AWS Lambda Interview Questions and Answers

Latest AWS Lambda Interview Questions and Answers [2023]

If you’re looking for  Frequently asked AWS Lambda Interview Questions for Experienced or Freshers, you are in the right place. There are a lot of opportunities from many reputed companies in the world. According to research AWS Lambda has a market share of about 44%. So, You still have the opportunity to move ahead in your career in AWS Lambda Development. Get prepared for your AWS Lambda interview with these top questions and answers. 

AWS Lambda Interview Questions

Q1. What is “AWS Lambda”?

Q2. What is meant by Auto-scaling in AWS Lambda?

Q3. Which languages are supported by AWS Lambda?

Q4. How long can an AWS Lambda function execute?

Q5. How does AWS Lambda secure my code?

Q6. What do you understand by the Serverless application in AWS lambda?

Q7. How do you start using a serverless application?

Q8. What benefits come from adopting a serverless approach?

Q9. What are the methods for reusing code across AWS Lambda functions?

Q10. If you use Lambda Layers, can you expand the size of a deployment package?

Q11. What happens to your lambda functions if a lambda layer is deleted?

Q12. What benefits does AWS Lambda have over competing technologies like Microsoft Azure and Google Cloud Functions?

Q13. List a few suitable use cases for AWS Lambda.

Q14. List the top three security practices for AWS Lambda.

Q15. What services have you integrated with AWS Lambda?

Q16. Explain the concept of cold and warm starts in AWS Lambda

Q17. What’s the difference between synchronous and asynchronous invocation in AWS Lambda?

Q18. Explain your workflows for development and deployment of AWS Lambda functions.

Q19. Can one lambda function call another lambda function?

Q20. Can you execute queries on an RDS instance (in a private subnet) using Lambda?

Q21. What is meant by the term “auto-scaling” in lambda?

Q22. What is “AMI” in AWS Lambda?

Q23. What are the limits of the availability of lambda functions on Amazon Web Services?

Q24. What exactly automates deployment is?

Q25. What are the features in AWS lambda that automate the deployment?

Q26. Tell us about the frameworks which are available for serverless?

Q27. Is it possible to debug and troubleshoot the micro or small services?

Q28. What makes Lambda a time-saving approach?

Q29. What is the time limit for execution in Lambda when you perform DDOS?

Q30. What do you know about Zero downtime deployment?

Q31. Among On-demand and Reserved Instances, which one is better to impose a limit on expenditure when it comes to optimizing the speed on Lambda?

Q32. What is EC2 service?

Q33. What is elastic blockage storage in Lambda?

Q34. Give a simple method to improve performance in AWS Lambda?

Q35. Is vertical scaling possible in Lambda?

Q36. What is SQS in Lambda? What role does it play?

Q37. What do you know about Lambda Expression?

Q38. What are the Final Variables and Effectively final variables in Lambda?

Q39. Is Lambda Expression a nameless suspension of Code?

Q40.  How do you start AWS Lambda?

Q41. AWS Lambda provides many benefits. What are the cons of using AWS Lambda?

Q42. How do you manage concurrency and scaling in AWS Lambda?

Q43. How do you pass environment variables to AWS Lambda?

Q44. How do you re-use code across AWS Lambda functions?

Q45. What happens to your lambda functions if you delete a Lambda Layer?

Q46. How do you share large files between lambda functions?

Q47. What are Lambda limits per region?

Q48. What is AWS Lambda@Edge?

Q49. Explain Lambda with RDS Proxy.

Q50. Lambda@edge limits

Q51. Explain CloudFront events that can be used to trigger Lambda@Edge.

Q52. Lambda@Edge benefits

Q53. Lambda@Edge pricing

Q54. What is the difference between AWS Lambda and Lambda@edge?

Q55. How does AWS Lambda work?

Q56. AWS Lambda Concepts

Q57. Use Cases of AWS Lambda

Q58. Best practices of Lambda function

Q59. When not to use AWS Lambda

Q60. Advantages of using AWS Lambda

Q61. Explain Limitations of AWS Lambda

Q62.Explain AWS Lambda Pricing

Q63. What is the main difference between an anonymous class and a lambda function?

