Last updated on August 22, 2024
Here are 10 AWS Certified Solutions Architect Associate SAA-C03 practice exam questions to help you gauge your readiness for the actual exam.
Question 1
A tech company has a CRM application hosted on an Auto Scaling group of On-Demand EC2 instances with different instance types and sizes. The application is extensively used during office hours from 9 in the morning to 5 in the afternoon. Their users are complaining that the performance of the application is slow during the start of the day but then works normally after a couple of hours.
Which of the following is the MOST operationally efficient solution to implement to ensure the application works properly at the beginning of the day?
- Configure a Dynamic scaling policy for the Auto Scaling group to launch new instances based on the CPU utilization.
- Configure a Dynamic scaling policy for the Auto Scaling group to launch new instances based on the Memory utilization.
- Configure a Scheduled scaling policy for the Auto Scaling group to launch new instances before the start of the day.
- Configure a Predictive scaling policy for the Auto Scaling group to automatically adjust the number of Amazon EC2 instances
Correct Answer: 3
Scaling based on a schedule allows you to scale your application in response to predictable load changes. For example, every week the traffic to your web application starts to increase on Wednesday, remains high on Thursday, and starts to decrease on Friday. You can plan your scaling activities based on the predictable traffic patterns of your web application.Â
To configure your Auto Scaling group to scale based on a schedule, you create a scheduled action. The scheduled action tells Amazon EC2 Auto Scaling to perform a scaling action at specified times. To create a scheduled scaling action, you specify the start time when the scaling action should take effect and the new minimum, maximum, and desired sizes for the scaling action. At the specified time, Amazon EC2 Auto Scaling updates the group with the values for minimum, maximum, and desired size specified by the scaling action. You can create scheduled actions for scaling one time only or for scaling on a recurring schedule.
Hence, configuring a Scheduled scaling policy for the Auto Scaling group to launch new instances before the start of the day is the correct answer. You need to configure a Scheduled scaling policy. This will ensure that the instances are already scaled up and ready before the start of the day since this is when the application is used the most.
The following options are both incorrect. Although these are valid solutions, it is still better to configure a Scheduled scaling policy as you already know the exact peak hours of your application. By the time either the CPU or Memory hits a peak, the application already has performance issues, so you need to ensure the scaling is done beforehand using a Scheduled scaling policy:
-Configure a Dynamic scaling policy for the Auto Scaling group to launch new instances based on the CPU utilization
-Configure a Dynamic scaling policy for the Auto Scaling group to launch new instances based on the Memory utilization
The option that says: Configure a Predictive scaling policy for the Auto Scaling group to automatically adjust the number of Amazon EC2 instances is incorrect. Although this type of scaling policy can be used in this scenario, it is not the most operationally efficient option. Take note that the scenario mentioned that the Auto Scaling group consists of Amazon EC2 instances with different instance types and sizes. Predictive scaling assumes that your Auto Scaling group is homogenous, which means that all EC2 instances are of equal capacity. The forecasted capacity can be inaccurate if you are using a variety of EC2 instance sizes and types on your Auto Scaling group.Â
References:
https://docs.aws.amazon.com/autoscaling/ec2/userguide/schedule_time.html
https://docs.aws.amazon.com/autoscaling/ec2/userguide/ec2-auto-scaling-scheduled-scaling.html
https://docs.aws.amazon.com/autoscaling/ec2/userguide/ec2-auto-scaling-predictive-scaling.html#predictive-scaling-limitations
Check out this AWS Auto Scaling Cheat Sheet:
https://tutorialsdojo.com/aws-auto-scaling/
Question 2
A financial application is composed of an Auto Scaling group of EC2 instances, an Application Load Balancer, and a MySQL RDS instance in a Multi-AZ Deployments configuration. To protect the confidential data of your customers, you have to ensure that your RDS database can only be accessed using the profile credentials specific to your EC2 instances via an authentication token.
As the Solutions Architect of the company, which of the following should you do to meet the above requirement?
- Enable the IAM DB Authentication.
- Configure SSL in your application to encrypt the database connection to RDS.
- Create an IAM Role and assign it to your EC2 instances which will grant exclusive access to your RDS instance.
