Amazon AWS Certified SysOps Administrator - Associate SOA-C02 Exam Practice Test

Answer : A

To address the issue of slow startup times during unexpected traffic surges, a warm pool for the Auto Scaling group is an effective solution:

Warm Pool Concept: A warm pool allows you to maintain a set of pre-initialized or partially initialized EC2 instances that are not actively serving traffic but can be quickly brought online when needed.

Management of Instances: Instances in the warm pool can be kept in a stopped state and then started much more quickly than launching new instances, as the machine-specific data caches are already created.

Scalability and Responsiveness: During a surge in traffic, especially unpredictable ones like those triggered by advertisements, instances from the warm pool can be rapidly activated to handle the increased load, ensuring that the application remains responsive without the typical delays associated with boot processes.

This method significantly reduces the time to scale out by utilizing pre-warmed instances, enhancing the application's ability to cope with sudden and substantial increases in traffic.

Answer : D

To route traffic based on the URL path during a transition period where both an EC2-based legacy application and a new AWS Lambda function are in use:

Use of Application Load Balancer (ALB): ALBs support advanced request routing based on the URL path, among other criteria. This capability allows the ALB to evaluate the URL path of incoming requests and route them appropriately to either the legacy EC2 instances or the Lambda function.

Path-Based Routing Rules: Configure the ALB with rules that specify which URL paths should be directed to the EC2 instances and which should be routed to the Lambda function. For example, requests to /legacy/* might go to the EC2 instances, while /new/* could be directed to the Lambda function.

Integration with Lambda: ALBs can directly invoke Lambda functions in response to HTTP requests, making them ideal for scenarios where both server-based and serverless components are used in tandem.

This setup not only facilitates a smooth transition by enabling simultaneous operation of both components but also leverages the native capabilities of ALBs to manage traffic based on application requirements effectively.

Answer : A

For member accounts in AWS Organizations to receive notifications about estimated costs exceeding a predetermined amount, billing alerts must be enabled in the management/payer account.

Enable Billing Alerts in the Management Account:

Open the AWS Billing and Cost Management console at AWS Billing Console.

In the navigation pane, choose Billing preferences.

Under Billing preferences, ensure that Receive Billing Alerts is enabled.

Create a Budget and Set Up Notifications:

Open the AWS Budgets console at AWS Budgets Console.

Create a budget and configure it to monitor the estimated costs.

Set up notifications for when the budget thresholds are exceeded and specify the email addresses of the managers in the member accounts.

By enabling billing alerts in the management account, you allow member accounts to receive notifications about their estimated costs.

Setting Up Alerts and Notifications

Creating an AWS Budget

Answer : D

https://docs.aws.amazon.com/vpc/latest/userguide/egress-only-internet-gateway.html

To allow outbound IPv6 traffic from instances in your VPC to the internet, but prevent inbound traffic from the internet, you should use an egress-only internet gateway.

Egress-Only Internet Gateway:

An egress-only internet gateway is a horizontally scaled, redundant, and highly available VPC component that allows outbound communication over IPv6 from instances in your VPC to the internet and prevents the internet from initiating an IPv6 connection with your instances.

Routing Configuration:

Open the Amazon VPC console.

Select the route table associated with your VPC.

Add a route for IPv6 traffic (destination ::/0) to the egress-only internet gateway.

Egress-Only Internet Gateways

Routing for IPv6 Traffic

Answer : B

To allow the TTL (Time to Live) of individual pages to vary while adhering to the maximum and minimum TTL settings configured for the Amazon CloudFront distribution, setting cache behaviors directly at the origin is most effective:

Use Cache-Control Headers: By configuring the Cache-Control: max-age directive in the HTTP headers of the objects served from the origin, you can specify how long an object should be cached by CloudFront before it is considered stale.

Integration with CloudFront: When CloudFront receives a request for an object, it checks the cache-control header to determine the TTL for that specific object. This allows individual objects to have their own TTL settings, as long as they are within the globally set minimum and maximum TTL values for the distribution.

Operational Efficiency: This method does not require any additional AWS services or modifications to the distribution settings. It leverages HTTP standard practices, ensuring compatibility and ease of management.

Implementing the TTL management through cache-control headers at the origin provides precise control over caching behavior, aligning with varying content freshness requirements without complex configurations.

Answer : B

To analyze CloudWatch logs across multiple AWS Lambda functions for historical errors, the most operationally efficient way is to use AWS Glue and Amazon Athena.

AWS Glue and Amazon Athena:

AWS Glue can crawl the data in S3, creating a catalog that makes it queryable.

Amazon Athena allows you to run SQL queries on the data cataloged by AWS Glue.

Steps to Implement:

Set up an AWS Glue crawler to index the logs stored in S3.

Configure the crawler to create a table in the AWS Glue Data Catalog.

Use Amazon Athena to query the table for errors using SQL. Since errors have a common string prefix, you can use SQL queries to filter and find these errors.

AWS Glue

Amazon Athena

Answer : D

Evictions in Redis occur when memory is full and new data overwrites older data. To reduce evictions and retain more data:

Increase node size (memory capacity) or

Add more nodes (sharding)

From ElastiCache Redis eviction documentation:

High eviction count suggests memory pressure. To reduce evictions, consider increasing node size.