Q64. When should I use AWS Lambda functions with more than 3008 MB of memory?

Q65. How long can an AWS Lambda function execute?

Q66. How do I make an AWS Lambda function respond to changes in an Amazon S3 bucket?

Q67. Do You Think Lambda Saves Time When It Comes To Coding? 

Q68. Can You Create Different Versions Of Functions In AWS? 

Q69. How Would You Make Different Lambda Functions Work Together In A Complex Workflow? 

Q70. How Does AWS Lambda Contribute To Faster Development ?

 

Q1. What is “AWS Lambda”?

Lambda, a software service platform offered by Amazon Web Services, is an example of this type of platform. Lambda enables serverless computing in specific scenarios. Events generated by AWS can be used to initiate the execution of code in any application.

You have access to a wide range of AWS services, including the Amazon Simple Storage Service (S3) for storing files, the Amazon DynamoDB for updating tables, the Amazon API Gateway for gaining access, and many more. AWS Lambda frees developers from the burden of configuring and managing software servers, allowing them to focus on writing and running their programmes.

  • Virtual function. Function as a Service (FaaS), serverless.
  • Runs on demand and scaling is automated. 

 

Q2. What is meant by Auto-scaling in AWS Lambda?

It is an application in AWS that is responsible for target tracking scaling policy that adjusts provisioned concurrency levels automatically. 

 

Q3. Which languages are supported by AWS Lambda?

The languages AWS Lambda supports are Java, Go, PowerShell, Node. js, C#, Python, and Ruby.

 

Q4. How long can an AWS Lambda function execute?

The complete execution will take about 300 seconds from placing user calls to AWS Lambda. Three seconds will be taken as the default time out, and then you can set any timeout value between 1 – 300 seconds.

 

Q5. How does AWS Lambda secure my code?

User codes in AWS Lambda can be stored in the Amazon S3, and then the code can be encrypted with the help of suitable methods. AWS Lambda is used to carry out extra data integrity checks when the code runs. 

 

Q6. What do you understand by the Serverless application in AWS lambda?

Lambda-based serverless applications consist of functions that are called in response to different events. The basic serverless application has one or more functions activated by functional events such as object uploads to Amazon S3, Amazon SNS, and API activities. These functions can operate independently and employ other resources like Amazon Dynamo DB tables or Amazon S3 buckets. Functions are the most common serverless application.

 

Q7. How do you start using a serverless application?

You must download a blueprint after accessing the AWS Lambda console to get started. An AWS SAM file, which is used to define AWS resources in the application, and a .ZIP file, which contains the function’s code, are included in the downloaded file. The serverless application you download can then be packaged and deployed using the AWS CloudFormation commands. 

 

Q8. What benefits come from adopting a serverless approach?

The serverless approach offers numerous advantages-

  • The approach is fairly easy, leading to a shorter market time and more sales.
  • Customers only need to pay when the code is active, which allows for significant cost savings and increased revenues.
  • Clients can run this application without any additional infrastructure.

 

Q9. What are the methods for reusing code across AWS Lambda functions?

There are two methods for reusing code among multiple AWS Lambda functions:

Lambda Layers: You can reuse your code or logic across various Lambda functions by storing it in lambda layers.

monorepo: Use the mono repository and create packages dynamically while deploying.

 

Q10. If you use Lambda Layers, can you expand the size of a deployment package?

If you use Lambda Layers, you cannot expand the deployment package size. The size of the lambda function and its related layers are included in the 50 MB zipped maximum deployment size.

 

Q11. What happens to your lambda functions if a lambda layer is deleted?

Existing lambda functions that make use of the deleted layer will continue to function since lambda layers and lambda functions are combined at deployment time. The deleted lambda layer, however, cannot be used to build a new lambda function.

 

Q12. What benefits does AWS Lambda have over competing technologies like Microsoft Azure and Google Cloud Functions?

You can easily integrate AWS Lambda with other AWS services. Lambda functions can be used for various tasks, including back-end operations, data processing, real-time stream processing, etc. These are just some of the major benefits that AWS Lambda has over the products of other cloud providers.

 

Q13. List a few suitable use cases for AWS Lambda.