- Use a combination of IAM and STS to restrict access to your RDS instance via a temporary token.
Correct Answer: 1
You can authenticate to your DB instance using AWS Identity and Access Management (IAM) database authentication. IAM database authentication works with MySQL and PostgreSQL. With this authentication method, you don’t need to use a password when you connect to a DB instance. Instead, you use an authentication token.
An authentication token is a unique string of characters that Amazon RDS generates on request. Authentication tokens are generated using AWS Signature Version 4. Each token has a lifetime of 15 minutes. You don’t need to store user credentials in the database, because authentication is managed externally using IAM. You can also still use standard database authentication.
IAM database authentication provides the following benefits:
-
Network traffic to and from the database is encrypted using Secure Sockets Layer (SSL).
-
You can use IAM to centrally manage access to your database resources, instead of managing access individually on each DBÂ instance.
-
For applications running on Amazon EC2, you can use profile credentials specific to your EC2 instance to access your database instead of a password, for greater security
Hence, enabling IAM DB Authentication is the correct answer based on the above reference.
Configuring SSL in your application to encrypt the database connection to RDS is incorrect because an SSL connection is not using an authentication token from IAM. Although configuring SSL to your application can improve the security of your data in flight, it is still not a suitable option to use in this scenario.
Creating an IAM Role and assigning it to your EC2 instances which will grant exclusive access to your RDS instance is incorrect because although you can create and assign an IAM Role to your EC2 instances, you still need to configure your RDS to use IAM DB Authentication.
Using a combination of IAM and STS to restrict access to your RDS instance via a temporary token is incorrect because you have to use IAM DB Authentication for this scenario, and not a combination of an IAM and STS. Although STS is used to send temporary tokens for authentication, this is not a compatible use case for RDS.
Reference:
https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/UsingWithRDS.IAMDBAuth.html
Check out this Amazon RDS cheat sheet:
https://tutorialsdojo.com/amazon-relational-database-service-amazon-rds/
Question 3
A company hosted a web application in an Auto Scaling group of EC2 instances. The IT manager is concerned about the over-provisioning of the resources that can cause higher operating costs. A Solutions Architect has been instructed to create a cost-effective solution without affecting the performance of the application.
Which dynamic scaling policy should be used to satisfy this requirement?
- Use simple scaling.
- Use scheduled scaling.
- Use suspend and resume scaling.
- Use target tracking scaling.
Correct Answer: 4
An Auto Scaling group contains a collection of Amazon EC2 instances that are treated as a logical grouping for the purposes of automatic scaling and management. An Auto Scaling group also enables you to use Amazon EC2 Auto Scaling features such as health check replacements and scaling policies. Both maintaining the number of instances in an Auto Scaling group and automatic scaling are the core functionality of the Amazon EC2 Auto Scaling service. The size of an Auto Scaling group depends on the number of instances that you set as the desired capacity. You can adjust its size to meet demand, either manually or by using automatic scaling.
Step scaling policies and simple scaling policies are two of the dynamic scaling options available for you to use. Both require you to create CloudWatch alarms for the scaling policies. Both require you to specify the high and low thresholds for the alarms. Both require you to define whether to add or remove instances, and how many, or set the group to an exact size. The main difference between the policy types is the step adjustments that you get with step scaling policies. When step adjustments are applied, and they increase or decrease the current capacity of your Auto Scaling group, the adjustments vary based on the size of the alarm breach.
The primary issue with simple scaling is that after a scaling activity is started, the policy must wait for the scaling activity or health check replacement to complete and the cooldown period to expire before responding to additional alarms. Cooldown periods help to prevent the initiation of additional scaling activities before the effects of previous activities are visible.
With a target tracking scaling policy, you can increase or decrease the current capacity of the group based on a target value for a specific metric. This policy will help resolve the over-provisioning of your resources. The scaling policy adds or removes capacity as required to keep the metric at, or close to, the specified target value. In addition to keeping the metric close to the target value, a target tracking scaling policy also adjusts to changes in the metric due to a changing load pattern.Â
Hence, the correct answer is: Use target tracking scaling.
The option that says: Use simple scaling is incorrect because you need to wait for the cooldown period to complete before initiating additional scaling activities. Target tracking or step scaling policies can trigger a scaling activity immediately without waiting for the cooldown period to expire.
