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NEW QUESTION: 1
A provider core consists of 4 PE and 2 P routers. A fully meshed VPRN service is configured on all 4 PEs, and MPLS LSP-based SDPs are used for the service configuration. How many SDPs must be bound to the VPRN service on each PE?
A. Two SDPs must be bound to the VPRN service on each PE.
B. Five SDPs must be bound to the VPRN service on each PE.
C. Twelve SDPs must be bound to the VPRN service on each PE.
D. Three SDPs must be bound to the VPRN service on each PE.
Answer: D

NEW QUESTION: 2
A company ingests and processes streaming market data. The data rate is constant. A nightly process that calculates aggregate statistics is run, and each execution takes about 4 hours to complete. The statistical analysis is not mission critical to the business, and previous data points are picked up on the next execution if a particular run fails.
The current architecture uses a pool of Amazon EC2 Reserved Instances with 1-year reservations running full time to ingest and store the streaming data in attached Amazon EBS volumes. On-Demand EC2 instances are launched each night to perform the nightly processing, accessing the stored data from NFS shares on the ingestion servers, and terminating the nightly processing servers when complete. The Reserved Instance reservations are expiring, and the company needs to determine whether to purchase new reservations or implement a new design.
Which is the most cost-effective design?
A. Update the ingestion process to use Amazon Kinesis Data Firehouse to save data to Amazon S3. Use AWS Batch to perform nightly processing with a Spot market bid of 50% of the On-Demand price.
B. Update the ingestion process to use Amazon Kinesis Data Firehose to save data to Amazon S3. Use a fleet of On-Demand EC2 instances that launches each night to perform the batch processing of the S3 data and terminates when the processing completes.
C. Update the ingestion process to use a fleet of EC2 Reserved Instances behind a Network Load Balancer with 3-year leases. Use Batch with Spot instances with a maximum bid of 50% of the On-Demand price for the nightly processing.
D. Update the ingestion process to use Amazon Kinesis Data Firehose to save data to Amazon Redshift.
Use an AWS Lambda function scheduled to run nightly with Amazon CloudWatch Events to query Amazon Redshift to generate the daily statistics.
Answer: A
Explanation:
Explanation
https://www.simform.com/aws-lambda-vs-ec2/
https://aws.amazon.com/about-aws/whats-new/2018/10/aws-lambda-supports-functions-that-can-run-up-to-15-m
https://aws.amazon.com/batch/faqs/?nc=sn&loc=5

NEW QUESTION: 3
You are selecting services to write and transform JSON messages from Cloud Pub/Sub to BigQuery for a data pipeline on Google Cloud. You want to minimize service costs. You also want to monitor and accommodate input data volume that will vary in size with minimal manual intervention. What should you do?
A. Use Cloud Dataproc to run your transformations. Use the diagnose command to generate an operational output archive. Locate the bottleneck and adjust cluster resources.
B. Use Cloud Dataproc to run your transformations. Monitor CPU utilization for the cluster. Resize the number of worker nodes in your cluster via the command line.
C. Use Cloud Dataflow to run your transformations. Monitor the total execution time for a sampling of jobs.
Configure the job to use non-default Compute Engine machine types when needed.
D. Use Cloud Dataflow to run your transformations. Monitor the job system lag with Stackdriver. Use the default autoscaling setting for worker instances.
Answer: D
Explanation:
Dataflow is good with autoscaling and stackdriver to monitor CPU and Storage.

NEW QUESTION: 4
Which option can be used to provide a nonproprietary method of load balancing and redundancy between the access and aggregation layers in the data canter?
A. vPC
B. LACP
C. host vPC
D. PAgP
Answer: B