Common applications of AWS Lambda include processing large amounts of data, developing event-driven apps, and operating web and mobile backends. These applications help you come up with practical use cases. Here are three examples of potential uses:

  1. Operating serverless websites: Due to its pricing structure, S3 storage, and hosting, Lambda is becoming increasingly popular.
  2. Predictive page rendering: It sets up websites for display in accordance with the choices that users make in subsequent requests.
  3. Creating an innovative app: As you manage infrastructure and other deployment processes, this use case will help you save money, time, and effort.

 

Q14. List the top three security practices for AWS Lambda.

AWS mainly handles infrastructure security standards like Identity Access and Management (IAM) permissions & roles, VPC & networking settings, etc. Additionally, you must take care of other cloud configurations and applications. The three ideal security practices are as follows:

  1. The best security strategy for Lambda functions is to grant IAM the least privilege. One IAM role should be configured for each Lambda function only to allow access to necessary resources. IAM can be set up to provide resource-based controls that validate a service’s authorization before invoking a function.
  2. Do not include AWS configuration in the function or Lambda execution configuration. It’s a good practice to keep it in the Lambda environment variables or the EC2 System Manager Parameter Store.
  3. Use API Gateway to give the functions an additional layer of protection. To enable security, it uses request throttling, authentication, and encryption. It modifies the authorization settings and API configuration.

 

Q15. What services have you integrated with AWS Lambda?

Only tell about the services that you’ve really used.

You may have used S3, SNS, SQS, Kinesis, DynamoDB, SES, or others. Not all projects will be completely serverless.

If you’ve used any non-serverless component along with AWS Lambda, mention those too. For example, you might’ve used AWS Lambda with RDS. If you’ve used such a configuration,  you can explain about that along with your reasoning.

 

Q16. Explain the concept of cold and warm starts in AWS Lambda

Lambda services receive a request to run a lambda function. The service prepares the execution environment by downloading the handler function code and by allocating memory along with other configuration.

Even though you’re not billed for this execution environment preparation time, you’ll have to face the delay in invoking your lambda function. This delay is called a “cold start“.

The cold start timing is less significant for TypeScript and Python runtime environments, whereas it’s a bit higher for Java or C# runtime environments.

To improve performance, the lambda service will keep the execution environment for some time. When you receive the request for the same lambda function again during this period, your handler can start executing immediately. This type of invocation is called a “warm start“.

 

Q17. What’s the difference between synchronous and asynchronous invocation in AWS Lambda?

In synchronous invocation, the caller will wait for the execution to complete. But in asynchronous invocation, the caller will put the event in an internal queue which will later be processed in the lambda function.

For example, if you’re building serverless APIs using API Gateway, it’ll be a synchronous invocation. But if you’re using S3, it’ll be an asynchronous invocation.

 

Q18. Explain your workflows for development and deployment of AWS Lambda functions.

You can explain which framework(s) you’ve used to develop and deploy lambda functions. You can also talk about any IaC (Infrastructure as Code) tool that you’ve used.

Below is non-exhaustive list of the most commonly used frameworks:

  • Serverless
  • AWS CDK
  • AWS SAM
  • CloudFormation
  • Pulumi
  • If you’ve used Terraform, you can talk about that as well.

 

Q19. Can one lambda function call another lambda function?

You can do this, but it is not recommended. If you want to design a workflow which involves multiple lambda functions, you can use step functions.

A standard approach is to emit an event and trigger a lambda based on the event. You can use SQS, SNS, or EventBridge as intermediary for these events.

 

Q20. Can you execute queries on an RDS instance (in a private subnet) using Lambda?

Yes, you can execute the query in RDS using AWS Lambda. For that you can have your lambda inside the same VPC.

There may be some performance implications if you use AWS Lambda directly with RDS because of the database connection creation time. To avoid those, you can use an RDS Proxy.

 

Q21. What is meant by the term “auto-scaling” in lambda?

Simply said, auto-scaling in AWS lambda is a function of the Amazon web service that enables users to start new instances of a service and carry out any necessary configuration chores without having to manually interfere.

