A developer is creating an ecommerce workflow in an AWS Step Functions state machine that includes an HTTP Task state. The task passes shipping information and order details to an endpoint.
The developer needs to test the workflow to confirm that the HTTP headers and body are correct and that the responses meet expectations.
Which solution will meet these requirements?
State Machine Testing with Logs:
Changing the log level to ALL enables capturing detailed request and response data. This helps verify HTTP headers, body, and responses.
Incorrect Options Analysis:
Option A and B: The TestState API is not a valid option for Step Functions.
Option C: A data flow simulator does not exist for AWS Step Functions.
A company is deploying a critical application by using Amazon RDS for MySQL. The application must be highly available and must recover automatically. The company needs to support interactive users (transactional queries) and batch reporting (analytical queries) with no more than a 4-hour lag. The analytical queries must not affect the performance of the transactional queries.
Key Requirements:
High availability and automatic recovery.
Separate transactional and analytical queries with minimal performance impact.
Allow up to a 4-hour lag for analytical queries.
Analysis of Options:
Option A:
Multi-AZ deployments provide high availability but do not include read replicas for separating transactional and analytical queries.
Analytical queries on the secondary DB instance would impact the transactional workload.
Incorrect Approach: Does not meet the requirement of query separation.
Option B:
Multi-AZ DB clusters provide high availability and include a reader endpoint. However, these are better suited for Aurora and not RDS for MySQL.
Incorrect Approach: Not applicable to standard RDS for MySQL.
Option C:
Multiple read replicas allow separation of transactional and analytical workloads.
Queries can be pointed to a replica in a different AZ, ensuring no impact on transactional queries.
Correct Approach: Meets all requirements with high availability and query separation.
Option D:
Creating nightly snapshots and read-only databases adds significant operational overhead and does not support the 4-hour lag requirement.
Incorrect Approach: Not practical for dynamic query separation.
AWS Solution Architect Reference:
A company has a three-tier environment on AWS that ingests sensor data from its users' devices The traffic flows through a Network Load Balancer (NIB) then to Amazon EC2 instances for the web tier and finally to EC2 instances for the application tier that makes database calls
What should a solutions architect do to improve the security of data in transit to the web tier?
A: How do you protect your data in transit?
Best Practices:
Implement secure key and certificate management: Store encryption keys and certificates securely and rotate them at appropriate time intervals while applying strict access control; for example, by using a certificate management service, such as AWS Certificate Manager (ACM).
Enforce encryption in transit: Enforce your defined encryption requirements based on appropriate standards and recommendations to help you meet your organizational, legal, and compliance requirements.
Automate detection of unintended data access: Use tools such as GuardDuty to automatically detect attempts to move data outside of defined boundaries based on data classification level, for example, to detect a trojan that is copying data to an unknown or untrusted network using the DNS protocol.
Authenticate network communications: Verify the identity of communications by using protocols that support authentication, such as Transport Layer Security (TLS) or IPsec.
https://wa.aws.amazon.com/wat.question.SEC_9.en.html
How can a company detect and notify security teams about PII in S3 buckets?
Amazon Macie is purpose-built for detecting PII in S3.
Option A uses EventBridge to filter SensitiveData findings and notify via SNS, meeting the requirements.
Options B and D involve GuardDuty, which is not designed for PII detection.
Option C uses SQS, which is less suitable for immediate notifications.
An ecommerce company is migrating its on-premises workload to the AWS Cloud. The workload currently consists of a web application and a backend Microsoft SQL database for storage.
The company expects a high volume of customers during a promotional event. The new infrastructure in the AWS Cloud must be highly available and scalable.
Which solution will meet these requirements with the LEAST administrative overhead?
To ensure high availability and scalability, the web application should run in an Auto Scaling group across two Availability Zones behind an Application Load Balancer (ALB). The database should be migrated to Amazon RDS with Multi-AZ deployment, which ensures fault tolerance and automatic failover in case of an AZ failure. This setup minimizes administrative overhead while meeting the company's requirements for high availability and scalability.
Option A: Read replicas are typically used for scaling read operations, and Multi-AZ provides better availability for a transactional database.
Option B: Replicating across AWS Regions adds unnecessary complexity for a single web application.
Option D: EC2 instances across three Availability Zones add unnecessary complexity for this scenario.
AWS Reference:
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