P.S.JpexamがGoogle Driveで共有している無料の2026 Amazon SAA-C03ダンプ：https://drive.google.com/open?id=1NB6tRtuN9c02QCzOCGWoK3L-GToNp6ly
今の競争の激しいのIT業界の中にAmazon SAA-C03認定試験に合格して、自分の社会地位を高めることができます。弊社のIT業で経験豊富な専門家たちが正確で、合理的なAmazon SAA-C03「AWS Certified Solutions Architect - Associate」認証問題集を作り上げました。 弊社の勉強の商品を選んで、多くの時間とエネルギーを節約こともできます。
| Section | Weight | Objectives |
|---|---|---|
| Design High-Performing Architectures | 24% | - Design high-performance storage solutions
|
| Design Cost-Optimized Architectures | 20% | - Identify cost-effective storage solutions
|
| Design Resilient Architectures | 26% | - Design for reliability and recovery
|
| Design Secure Architectures | 30% | - Design for security and threat detection
|
私たちは皆、ほとんどの候補者が製品の品質を心配することを知っていました。SAA-C03学習教材の品質を保証するために、会社のすべての労働者は、共通の目標のために、 ; SAA-C03試験問題です。 SAA-C03ガイドトレントを購入すると、高品質の製品、リーズナブルな価格、アフターサービスを提供することが保証されます。私たちのSAA-C03テストトレントは、他の学習教材よりもあなたにとってより良い選択だと思います。
質問 # 595
A company hosts an internal serverless application on AWS by using Amazon API Gateway and AWS Lambda. The company's employees report issues with high latency when they begin using the application each day. The company wants to reduce latency.
Which solution will meet these requirements?
正解：D
解説：
AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. Lambda scales automatically based on the incoming requests, but it may take some time to initialize new instances of your function if there is a sudden increase in demand. This may result in high latency or cold starts for your application. To avoid this, you can use provisioned concurrency, which ensures that your function is initialized and ready to respond at any time. You can also set up a scheduled scaling policy that increases the provisioned concurrency before employees begin to use the application each day, and decreases it when the demand is low. References: https://docs.aws.amazon.com/lambda/latest/dg/configuration- concurrency.html
質問 # 596
A company has a web application in the AWS Cloud and wants to collect transaction data in real time. The company wants to prevent data duplication and does not want to manage infrastructure. The company wants to perform additional processing on the data after the data is collected.
Which solution will meet these requirements?
正解：A
解説：
* Understanding the Requirement: The company needs to collect transaction data in real time, avoid data duplication, and perform additional processing without managing infrastructure.
* Analysis of Options:
* SQS FIFO Queue with Lambda: Ensures data is processed in order and prevents duplication.
Lambda handles processing without the need to manage servers.
* SQS FIFO Queue with AWS Batch: While this ensures no duplicates, it introduces additional complexity and management overhead with AWS Batch.
* Kinesis Data Streams with AWS Batch and EC2: Involves more components and infrastructure management, which is against the requirement of not wanting to manage infrastructure.
* Step Functions with Lambda and EC2: Involves setting up multiple services and still requires managing EC2 instances, increasing complexity.
* Best Solution:
* SQS FIFO Queue with Lambda: This combination ensures real-time data processing, prevents duplication, and minimizes infrastructure management, meeting all requirements efficiently.
References:
* Amazon SQS FIFO Queues
* AWS Lambda and SQS Integration
質問 # 597
A weather forecasting company needs to process hundreds of gigabytes of data with sub- millisecond latency. The company has a high performance computing (HPC) environment in its data center and wants to expand its forecasting capabilities. A solutions architect must identify a highly available cloud storage solution that can handle large amounts of sustained throughput Files that are stored in the solution should be accessible to thousands of compute instances that will simultaneously access and process the entire dataset. What should the solutions architect do to meet these requirements?
正解：B
解説：
Amazon FSx for Lustre: Lustre is a high-performance file system designed for workloads that require fast storage with sustained high throughput and low latency. It integrates with Amazon S3, making it suitable for HPC environments.
Persistent File Systems:
Persistent Storage: Suitable for long-term storage and recurrent use, providing durability and availability.
High Throughput and Low Latency: Persistent Lustre file systems can handle large amounts of data with sub-millisecond latency, meeting the needs of high-performance computing workloads.