This function enables users to save time and effort. You are free to relax and see how the installation is carried out while keeping a close check on the threshold and key performance indicators as they appear in real-time.

 

Q22. What is “AMI” in AWS Lambda?

Amazon Machine Image is referred to by its acronym, AMI, and is utilized rather commonly in Lambda-based processing. In its most basic form, it is a starting point that has commonly used software such as an operating system, an application server, and potentially some extra programs already installed on it.

 

Q23. What are the limits of the availability of lambda functions on Amazon Web Services?

The lambda application hosted on Amazon Web Services makes use of redundancy and replication to ensure that your lambda and Amazon services continue to run without interruption. In addition, the management of Amazon Lambda’s downtime and maintenance windows is incorporated into this offering.

 

Q24. What exactly automates deployment is?

Automate Deployment cuts down human interference and help the organizations ensure outcomes that are quality-based and are best in every aspect.

 

Q25. What are the features in AWS lambda that automate the deployment?

There are environmental variables that are supported by AWS lambda. They can be used for data and several other credentials when it comes to modifying the deployment package. As it’s a serverless approach, it also supports aliases. There are certain types in fact that you can easily consider such as stage production and dev. Thus, functions can easily be considered for testing and without actually interrupting the production code. The end-point doesn’t change easily and thus one can keep up the pace with the task.

 

Q26. Tell us about the frameworks which are available for serverless?

There are several frameworks and serverless is extremely powerful. Its great support to Lambda and open whisk, as well as azure functions, makes it simply the best in every aspect. When it comes to extending the cloud formation, the Serverless Application Model can easily be considered. Scripting the changes to API becomes extremely simple with this approach and the best thing is the task is very quick and reliable.

 

Q27. Is it possible to debug and troubleshoot the micro or small services?

Yes, it’s possible. It can be performed even when the function is running and appropriate tasks are being performed.

 

Q28. What makes Lambda a time-saving approach?

There are certain reasons for this. The one is it’s possible to simply store everything in the local server memory. Also, data can be stored directly into the database without affecting the performance. In addition to this, testing is not much complicated. Integration testing can simply be made powerful through multiple vendors.

 

Q29. What is the time limit for execution in Lambda when you perform DDOS?

The time limit is 5 minutes.

 

Q30. What do you know about Zero downtime deployment?

Deployments are generally considered in the form of functions. AWS Lambda divides it into units in case they are complex. The fact here is app remains in offline mode during such a time period. However, the results are always good. 

 

Q31. Among On-demand and Reserved Instances, which one is better to impose a limit on expenditure when it comes to optimizing the speed on Lambda?

Reserved Instances are a better option. 

 

Q32. What is EC2 service?

In Lambda, there is always a need to have scalable computing capacity while dealing with data in the cloud. EC2 is meant for the same purpose as a web service. Networking, as well as security,  can easily be managed. Using minimal friction, configuring capacity can also be creased with EC2.

 

Q33. What is elastic blockage storage in Lambda?

It is basically a virtual storage area network where tasks can be started. It can tolerate faults easily and users need not worry about the loss of data even in case the disk damages in the RAID. Provisioning and allocating the storage can also be done in Elastic Block Storage. If required, it can also be connected to the API

 

Q34. Give a simple method to improve performance in AWS Lambda?

This can be done simply by using the Linux software RAID. Also, better security can simply be assured. 

 

Q35. Is vertical scaling possible in Lambda?

Yes, it’s possible and in fact, it is one of the best features in the AWS Lambda. Basically, it is considered when you need to spin a larger instance. In case you are already using the one, it can be paused. You need to detach the same as well from the server. It’s necessary to note the Id of the new device post which you can continue your process

 

Q36. What is SQS in Lambda? What role does it play?

SQS is basically nothing but an approach used for information sharing and passing among the different hosts and connectors. Different components of Lambda can be made accessible or in other words, communication can be made possible in them. Even if the functional components are different, they can simply be connected. A lot of failures can be eliminated simply through this approach and components can understand each other effectively.

 

Q37. What do you know about Lambda Expression?

When comes to writing shorthand code, they are generally considered. Basically, they are adopted as anonymous methods for this purpose. The productivity of developers can simply be enhanced and reliable code can simply be assured without making a lot of effort. They are basically nameless functions.