The option that says: Use scheduled scaling is incorrect because this policy is mainly used for predictable traffic patterns. You need to use the target tracking scaling policy to optimize the cost of your infrastructure without affecting the performance.
The option that says: Use suspend and resume scaling is incorrect because this type is used to temporarily pause scaling activities triggered by your scaling policies and scheduled actions.Â
References:
https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-scaling-target-tracking.html
https://docs.aws.amazon.com/autoscaling/ec2/userguide/AutoScalingGroup.html
Check out this AWS Auto Scaling Cheat Sheet:
https://tutorialsdojo.com/aws-auto-scaling/
Question 4
An online medical system hosted in AWS stores sensitive Personally Identifiable Information (PII) of the users in an Amazon S3 bucket. Both the master keys and the unencrypted data should never be sent to AWS to comply with the strict compliance and regulatory requirements of the company.
Which S3 encryption technique should the Architect use?
- Use S3 client-side encryption with an AWS KMS key.
- Use S3 client-side encryption with a client-side master key.
- Use S3 server-side encryption with a KMS key.
- Use S3 server-side encryption with customer provided key.
Correct Answer: 2
Client-side encryption is the act of encrypting data before sending it to Amazon S3. To enable client-side encryption, you have the following options:
– Use an AWS KMS key.
– Use a client-side master key.
When using an AWS KMS key to enable client-side data encryption, you provide an AWS KMS key identifier (KeyId) to AWS. On the other hand, when you use client-side master key for client-side data encryption, your client-side master keys and your unencrypted data are never sent to AWS. It’s important that you safely manage your encryption keys because if you lose them, you can’t decrypt your data.
This is how client-side encryption using a client-side master key works:
When uploading an object – You provide a client-side master key to the Amazon S3 encryption client. The client uses the master key only to encrypt the data encryption key that it generates randomly. The process works like this:
1. The Amazon S3 encryption client generates a one-time-use symmetric key (also known as a data encryption key or data key) locally. It uses the data key to encrypt the data of a single Amazon S3 object. The client generates a separate data key for each object.
2. The client encrypts the data encryption key using the master key that you provide. The client uploads the encrypted data key and its material description as part of the object metadata. The client uses the material description to determine which client-side master key to use for decryption.
3. The client uploads the encrypted data to Amazon S3 and saves the encrypted data key as object metadata (x-amz-meta-x-amz-key) in Amazon S3.
When downloading an object –Â The client downloads the encrypted object from Amazon S3. Using the material description from the object’s metadata, the client determines which master key to use to decrypt the data key. The client uses that master key to decrypt the data key and then uses the data key to decrypt the object.
Hence, the correct answer is:Â Use S3 client-side encryption with a client-side master key.
The option that says: Use S3 client-side encryption with an AWS KMS key is incorrect because, in client-side encryption with a KMS key, you provide an AWS KMS key identifier (KeyId) to AWS. The scenario clearly indicates that both the master keys and the unencrypted data should never be sent to AWS.
The option that says: Use S3 server-side encryption with a KMS key is incorrect because the scenario mentioned that the unencrypted data should never be sent to AWS, which means that you have to use client-side encryption in order to encrypt the data first before sending to AWS. In this way, you can ensure that there is no unencrypted data being uploaded to AWS. In addition, the master key used by Server-Side Encryption with AWS KMS–Managed Keys (SSE-KMS) is uploaded and managed by AWS, which directly violates the requirement of not uploading the master key.
The option that says:Â Use S3 server-side encryption with customer provided key is incorrect because, just as mentioned above, you have to use client-side encryption in this scenario instead of server-side encryption. For the S3 server-side encryption with a customer-provided key (SSE-C), you actually provide the encryption key as part of your request to upload the object to S3. Using this key, Amazon S3 manages both the encryption (as it writes to disks) and decryption (when you access your objects).
References:
https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingEncryption.html
https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingClientSideEncryption.html
Question 5
A Solutions Architect is hosting a website in an Amazon S3 bucket named tutorialsdojo. The users load the website using the following URL: http://tutorialsdojo.s3-website-us-east-1.amazonaws.com and there is a new requirement to add a JavaScript on the webpages in order to make authenticated HTTPÂ GET requests against the same bucket by using the Amazon S3 API endpoint (tutorialsdojo.s3.amazonaws.com). Upon testing, you noticed that the web browser blocks JavaScript from allowing those requests.
