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NEW QUESTION # 654
A company hostss a three application on Amazon EC2 instances in a single Availability Zone. The web application uses a self-managed MySQL database that is hosted on an EC2 instances to store data in an Amazon Elastic Block Store (Amazon EBS) volumn. The MySQL database currently uses a 1 TB Provisioned IOPS SSD (io2) EBS volume. The company expects traffic of 1,000 IOPS for both reads and writes at peak traffic.
The company wants to minimize any distruptions, stabilize perperformace, and reduce costs while retaining the capacity for double the IOPS. The company wants to more the database tier to a fully managed solution that is highly available and fault tolerant.
Which solution will meet these requirements MOST cost-effectively?
Answer: B
Explanation:
RDS supported Storage > https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html GP2 max IOPS > https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/general-purpose.html#gp2- performance Amazon RDS provides three storage types: General Purpose SSD (also known as gp2 and gp3), Provisioned IOPS SSD (also known as io1), and magnetic (also known as standard). They differ in performance characteristics and price, which means that you can tailor your storage performance and cost to the needs of your database workload. You can create MySQL, MariaDB, Oracle, and PostgreSQL RDS DB instances with up to 64 tebibytes (TiB) of storage. You can create SQL Server RDS DB instances with up to 16 TiB of storage. For this amount of storage, use the Provisioned IOPS SSD and General Purpose SSD storage types.
https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html
NEW QUESTION # 655
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?
Answer: D
Explanation:
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. 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.
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/
NEW QUESTION # 656
A company is creating a prototype of an ecommerce website on AWS. The website consists of an Application Load Balancer, an Auto Scaling group of Amazon EC2 instances for web servers, and an Amazon RDS for MySQL DB instance that runs with the Single-AZ configuration.
The website is slow to respond during searches of the product catalog. The product catalog is a group of tables in the MySQL database that the company does not ate frequently. A solutions architect has determined that the CPU utilization on the DB instance is high when product catalog searches occur.
What should the solutions architect recommend to improve the performance of the website dunng searches of the product catalog?
Answer: D
Explanation:
* Requirement Analysis: The product catalog search is causing high CPU utilization on the MySQL DB instance, slowing down the website.
* ElastiCache Overview: Amazon ElastiCache for Redis can be used to cache frequently accessed data, reducing load on the database.
* Lazy Loading: This caching strategy loads data into the cache only when it is requested, improving response times for repeated queries.
* Implementation:
* Set up an ElastiCache for Redis cluster.
* Modify the application to check the cache before querying the database.
* Use lazy loading to populate the cache on cache misses.
* Conclusion: This approach reduces database load and improves website performance during product catalog searches.
References
* Amazon ElastiCache: ElastiCache Documentation
* Caching Strategies: ElastiCache Caching Strategies
NEW QUESTION # 657
A company runs a high performance computing (HPC) workload on AWS. The workload required low-latency network performance and high network throughput with tightly coupled node-to-node communication. The Amazon EC2 instances are properly sized for compute and storage capacity, and are launched using default options.
What should a solutions architect propose to improve the performance of the workload?
Answer: B
Explanation:
Explanation
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-ec2-placementgroup.html
"A cluster placement group is a logical grouping of instances within a single Availability Zone that benefit from low network latency, high network throughput"
NEW QUESTION # 658
A gaming company is moving its public scoreboard from a data center to the AWS Cloud. The company uses Amazon EC2 Windows Server instances behind an Application Load Balancer to host its dynamic application. The company needs a highly available storage solution for the application. The application consists of static files and dynamic server-side code.
Which combination of steps should a solutions architect take to meet these requirements? (Select TWO.)
Answer: B,C
Explanation:
A because Elasticache, despite being ideal for leaderboards per Amazon, doesn't cache at edge locations. D because FSx has higher performance for low latency needs.
https://www.techtarget.com/searchaws/tip/Amazon-FSx-vs-EFS-Compare-the-AWS-file-services "FSx is built for high performance and submillisecond latency using solid-state drive storage volumes. This design enables users to select storage capacity and latency independently. Thus, even a subterabyte file system can have 256 Mbps or higher throughput and support volumes up to 64 TB." Amazon S3 is an object storage service that can store static files such as images, videos, documents, etc.
Amazon EFS is a file storage service that can store files in a hierarchical structure and supports NFS protocol.
Amazon FSx for Windows File Server is a file storage service that can store files in a hierarchical structure and supports SMB protocol. Amazon EBS is a block storage service that can store data in fixed-size blocks and attach to EC2 instances.
Based on these definitions, the combination of steps that should be taken to meet the requirements are:
A: Store the static files on Amazon S3. Use Amazon CloudFront to cache objects at the edge. D. Store the server-side code on Amazon FSx for Windows File Server. Mount the FSx for Windows File Server volume on each EC2 instance to share the files.
NEW QUESTION # 659
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