 

Q38. What are the Final Variables and Effectively final variables in Lambda?

Final Variables are those which cannot be modified once assigned. When they are in an earlier stage where it is possible to make any form of change, they are called effectively variable. The value is yet to be assigned to them. The outcome is required without restriction in many cases and that is the reason to use effective variables. They can also play a role in testing. If final variables are to be equipped with several additional features, this can be done through effective Variables. Most local expressions in Lambda are final.

 

Q39. Is Lambda Expression a nameless suspension of Code?

Yes, it is actually a nameless suspension of code.

 

Q40.  How do you start AWS Lambda?

Sign in to the AWS Management Console. Go to Services Menu and select the IAM console. In the Navigation pane, go to Roles and then Create roles. In the Select type of trusted entity, choose AWS service, and then choose Lambda for the service that will use this role.

 

Q41. AWS Lambda provides many benefits. What are the cons of using AWS Lambda?

Yeah, Lambda provides many benefits such as cost and scalability without any need to maintain the servers. But it’s not the answer to everything – like any service, it has its own problems

Debugging: If you’re using serverless architectures using Lambda, you might have to rely on logging to find the root cause of the issue. This is because your application will be distributed across many services/ lambda functions.

Testing: You can mock AWS services in your local testing. But it is better to have a separate environment in AWS to test your lambdas. This makes testing a bit complex.

Background jobs: Lambda has a timeout limit of 15 minutes. If you want any particular task to take more than 15 minutes, you might have to move to Fargate or some other solution.

Cost: If you’re running a high traffic application which processes the requests 24/7, using lambda can be expensive. It is better to use Fargate, EC2 or other services, if you have constant high traffic.

Q42. How do you manage concurrency and scaling in AWS Lambda?

Concurrency is the ability to execute multiple lambda functions at the same time. Scaling is the process of increasing the number of copies of your lambda function to handle the incoming requests. 

You can control concurrency by setting the value of reserved concurrency so that only the mentioned number of lambda functions will be invoked.

 

Q43. How do you pass environment variables to AWS Lambda?

There are different ways to pass environment variables to AWS Lambda, and it depends on the type of value is getting passed.

  1. Non-sensitive data: If you want to pass any non-sensitive information, you can pass the values directly to your lambda function environment variables. But these values would be visible in the AWS console in the Lambda service
  2. Sensitive data: If you want to pass sensitive data such as passwords and API keys, you can use either a Secret Manager or Parameter store. But, you need to make sure you provide necessary roles to Lambda for accessing and decrypting secrets from the respective services.

 

Q44. How do you re-use code across AWS Lambda functions?

There are 2 ways to re-use code across many AWS Lambda functions:

Use Lambda Layers: You can store your code or logic in lambda layers, which you can re-use across different lambda functions.

Use monorepo: You can use mono repo and dynamically build packages at deploy time.

 

Q45. What happens to your lambda functions if you delete a Lambda Layer?

In this question, the interviewer wants to see how well you understand lambda layers.

Existing lambda functions which use that deleted layer will continue to work – as lambda layers are merged with lambda functions at deployment time.

But you can’t create a new lambda function using that deleted lambda layer.

 

Q46. How do you share large files between lambda functions?

You can use the Elastic File System (EFS) to share large files between different functions.  

You can create an access point in the created EFS with the appropriate permissions and use that access point in your mount path in your lambda.

Any files written on that mount path will be accessible to all other lambda functions provided they have the mount path with appropriate permissions.

 

Q47. What are Lambda limits per region?

There are two types of limit in Lambda per region.

  1. Execution Limit 
  2. Deployment Limit

Execution Limits: 

  • Size of env variable – 4KB 
  • Memory allocation= 128 MB – 10 GB. 
  • Max execution time 9000 sec ie 15 min. 
  • Disk capacity (/tmp)= 512 MB – 10 GB
  • Concurrency execution 1000s

Deployment Limits:  

  • /tmp can be used
  • Environment variable size=4KB
  • Deployment size compressed = 50 MB
  • Deployment size uncompressed =250 MB

 

Q48. What is AWS Lambda@Edge?