Which of the following options is the MOST suitable solution that you should implement for this scenario?
- Enable cross-account access.
- Enable Cross-Zone Load Balancing.
- Enable Cross-origin resource sharing (CORS) configuration in the bucket.
- Enable Cross-Region Replication (CRR).
Correct Answer: 3
Cross-origin resource sharing (CORS) defines a way for client web applications that are loaded in one domain to interact with resources in a different domain. With CORS support, you can build rich client-side web applications with Amazon S3 and selectively allow cross-origin access to your Amazon S3 resources.
Suppose that you are hosting a website in an Amazon S3 bucket named your-website and your users load the website endpoint http://your-website.s3-website-us-east-1.amazonaws.com. Now you want to use JavaScript on the webpages that are stored in this bucket to be able to make authenticated GET and PUT requests against the same bucket by using the Amazon S3 API endpoint for the bucket, your-website.s3.amazonaws.com. A browser would normally block JavaScript from allowing those requests, but with CORS you can configure your bucket to explicitly enable cross-origin requests from your-website.s3-website-us-east-1.amazonaws.com.
In this scenario, you can solve the issue by enabling the CORS in the S3 bucket. Hence, enabling Cross-origin resource sharing (CORS) configuration in the bucket is the correct answer.
Enabling cross-account access is incorrect because cross-account access is a feature in IAM and not in Amazon S3.
Enabling Cross-Zone Load Balancing is incorrect because Cross-Zone Load Balancing is only used in ELB and not in S3.
Enabling Cross-Region Replication (CRR) is incorrect because CRR is a bucket-level configuration that enables automatic, asynchronous copying of objects across buckets in different AWS Regions.
References:
http://docs.aws.amazon.com/AmazonS3/latest/dev/cors.html
https://docs.aws.amazon.com/AmazonS3/latest/dev/ManageCorsUsing.html
Question 6
A company is designing a banking portal that uses Amazon ElastiCache for Redis as its distributed session management component. To secure session data and ensure that Cloud Engineers must authenticate before executing Redis commands, specifically MULTI EXECÂ commands, the system should enforce strong authentication by requiring users to enter a password. Additionally, access should be managed with long-lived credentials while supporting robust security practices.
As the Solutions Architect, which of the following should you do to meet the above requirement?
- Generate an IAM authentication token using AWS credentials and provide this token as a password.
- Set up a Redis replication group and enable the
AtRestEncryptionEnabledparameter. - Authenticate the users using Redis AUTH by creating a new Redis Cluster with both the
--transit-encryption-enabledand--auth-token parameters enabled. - Enable the in-transit encryption for Redis replication groups.
Correct Answer: 3
Using Redis AUTH command can improve data security by requiring the user to enter a password before they are granted permission to execute Redis commands on a password-protected Redis server. Hence, the correct answer is: Authenticate the users using Redis AUTH by creating a new Redis Cluster with both the --transit-encryption-enabled and --auth-token parameters enabled.
To require that users enter a password on a password-protected Redis server, include the parameter --auth-token with the correct password when you create your replication group or cluster and on all subsequent commands to the replication group or cluster.
The option that says: Generate an IAM authentication token using AWS credentials and provide this token as a password is incorrect. IAM authentication is simply not supported for executing Redis commands like MULTI EXEC, and IAM tokens expire every 12 hours, which does not align with the need for long-lived credentials.
The option that says: Set up a Redis replication group and enable the AtRestEncryptionEnabled parameter is incorrect because the Redis At-Rest Encryption feature only secures the data inside the in-memory data store. You have to use the Redis AUTH option instead.
