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Certifications: Amazon Specialty
Exam Name: AWS Advanced Networking Specialty
Exam Code: AWS-Certified-Advanced-Networking-Specialty
Total Questions: 90
♥ 2018 Valid AWS-Certified-Advanced-Networking-Specialty Exam Questions ♥
AWS-Certified-Advanced-Networking-Specialty exam questions, AWS-Certified-Advanced-Networking-Specialty PDF dumps; AWS-Certified-Advanced-Networking-Specialty exam dumps:: https://www.dumpsschool.com/AWS-Certified-Advanced-Networking-Specialty-exam-dumps.html (90 Q&A) (New Questions Are 100% Available! Also Free Practice Test Software!)
Latest and Most Accurate Amazon AWS-Certified-Advanced-Networking-Specialty Dumps Exam Questions and Answers:
You are responsible for a legacy web application whose server environment is approaching end of life You would like to migrate this application to AWS as quickly as possible, since the application environment currently has the following limitations:
The VM’s single 10GB VMDK is almost full
Me virtual network interface still uses the 10Mbps driver, which leaves your 100Mbps WAN connection completely underutilized
It is currently running on a highly customized. Windows VM within a VMware environment:
You do not have me installation media
This is a mission critical application with an RTO (Recovery Time Objective) of 8 hours. RPO (Recovery Point Objective) of 1 hour. How could you best migrate this application to AWS while meeting your business continuity requirements?
A. Use the EC2 VM Import Connector for vCenter to import the VM into EC2.
B. Use Import/Export to import the VM as an ESS snapshot and attach to EC2.
C. Use S3 to create a backup of the VM and restore the data into EC2.
D. Use me ec2-bundle-instance API to Import an Image of the VM into EC2
An International company has deployed a multi-tier web application that relies on DynamoDB in a single region For regulatory reasons they need disaster recovery capability In a separate region with a Recovery Time Objective of 2 hours and a Recovery Point Objective of 24 hours They should synchronize their data on a regular basis and be able to provision me web application rapidly using CloudFormation.
The objective is to minimize changes to the existing web application, control the throughput of DynamoDB used for the synchronization of data and synchronize only the modified elements.
Which design would you choose to meet these requirements?
A. Use AWS data Pipeline to schedule a DynamoDB cross region copy once a day. create a Lastupdated’ attribute in your DynamoDB table that would represent the timestamp of the last update and use it as a filter.
B. Use EMR and write a custom script to retrieve data from DynamoDB in the current region using a SCAN operation and push it to DynamoDB in the second region.
C. Use AWS data Pipeline to schedule an export of the DynamoDB table to S3 in the current region once a day then schedule another task immediately after it that will import data from S3 to DynamoDB in the other region.
D. Send also each Ante into an SQS queue in me second region; use an auto-scaling group behind the SQS queue to replay the write in the second region.
Refer to the architecture diagram above of a batch processing solution using Simple Queue Service (SQS) to set up a message queue between EC2 instances which are used as batch processors Cloud Watch monitors the number of Job requests (queued messages) and an Auto Scaling group adds or deletes batch servers automatically based on parameters set in Cloud Watch alarms. You can use this architecture to implement which of the following features in a cost effective and efficient manner?
A. Reduce the overall lime for executing jobs through parallel processing by allowing a busy EC2 instance that receives a message to pass it to the next instance in a daisy-chain setup.
B. Implement fault tolerance against EC2 instance failure since messages would remain in SQS and worn can continue with recovery of EC2 instances implement fault tolerance against SQS failure by backing up messages to S3.
C. Implement message passing between EC2 instances within a batch by exchanging messages through SQS.
D. Coordinate number of EC2 instances with number of job requests automatically thus Improving cost effectiveness.
E. Handle high priority jobs before lower priority jobs by assigning a priority metadata field to SQS messages.
There are cases where a large number of batch jobs may need processing, and where the the jobs may need to be re-prioritized.
For example, one such case is one where there are differences between different levels of services for unpaid users versus subscriber users (such as the time until publication) in services enabling, for example, presentation files to be uploaded for publication from a web browser. When the user uploads a presentation file, the conversion processes, for example, for publication are performed as batch processes on the system side, and the file is published after the conversion. Is it then necessary to be able to assign the level of priority to the batch processes for each type of subscriber.
Explanation of the Cloud Solution/Pattern
A queue is used in controlling batch jobs. The queue need only be provided with priority numbers. Job requests are controlled by the queue, and the job requests in the queue are processed by a batch server. In Cloud computing, a highly reliable queue is provided as a service, which you can use to structure a highly reliable batch system with ease. You may prepare multiple queues depending on priority levels, with job requests put into the queues depending on their priority levels, to apply prioritization to batch processes. The performance (number) of batch servers corresponding to a queue must be in accordance with the priority level thereof.
In AWS, the queue service is the Simple Queue Service (SQS). Multiple SQS queues may be prepared to prepare queues for individual priority levels (with a priority queue and a secondary queue). Moreover, you may also use the message Delayed Send function to delay process execution.