AWS Lambda@Edge is an extension of AWS Lambda that grants greater flexibility and lower latency to distributed Lambda functions. You can run Lambda@Edge functions with Node.js and Python. 

The benefit of Lambda@Edge is that it uses the Amazon CloudFront content delivery network (CDN) to enable you to deliver function results globally. This is in contrast to Lambda, which requires you to provision instances in each location you want to operate from.

Can use lambda to change the cloud front request and response. 

1) Viewer Request: After cloud front receives a request from viewer. 

2) Origin Request: Before cloud front forwards a request to the origin. 

3) Origin response: After cloud front receives the response from the origin

4) View response: Before cloud front forwards the response to viewer. 

 

Q49. Explain Lambda with RDS Proxy.

Lambda function must be deployed in your VPC because RDS proxy is never publicly accessible. With RDS proxy, it improves scalability by pooling and sharing DB connection. Improve availability by reducing 66% failover time by storing connection. 

 

Q50. Lambda@edge limits

The following AWS Lambda features are not supported by Lambda@Edge:

  • Lambda functions with more than 512 MB of ephemeral storage.
  • The runtime must be Node.js 12.x, Node.js 14.x, Python 3.7, Python 3.8, Python 3.9.
  • Configuration of your Lambda function to access resources inside your VPC.
  • Lambda function dead letter queues.
  • Lambda environment variables.
  • Lambda functions with AWS Lambda layers.
  • Using AWS X-Ray.
  • Lambda reserved concurrency and provisioned concurrency.
  • Lambda functions that use the arm64 architecture.

 

Q51. Explain CloudFront events that can be used to trigger Lambda@Edge.

Your functions will automatically trigger in response to the following Amazon CloudFront events:

Viewer Request – This event occurs when an end-user or a device on the Internet makes an HTTP(S) request to CloudFront, and the request arrives at the edge location closest to that user.

Viewer Response – This event occurs when the CloudFront server at the edge is ready to respond to the end-user or the device that made the request.

Origin Request – This event occurs when the CloudFront edge server does not already have the requested object in its cache, and the viewer request is ready to be sent to your backend origin web server (e.g. Amazon EC2 or Amazon S3).

Origin Response – This event occurs when the CloudFront server at the edge receives a response from your backend origin web server.

 

Q52. Lambda@Edge benefits

  1. Managed computing: 

You can automatically scale and run your code in AWS locations around the world without deploying or managing origin servers in multiple locations, or setting up load balancing or DNS (Domain Name System) routing services.

You can add new functionality without making any changes to existing applications running on the origin server. Finally, by using Lambda@Edge and CloudFront, you have less origin infrastructure to manage than with a traditional CDN.

  1. Lower latency for webs and apps:

Lambda@Edge runs your code in AWS edge locations around the world, close to your users, so you can deliver full-featured custom content with high performance and low latency.

  1. Customize your content at the edge:

With Lambda@Edge, you can customize the content delivered through CloudFront CDN, and you can select the computing resources provided, thus customizing execution time, based on your application performance needs.

 

Q53. Lambda@Edge pricing

Lambda@Edge is charged based on the following two factors:

  1. The number of requests. The cost is $0.60 per 1 million requests ($0.0000006 per request). At the time of writing, the price is the same for every AWS region.
  2. Function duration. Currently, the cost is $0.00005001 for every GB-second used. For example, if you allocate 128MB of memory to be available per execution with your Lambda@Edge function, then your duration charge will be $0.00000625125 for every 128MB-second used. Note that Lambda@Edge functions are metered at a granularity of 50ms

 

Q54. What is the difference between AWS Lambda and Lambda@edge?

The difference is that AWS Lambda is a regional service, and if you use it for Internet-related apps, you usually use it with Amazon API Gateway. And if you need to use this kind of application globally, you can deploy it yourself to multiple regions around the world or you can leverage Amazon CloudFront CDN.

Using Lambda@Edge and Amazon CloudFront allows you to execute logic automatically across multiple AWS edge locations based on where your end viewers are located.

 

Q55. How does AWS Lambda work?