The option that says: Enable the in-transit encryption for Redis replication groups is incorrect. Although in-transit encryption is part of the solution, it is missing the most important thing which is the Redis AUTH
References:
https://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/auth.html
https://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/encryption.html
Check out this Amazon Elasticache Cheat Sheet:
https://tutorialsdojo.com/amazon-elasticache/
Redis (cluster mode enabled vs disabled) vs Memcached:
https://tutorialsdojo.com/redis-cluster-mode-enabled-vs-disabled-vs-memcached/
Question 7
A company runs an online payments application in an Auto Scaling group of Amazon EC2 instances in multiple Availability Zones. The EC2 instances are all launched in private subnets. An internet-facing Application Load Balancer (ALB) has been provisioned and points to the existing EC2 instances as the target group. The team noticed that the internet traffic was not reaching the Amazon EC2 instances.
What is the MOST operationally efficient solution that meets these requirements?
- Set up a NAT gateway in a public subnet to allow incoming Internet traffic. Use a Gateway Load Balancer instead of an Application Load Balancer.
- Move the existing Amazon EC2 instances that are running from the private subnets to public subnets. Allow outbound traffic to
0.0.0.0/0Â in the security groups of the EC2 instances. - Add a rule to allow outbound traffic to
0.0.0.0/0Fin the security groups of the EC2 instances. Update the route tables of the existing subnets to send all0.0.0.0/0Â traffic through the internet gateway route. - Launch public subnets in each Availability Zone and associate them with the Application Load Balancer. Modify the route tables for the public subnets with a route to the private subnets of the EC2 instances.
Correct Answer: 4
An Application Load Balancer functions at the application layer, the seventh layer of the Open Systems Interconnection (OSI) model. After the load balancer receives a request, it evaluates the listener rules in priority order to determine which rule to apply and then selects a target from the target group for the rule action. You can configure listener rules to route requests to different target groups based on the content of the application traffic. Routing is performed independently for each target group, even when a target is registered with multiple target groups. You can configure the routing algorithm used at the target group level. The default routing algorithm is round robin; alternatively, you can specify the least outstanding requests routing algorithm.
You can add and remove targets from your load balancer as your needs change without disrupting the overall flow of requests to your application. Elastic Load Balancing scales your load balancer as traffic to your application changes over time. Elastic Load Balancing can scale to the vast majority of workloads automatically.
If you are launching an Application Load Balancer, you can choose from an:
-Internet-facing load balancer
-Internal load balancer
The nodes of an internet-facing load balancer have public IP addresses. The DNS name of an internet-facing load balancer is publicly resolvable to the public IP addresses of the nodes. Therefore, internet-facing load balancers can route requests from clients over the internet.
The nodes of an internal load balancer have only private IP addresses. The DNS name of an internal load balancer is publicly resolvable to the private IP addresses of the nodes. Therefore, internal load balancers can only route requests from clients with access to the VPC for the load balancer.
Both internet-facing and internal load balancers route requests to your targets using private IP addresses. Therefore, your targets do not need public IP addresses to receive requests from an internal or an internet-facing load balancer.
If your application has multiple tiers, you can design an architecture that uses both internal and internet-facing load balancers. For example, this is true if your application uses web servers that must be connected to the internet and application servers that are only connected to the web servers. Create an internet-facing load balancer and register the web servers with it. Create an internal load balancer and register the application servers with it. The web servers receive requests from the internet-facing load balancer and send requests for the application servers to the internal load balancer. The application servers receive requests from the internal load balancer.
In this scenario, you have an internet-facing load balancer with an attached Amazon EC2 instances that are launched in a private subnet. You can create public subnets in the same Availability Zones as the private subnets used by the backend instances. Afterward, associate the public subnets with your load balancer.
Hence, the correct answer is: Launch public subnets in each Availability Zone and associate them with the Application Load Balancer. Modify the route tables for the public subnets with a route to the private subnets of the EC2 instances.
The option that says: Set up a NAT gateway in a public subnet to allow incoming Internet traffic. Use a Gateway Load Balancer instead of an Application Load Balancer is incorrect because the scenario does not warrant the use of a Gateway Load Balancer since the issue is merely the connectivity between the public Internet and the EC2 instances.Â
The option that says: Move the existing Amazon EC2 instances that are running from the private subnets to public subnets. Allow outbound traffic to 0.0.0.0/0 in the security groups of the EC2 instances is incorrect because moving the instances to a public subnet would be a security risk. This shouldn’t be done simply because of a connectivity problem as it can compromise the security of your application. Remember that the EC2 instances hosted in a public subnet would be exposed on the world wide web where web vulnerability attacks run aplenty.
