario when you can practically trigger an AWS Lambda Function?
One practical scenario for triggering an AWS Lambda function occurs when you have an application that requires real-time processing of incoming data or events.
Think about a social media site where people can post information. You can set up a trigger that runs a Lambda function whenever a person makes a new post. This function can then perform tasks such as processing the post, analyzing its content, updating relevant databases, sending notifications, or triggering additional actions.
By using Lambda as a serverless compute service, you can seamlessly handle incoming events or data without the need to provision and manage servers, ensuring efficient and scalable processing in response to user activities.
Is there a way to test lambda functions that doesn’t involve writing scripts?
To test AWS Lambda functions without scripting, you can utilize the AWS Lambda Console.
Step 1:- Open the AWS Management Console and navigate to the Lambda service.
Step 2:- Select the Lambda function you want to test.
Step 3:- Click “Test” in the “Designer” part.
Step 4:- In the “Configure test event” dropdown, select a pre-configured sample event or create a custom test event.
Step 5:- Provide the required input data for the event, mimicking the real-world data that the function expects.
Step 6:- Click on the “Test” button to trigger the function with the test event.
Step 7:- Observe the function’s execution results, including the output, logs, and any error messages.
By following these steps, you can test your Lambda function by manually invoking it with test data.
AWS Lambda Interview Questions For Experienced
How can you handle errors in AWS Lambda?
To handle errors in AWS Lambda functions:
- Implement error handling in your code using try-catch blocks or error handling functions.
- Return appropriate error responses to the invoking source, such as HTTP status codes and error messages.
- Utilize logging frameworks like AWS CloudWatch Logs to capture error information for troubleshooting.
- Configure Dead Letter Queues (DLQs) to route failed events for further analysis or processing.
- Leverage the automatic retry mechanism provided by AWS Lambda for certain types of errors to improve function resilience.
Can you explain the event-driven architecture and how AWS Lambda fits into it?
Event-driven architecture is a design approach that focuses on responding to events rather than direct requests. AWS Lambda seamlessly integrates with this architecture by allowing code execution in response to events from different sources. It enables the creation of scalable and flexible systems where Lambda functions perform tasks triggered by events, resulting in cost-effective and easily scalable serverless applications.
How does AWS Lambda handle scaling and concurrency?
AWS Lambda handles scaling and concurrency automatically. It scales your functions based on incoming requests and event-driven triggers, dynamically adjusting the number of instances as needed. Lambda functions are stateless, allowing for parallel execution and efficient scaling. AWS Lambda takes care of the scaling and concurrency management, allowing you to focus on writing code without worrying about infrastructure limitations.
Describe how you would optimize the performance and cost efficiency of an AWS Lambda function?
AWS Lambda is a serverless computing platform that allows you to run code without provisioning or managing servers. By following best practices such as choosing the right memory size, avoiding recursive code, and using event-driven triggers, we can optimize the performance and cost efficiency of AWS Lambda functions.
How can you secure sensitive information in AWS Lambda, such as API keys or database credentials?
To secure sensitive information in AWS Lambda:
- Avoid hardcoding sensitive data in the code.
- Use environment variables for storing sensitive information.
- Encrypt sensitive data using AWS KMS.
- Apply least privilege by assigning appropriate IAM roles and permissions.
- Restrict access to resources using security groups and VPC settings.
- Implement network controls like API Gateway for secure access.
- Rotate and update credentials regularly.
- Monitor and log activities using CloudTrail and CloudWatch Logs.
- Follow secure coding practices and conduct security audits.
- Regularly review and assess security to address vulnerabilities.
What are the integration options available for AWS Lambda with other AWS services?
AWS Lambda offers seamless integration with various AWS services, including –
- API Gateway
- CloudWatch Events
These integrations allow you to build serverless architectures, process real-time data, trigger functions based on events, handle messaging workflows, and more. AWS Lambda is a powerful tool for making scalable, event-driven apps within the AWS environment.
How can you implement long-running tasks or workflows in AWS Lambda?
AWS Lambda is not designed for long-running tasks. It is best suited for short and predictable workloads that typically last up to 15 minutes. If you require longer execution times, it is recommended to use AWS Batch jobs, which are specifically designed for running extended and batch processing tasks.
What third-party frameworks or tools have you used to enhance your AWS Lambda development experience?
Yes, I have used a number of third-party frameworks and tools to enhance my AWS Lambda development experience. Some of the most popular frameworks and tools include the Serverless Framework, AWS SAM, and the AWS CDK. These frameworks and tools can help to improve the development process, reduce the risk of errors, and improve the overall performance of your AWS Lambda functions.
What occurs when the maximum number of executions for an AWS Lambda account is reached?
When an AWS Lambda account has hit its maximum number of runs, any new calls to Lambda functions will be rejected. This means that the Lambda service will stop accepting new requests for function executions until the account’s execution limit is increased or additional capacity is provisioned. The specific behavior may vary depending on the AWS region and service limits in place.
What permissions are required to access AWS services from a Lambda function? How do you configure these permissions?
To access AWS services from a Lambda function, you need to configure an IAM role with appropriate permissions. This role grants the necessary access to specific services and actions. You can create or update the IAM role in the AWS Management Console, attach policies that define the required permissions, and assign the role to your Lambda function.
The following AWS Lambda managed policies provide varying permissions:
- AWSLambdaBasicExecutionRole: Provides the basic permissions required for a Lambda function to write logs to CloudWatch Logs and access AWS X-Ray for tracing.
- AWSLambdaRole: Allows Lambda functions to call AWS services on your behalf and write logs to CloudWatch Logs.
- AWSLambdaVPCAccessExecutionRole: Grants Lambda functions permission to access resources in a Virtual Private Cloud (VPC).
- AWSLambdaENIManagementAccess: Allows Lambda functions to manage Elastic Network Interfaces (ENIs) for VPC access.
- AWSLambdaKinesisExecutionRole: Provides permissions for Lambda functions to process records from Kinesis streams.
- AWSLambdaDynamoDBExecutionRole: Grants permissions for Lambda functions to read and write to DynamoDB tables.
- AWSLambdaSQSQueueExecutionRole: Allows Lambda functions to process messages from Amazon Simple Queue Service (SQS) queues.
- AWSLambdaSNSPublishingRole: Provides permissions for Lambda functions to publish messages to Amazon SNS topics.