Step 1: First upload your AWS Lambda code in any language supported by AWS Lambda. Java, Python, Go, and C# are some of the languages that are supported by AWS Lambda function.

Step 2: These are some AWS services which allow you to trigger AWS Lambda.

Step 3: AWS Lambda helps you to upload code and the event details on which it should be triggered.

Step 4: Executes AWS Lambda Code when it is triggered by AWS services:

Step 5: AWS charges only when the AWS lambda code executes, and not otherwise.

This will happen in the following scenarios:

  • Upload files in an S3 bucket
  • When HTTP get/post endpoint URL is hit
  • For adding/modifying and deleting Dynamo DB tables
  • In the process of data streams collection
  • Push notification
  • Hosting of website
  • Email sending

 

Q56. AWS Lambda Concepts

Function: A function is a program or a script which runs in AWS Lambda. Lambda passes invocation events into your function, which processes an event and returns its response.

Runtimes: Runtime allows functions in various languages which runs on the same base execution environment. This helps you to configure your function in runtime. It also matches your selected programming language.

Event source: An event source is an AWS service, such as Amazon SNS, or a custom service. This triggers function helps you to executes its logic.

Lambda Layers: Lambda layers are an important distribution mechanism for libraries, custom runtimes, and other important function dependencies. This AWS component also helps you to manage your development function code separately from the unchanging code and resources that it uses.

Log streams: Log stream allows you to annotate your function code with custom logging statements which helps you to analyse the execution flow and performance of your AWS Lambda functions.

 

Q57. Use Cases of AWS Lambda

AWS Lambda used for a wide range of applications like:

  1. Helps you for ETL process
  2. Allows you to perform real-time file processing and real-time stream processing
  3. Use for creating web applications
  4. Use in Amazon products like Alexa Chatbots and Amazon Echo/Alexa
  5. Data processing (real-time streaming analytics)
  6. Automated Backups of everyday tasks
  7. Scalable back ends (mobile apps, loT devices)
  8. Helps you to execute server-side backend logic
  9. Allows you to filter and Transform data

 

Q58. Best practices of Lambda function

Here are some best practices of AWS Lambda functions:

  1. Use the right “timeout.”
  2. Utilize the functions of local storage which is 500MB in size in the /temp folder
  3. Minimizing the use of start-up code which is not directly related to processing the current event.
  4. You should use built-in CloudWatch monitoring of your Lambda functions to view and optimize request latencies.

 

Q59. When not to use AWS Lambda

Following are the situation where Lambda is surely not an ideal option:

  1. It is not appropriate to use AWS Lambda software packages or applications which rely on calling underlying Windows RPCs
  2. If is used for custom software applications with licensing agreements like MS-Office document processing, Oracle databases, etc.
  3. AWS Lambda should not be used for custom hardware process such as GPU acceleration, hardware affinity.

 

Q60. Advantages of using AWS Lambda

Here, are pros/benefits of using AWS lambda:

  • AWS Lambda is a highly flexible tool to use
  • It helps you to grant access to resources, including VPCs
  • Author directly with WYSIWYG editor in console.
  • You can use it as a plugin for Eclipse and Visual Studio.
  • As it is serverless architecture, you don’t need to worry about managing or provisioning servers.
  • You do not need to set up any Virtual Machine.
  • Helps developers to run and execute the code’s response to events without building any infrastructure.
  • You just need to for the compute time taken, only when your code runs.
  • You can monitor your code performance in real time through CloudWatch.
  • It allows you to run your code without provisioning or to manage any other server
  • Helps you to execute the code only when needed
  • You can scale it automatically to handle a few requests per day and even support more than thousands of requests per second.
  • AWS Lambda can be configured with the help of external event timers to perform scheduled tasks.
  • Lambda function in AWS should be configured with external event and timers so; it can be used for scheduling.
  • Lambda functions are stateless so that it can be scaled quickly.
  • AWS Lambda is fast so it will execute your code within milliseconds.