The option that says: Add a rule to allow outbound traffic to 0.0.0.0/0 in the security groups of the EC2 instances. Update the route tables of the existing subnets to send all 0.0.0.0/0 traffic through the internet gateway route is incorrect because a security group is stateful, which means that if its inbound rules accept a traffic from the Internet, then there’s no need to configure its corresponding outbound rules.
References:
https://aws.amazon.com/premiumsupport/knowledge-center/public-load-balancer-private-ec2/
https://docs.aws.amazon.com/vpc/latest/userguide/VPC_SecurityGroups.html
Check out this Elastic Load Balancing Cheat Sheet:
https://tutorialsdojo.com/aws-elastic-load-balancing-elb/
Question 8
The company that you are working for has a highly available architecture consisting of an elastic load balancer and several EC2 instances configured with auto-scaling in three Availability Zones. You want to monitor your EC2 instances based on a particular metric, which is not readily available in CloudWatch.
Which of the following is a custom metric in CloudWatch which you have to manually set up?
- Memory Utilization of an EC2 instance
- CPU Utilization of an EC2 instance
- Disk Reads activity of an EC2 instance
- Network packets out of an EC2 instance
Correct Answer: 1
CloudWatch has available Amazon EC2 Metrics for you to use for monitoring. CPU Utilization identifies the processing power required to run an application upon a selected instance. Network Utilization identifies the volume of incoming and outgoing network traffic to a single instance. Disk Reads metric is used to determine the volume of the data the application reads from the hard disk of the instance. This can be used to determine the speed of the application. However, there are certain metrics that are not readily available in CloudWatch such as memory utilization, disk space utilization, and many others which can be collected by setting up a custom metric.
You need to prepare a custom metric using CloudWatch Monitoring Scripts which is written in Perl. You can also install CloudWatch Agent to collect more system-level metrics from Amazon EC2 instances. Here’s the list of custom metrics that you can set up:
– Memory utilization
– Disk swap utilization
– Disk space utilization
– Page file utilization
– Log collection
CPU Utilization of an EC2 instance, Disk Reads activity of an EC2 instance, and Network packets out of an EC2 instance are all incorrect because these metrics are readily available in CloudWatch by default.
References:Â
https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/monitoring_ec2.html
https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/mon-scripts.html#using_put_script
Check out this Amazon EC2 Cheat Sheet:
https://tutorialsdojo.com/amazon-elastic-compute-cloud-amazon-ec2/
Check out this Amazon CloudWatch Cheat Sheet:
https://tutorialsdojo.com/amazon-cloudwatch/
Question 9
A software development company is using serverless computing with AWS Lambda to build and run applications without having to set up or manage servers. They have a Lambda function that connects to a MongoDB Atlas, which is a popular Database as a Service (DBaaS) platform and also uses a third party API to fetch certain data for their application. One of the developers was instructed to create the environment variables for the MongoDB database hostname, username, and password as well as the API credentials that will be used by the Lambda function for DEV, SIT, UAT, and PROD environments.
Considering that the Lambda function is storing sensitive database and API credentials, how can this information be secured to prevent other developers in the team, or anyone, from seeing these credentials in plain text? Select the best option that provides maximum security.
- There is no need to do anything because, by default, AWS Lambda already encrypts the environment variables using the AWS Key Management Service.
- Enable SSL encryption that leverages on AWS CloudHSM to store and encrypt the sensitive information.
- AWS Lambda does not provide encryption for the environment variables. Deploy your code to an EC2 instance instead.
- Create a new KMS key and use it to enable encryption helpers that leverage on AWS Key Management Service to store and encrypt the sensitive information.
Correct Answer: 4
When you create or update Lambda functions that use environment variables, AWS Lambda encrypts them using the AWS Key Management Service. When your Lambda function is invoked, those values are decrypted and made available to the Lambda code.
The first time you create or update Lambda functions that use environment variables in a region, a default service key is created for you automatically within AWS KMS. This key is used to encrypt environment variables. However, if you wish to use encryption helpers and use KMS to encrypt environment variables after your Lambda function is created, you must create your own AWS KMS key and choose it instead of the default key. The default key will give errors when chosen. Creating your own key gives you more flexibility, including the ability to create, rotate, disable, and define access controls, and to audit the encryption keys used to protect your data.