Simultaneous Access: FSx for Lustre allows thousands of compute instances to access and process large datasets concurrently, ensuring that the high volume of data is handled efficiently.
Highly Available: FSx for Lustre is designed to provide high availability and is managed by AWS, reducing the operational burden.
質問 # 598
A startup is using Amazon RDS to store data from a web application. Most of the time, the application has low user activity but it receives bursts of traffic within seconds whenever there is a new product announcement. The Solutions Architect needs to create a solution that will allow users around the globe to access the data using an API.
What should the Solutions Architect do meet the above requirement?
正解：C
解説：
AWS Lambda lets you run code without provisioning or managing servers. You pay only for the compute time you consume. With Lambda, you can run code for virtually any type of application or backend service - all with zero administration. Just upload your code, and Lambda takes care of everything required to run and scale your code with high availability. You can set up your code to automatically trigger from other AWS services or call it directly from any web or mobile app.
The first time you invoke your function, AWS Lambda creates an instance of the function and runs its handler method to process the event. When the function returns a response, it stays active and waits to process additional events. If you invoke the function again while the first event is being processed, Lambda initializes another instance, and the function processes the two events concurrently. As more events come in, Lambda routes them to available instances and creates new instances as needed.
When the number of requests decreases, Lambda stops unused instances to free up the scaling capacity for other functions.
Your functions' concurrency is the number of instances that serve requests at a given time. For an initial burst of traffic, your functions' cumulative concurrency in a Region can reach an initial level of between 500 and 3000, which varies per Region.
Based on the given scenario, you need to create a solution that will satisfy the two requirements. The first requirement is to create a solution that will allow the users to access the data using an API. To implement this solution, you can use Amazon API Gateway. The second requirement is to handle the burst of traffic within seconds. You should use AWS Lambda in this scenario because Lambda functions can absorb reasonable bursts of traffic for approximately 15-30 minutes.
Lambda can scale faster than the regular Auto Scaling feature of Amazon EC2, Amazon Elastic Beanstalk, or Amazon ECS. This is because AWS Lambda is more lightweight than other computing services. Under the hood, Lambda can run your code to thousands of available AWS-managed EC2 instances (that could already be running) within seconds to accommodate traffic. This is faster than the Auto Scaling process of launching new EC2 instances that could take a few minutes or so. An alternative is to overprovision your compute capacity but that will incur significant costs. The best option to implement given the requirements is a combination of AWS Lambda and Amazon API Gateway.
Hence, the correct answer is: Create an API using Amazon API Gateway and use AWS Lambda to handle the bursts of traffic.
The option that says: Create an API using Amazon API Gateway and use the Amazon ECS cluster with Service Auto Scaling to handle the bursts of traffic in seconds is incorrect. AWS Lambda is a better option than Amazon ECS since it can handle a sudden burst of traffic within seconds and not minutes.
The option that says: Create an API using Amazon API Gateway and use Amazon Elastic Beanstalk with Auto Scaling to handle the bursts of traffic in seconds is incorrect because just like the previous option, the use of Auto Scaling has a delay of a few minutes as it launches new EC2 instances that will be used by Amazon Elastic Beanstalk.
The option that says: Create an API using Amazon API Gateway and use an Auto Scaling group of Amazon EC2 instances to handle the bursts of traffic in seconds is incorrect because the processing time of Amazon EC2 Auto Scaling to provision new resources takes minutes. Take note that in the scenario, a burst of traffic within seconds is expected to happen. References:
https://aws.amazon.com/blogs/startups/from-0-to-100-k-in-seconds-instant-scale-with-aws-lambda/
https://docs.aws.amazon.com/lambda/latest/dg/invocation-scaling.html
Check out this AWS Lambda Cheat Sheet: https://tutorialsdojo.com/aws-lambda/
質問 # 599
A company provides an API to its users that automates inquiries for tax computations based on item prices. The company experiences a larger number of inquiries during the holiday season only that cause slower response times. A solutions architect needs to design a solution that is scalable and elastic.
What should the solutions architect do to accomplish this?
正解：C
解説：
Lambda server-less is scalable and elastic than EC2 api gateway solution
質問 # 600
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