 

Q61. Explain Limitations of AWS Lambda

Here are the cons/disadvantages of using AWS Lambda:

  1. AWS Lambda tool is not suitable for small projects.
  2. AWS Lambda entirely relies on AWS for the infrastructure, so you can’t install any additional software if your code demands it.
  3. Concurrent execution is limited to 100
  4. AWS Lambda completely depended on AWS for the infrastructure; you cannot install anything additional software if your code demands it.
  5. Its memory volume can vary between 128 to 1536 MB.
  6. Event request should not exceed 128 KB.
  7. Lambda functions help you to write their logs only in CloudWatch. This is the only tool that allows you to monitor or troubleshoot your functions.
  8. Its code execution timeout is just 5 minutes.

 

Q62.Explain AWS Lambda Pricing

Lambda uses a pay-as-you-go model where users are charged based on what resources they use, how many requests they make, and for the code’s run time.  Run time is calculated by when the code is called to when it either returns or terminates, rounded up to the nearest millisecond.  The pricing for resources typically depends on how much memory is allocated to the program and the CPU power that is applied.

Free Tier: AWS Lambda does offer a free trial for new and unsure users.  This tier offers one million free requests and 400,000 GB-seconds of compute time per month.

Price Calculations:  1) Pay per calls – 0.20$ per 1 million request 2) Pay per duration. 

 

Q63. What is the main difference between an anonymous class and a lambda function?

The fundamental difference is in the emphasis that is placed on a number of different phrases. Keywords are utilized by lambda functions so that they can successfully resolve the functional classes. On the other hand, keywords are employed in order to resolve the anonymous functional class within the anonymous class.

 

Q64. When should I use AWS Lambda functions with more than 3008 MB of memory?

Customers running memory or compute intensive workloads can now powerup their functions. Larger memory functions help multithreaded applications run faster, making them ideal for data and computationally intensive applications like machine learning, batch and ETL jobs, financial modelling, genomics, HPC, and media processing.

 

Q65. How long can an AWS Lambda function execute?

AWS Lambda functions can be configured to run up to 15 minutes per execution. You can set the timeout to any value between 1 second and 15 minutes.

 

Q66. How do I make an AWS Lambda function respond to changes in an Amazon S3 bucket?

From the AWS Lambda console, you can select a function and associate it with notifications from an Amazon S3 bucket. Alternatively, you can use the Amazon S3 console and configure the bucket’s notifications to send to your AWS Lambda function. This same functionality is also available through the AWS SDK and CLI.

 

Q67. Do You Think Lambda Saves Time When It Comes To Coding? 

Yes. Lambda is a timesaver mainly because all the resources are stored in local server memory, making them easy to manage. It can also store data in its database directly without experiencing any performance issues. Lastly, Lambda comes with relatively simple testing techniques, such as integration testing, which can be made better by several vendors. 

 

Q68. Can You Create Different Versions Of Functions In AWS? 

Yes. Lambda is quite flexible and allows users to create different versions of their lambda functions.  Once created, the new version is separated from the original one to facilitate individual testing, after which it can be published and made official. This is possible thanks to Lambda API. When given such a command, it returns a JSON report with a function version number and a unique resource number for referencing the unpublished version of the function. 

 

Q69. How Would You Make Different Lambda Functions Work Together In A Complex Workflow? 

I would build modular lambda functions focusing on specific tasks and then create a step function for invoking each function depending on the given conditions. These test functions are usually responsible for different aspects of such an arrangement. They allow various components to coordinate with one another, even giving them another chance if they fail the first time. They also use state machines to monitor the states of different tasks. State machines are created in the Graphical User Interface. 

 

Q70. How Does AWS Lambda Contribute To Faster Development ?

AWS Lambda has a serverless architecture with several advantages, such as faster development.  This architecture supports rapid innovation, which translates into fewer operational issues. It also allows flexible technology stack updates, saving product engineers time. Users or product engineers can, therefore, entirely focus on the actual business logic of the application since all the system engineering problems have been taken care of. This is why AWS Lambda is quite popular in the business community. 

 

Conclusion

I hope this article helped you to prepare for AWS Lambda Interview Questions and Answers. Therefore, you must ensure that you are well-versed in the technical aspects of AWS Lambda to succeed in your upcoming interview. We wish you all the best, and also remember to give the interviewer an excellent first impression.

 

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