Hence, the correct answer is:Â Create a new KMS key and use it to enable encryption helpers that leverage on AWS Key Management Service to store and encrypt the sensitive information.
The option that says:Â There is no need to do anything because, by default, AWS Lambda already encrypts the environment variables using the AWS Key Management Service is incorrect. Although Lambda encrypts the environment variables in your function by default, the sensitive information would still be visible to other users who have access to the Lambda console. This is because Lambda uses a default KMS key to encrypt the variables, which is usually accessible by other users. The best option in this scenario is to use encryption helpers to secure your environment variables.
The option that says:Â Enable SSL encryption that leverages on AWS CloudHSM to store and encrypt the sensitive information is also incorrect since enabling SSL would encrypt data only when in-transit. Your other teams would still be able to view the plaintext at-rest. Use AWS KMS instead.
The option that says:Â AWS Lambda does not provide encryption for the environment variables. Deploy your code to an EC2 instance instead is incorrect since, as mentioned, Lambda does provide encryption functionality of environment variables.
References:
https://docs.aws.amazon.com/lambda/latest/dg/env_variables.html#env_encrypt
https://docs.aws.amazon.com/lambda/latest/dg/tutorial-env_console.html
Check out this AWS Lambda Cheat Sheet:
https://tutorialsdojo.com/aws-lambda/
Question 10
There was an incident in your production environment where the user data stored in the S3 bucket has been accidentally deleted by one of the Junior DevOps Engineers. The issue was escalated to your manager and after a few days, you were instructed to improve the security and protection of your AWS resources.
What combination of the following options will protect the S3 objects in your bucket from both accidental deletion and overwriting? (Select TWO.)
- Enable Versioning
- Provide access to S3 data strictly through pre-signed URL only
- Disallow S3 Delete using an IAM bucket policy
- Enable Amazon S3 Intelligent-Tiering
- Enable Multi-Factor Authentication Delete
Correct Answer: 1,5
By using Versioning and enabling MFA (Multi-Factor Authentication) Delete, you can secure and recover your S3 objects from accidental deletion or overwrite.Â
Versioning is a means of keeping multiple variants of an object in the same bucket. Versioning-enabled buckets enable you to recover objects from accidental deletion or overwrite. You can use versioning to preserve, retrieve, and restore every version of every object stored in your Amazon S3 bucket. With versioning, you can easily recover from both unintended user actions and application failures.
You can also optionally add another layer of security by configuring a bucket to enable MFA (Multi-Factor Authentication) Delete, which requires additional authentication for either of the following operations:
– Change the versioning state of your bucket
– Permanently delete an object version
MFA Delete requires two forms of authentication together:
– Your security credentials
– The concatenation of a valid serial number, a space, and the six-digit code displayed on an approved authentication device
Â
 Hence, the correct answers are:
– Enable Versioning
–Â Enable Multi-Factor Authentication Delete
Providing access to S3 data strictly through pre-signed URL only is incorrect since a pre-signed URL gives access to the object identified in the URL. Pre-signed URLs are useful when customers perform an object upload to your S3Â bucket, but does not help in preventing accidental deletes.
Disallowing S3 Delete using an IAM bucket policy is incorrect since you still want users to be able to delete objects in the bucket, and you just want to prevent accidental deletions. Disallowing S3 Delete using an IAM bucket policy will restrict all delete operations to your bucket.
Enabling Amazon S3 Intelligent-Tiering is incorrect since S3 intelligent tiering does not help in this situation.
Reference:Â
https://docs.aws.amazon.com/AmazonS3/latest/dev/Versioning.html
Check out this Amazon S3 Cheat Sheet:
https://tutorialsdojo.com/amazon-s3/
For more practice questions like these and to further prepare you for the actual AWS Certified Solutions Architect Associate SAA-C03 exam, we recommend that you take our top-notch AWS Certified Solutions Architect Associate Practice Exams, which have been regarded as the best in the market.Â
Also check out our AWS Certified Solutions Architect Associate SAA-C03 Exam Study Guide here.
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Written by: Jon Bonso