Use SQS to prepare multiple queues for the individual priority levels.
Place those processes to be executed immediately (job requests) in the high priority queue.
Prepare numbers of batch servers, for processing the job requests of the queues, depending on the priority levels.
Queues have a message “Delayed Send” function. You can use this to delay the time for starting a process.
You can increase or decrease the number of servers for processing jobs to change automatically the processing speeds of the priority queues and secondary queues.
You can handle performance and service requirements through merely increasing or decreasing the number of EC2 instances used in job processing.
Even if an EC2 were to fail, the messages (jobs) would remain in the queue service, enabling processing to be continued immediately upon recovery of the EC2 instance, producing a system that is robust to failure.
Depending on the balance between the number of EC2 instances for performing the processes and the number of messages that are queued, there may be cases where processing in the secondary queue may be completed first, so you need to monitor the processing speeds in the primary queue and the secondary queue.
Your company currently has a 2-tier web application running in an on-premises data center. You have experienced several infrastructure failures in the past two months resulting in significant financial losses. Your CIO is strongly agreeing to move the application to AWS. While working on achieving buy-in from the other company executives, he asks you to develop a disaster recovery plan to help improve Business continuity in the short term. He specifies a target Recovery Time Objective (RTO) of 4 hours and a Recovery Point Objective (RPO) of 1 hour or less. He also asks you to implement the solution within 2 weeks. Your database is 200GB in size and you have a 20Mbps Internet connection. How would you do this while minimizing costs?
A. Create an EBS backed private AMI which includes a fresh install of your application. Develop a CloudFormation template which includes your AMI and the required EC2, AutoScaling, and ELB resources to support deploying the application across Multiple- Availability-Zones. Asynchronously replicate transactions from your on-premises database to a database instance in AWS across a secure VPN connection.
B. Deploy your application on EC2 instances within an Auto Scaling group across multiple availability zones. Asynchronously replicate transactions from your on-premises database to a database instance in AWS across a secure VPN connection.
C. Create an EBS backed private AMI which includes a fresh install of your application. Setup a script in your data center to backup the local database every 1 hour and to encrypt and copy the resulting file to an S3 bucket using multi-part upload.
D. Install your application on a compute-optimized EC2 instance capable of supporting the application’s average load. Synchronously replicate transactions from your on-premises database to a database instance in AWS across a secure Direct Connect connection.
Overview of Creating Amazon EBS-Backed AMIs
First, launch an instance from an AMI that’s similar to the AMI that you’d like to create. You can connect to your instance and customize it. When the instance is configured correctly, ensure data integrity by stopping the instance before you create an AMI, then create the image. When you create an Amazon EBS-backed AMI, we automatically register it for you.
Amazon EC2 powers down the instance before creating the AMI to ensure that everything on the instance is stopped and in a consistent state during the creation process. If you’re confident that your instance is in a consistent state appropriate for AMI creation, you can tell Amazon EC2 not to power down and reboot the instance. Some file systems, such as XFS, can freeze and unfreeze activity, making it safe to create the image without rebooting the instance.
During the AMI-creation process, Amazon EC2 creates snapshots of your instance’s root volume and any other EBS volumes attached to your instance. If any volumes attached to the instance are encrypted, the new AMI only launches successfully on instances that support Amazon EBS encryption. For more information, see Amazon EBS Encryption.
Depending on the size of the volumes, it can take several minutes for the AMI-creation process to complete (sometimes up to 24 hours).You may find it more efficient to create snapshots of your volumes prior to creating your AMI. This way, only small, incremental snapshots need to be created when the AMI is created, and the process completes more quickly (the total time for snapshot creation remains the same). For more information, see Creating an Amazon EBS Snapshot.
After the process completes, you have a new AMI and snapshot created from the root volume of the instance. When you launch an instance using the new AMI, we create a new EBS volume for its root volume using the snapshot. Both the AMI and the snapshot incur charges to your account until you delete them. For more information, see Deregistering Your AMI.
If you add instance-store volumes or EBS volumes to your instance in addition to the root device volume, the block device mapping for the new AMI contains information for these volumes, and the block device mappings for instances that you launch from the new AMI automatically contain information for these volumes. The instance-store volumes specified in the block device mapping for the new instance are new and don’t contain any data from the instance store volumes of the instance you used to create the AMI. The data on EBS volumes persists. For more information, see Block Device Mapping.
An ERP application is deployed across multiple AZs in a single region. In the event of failure, the Recovery Time Objective (RTO) must be less than 3 hours, and the Recovery Point Objective (RPO) must be 15 minutes the customer realizes that data corruption occurred roughly 1.5 hours ago.
What DR strategy could be used to achieve this RTO and RPO in the event of this kind of failure?
A. Take hourly DB backups to S3, with transaction logs stored in S3 every 5 minutes.
B. Use synchronous database master-slave replication between two availability zones.
C. Take hourly DB backups to EC2 Instance store volumes with transaction logs stored In S3 every 5 minutes.
D. Take 15 minute DB backups stored In Glacier with transaction logs stored in S3 every 5 minutes.
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