Exam Professional Cloud Architect topic 1 question 19 discussion

Answer is C because persistent disk performance is based on the total persistent disk capacity attached to an instance and the number of vCPUs that the instance has. Incrementing the persistent disk capacity will increment its throughput and IOPS, which in turn improve the performance of MySQL.

Assuming that the database is approaching its hardware limits... both options A and C would improve performance, A would increase number of CPUs and memory, but C would increase memory by more. If it a software problem, it is likly it is a hashing problem (the search and sort algorithms are not specific enough to search within the database). This problem would not be fixed just by migrating to PostgreSQL or BigQuery but modifying the inserts would help the situation because it would entail specifications of data lookups. However, it wouldn't help with search performance just inserts and it doesn't help in normalization. So B, D, and E are eliminated. Since statistics is based on sets, the larger the number of sets the better the predictions. This means that the largest amount of memory would not only increase computer performance but also knowledge enhancements. So C beats A.

OLTP D/B performance is depended on IOPs. SSD is the best solution for higher IOPs. In GCP bigger the disk size higher the IOPs.

Choose C

increase size will not increase performance, it either increase RAM or serverless. A or D. if no cost concern will pick D

I was looking for CloudSQL in options, since it is not there, C is best

The fact that the database is used for importing and normalizing performance statistics suggests frequent data insertions. Optimizing this process through bulk inserts directly addresses a likely performance bottleneck.

The answer according to Google is A. This question is part of the Google's sample questions for the certification.

I see most of the people here replying C, but I do not think that the size of the disk we bring much gains in performance. D, yes, seems to me that will bring much improvements in performance, management, operations and cost. So B, Migrate their performance metrics warehouse to BigQuery

I would go with option E because Bulk Insert improves performance drastically unless it is been implemented already.

Increasing disk size will also increase its performance. https://cloud.google.com/compute/docs/disks/performance#optimize_disk_performance

C. Dynamically resize the SSD persistent disk to 500 GB By increasing the size of the SSD persistent disk, the database server can achieve better performance. A larger SSD persistent disk provides higher IOPS (input/output operations per second) and throughput, allowing for faster read and write operations. This can help improve the performance of the MySQL database server running on the Google Compute Engine instance.

On another website I found the question with the hint "you are not allowed to reboot the VM before next maintenance window". That makes it more clear --> C.

E. Modify all of their batch jobs to use bulk inserts into the database: This can be a very effective solution for improving performance. Bulk inserts can greatly reduce the number of round-trips to the database, which can help to minimize latency and improve overall throughput. Therefore, option E is the best choice for improving performance in this scenario.

in option C - even increasing disc can gain performance - that will take few months to face new limits. mySQL is not desiged for OLAP/analytics - but OLTP. so I vote on D

Correct answer is C. Increased disk capacity improved I/O and direct impacts the performance

C, because... N1 8cpu max IOPS = 15,000 https://cloud.google.com/compute/docs/disks/performance#n1_vms SSD persistent disks can reach up to 30 IOPS per GB of disk. https://cloud.google.com/compute/docs/disks/performance#example 80 GB X 30 IOPS = 2,400 IOPS 500 GB (answer C) X 30 IOPS = 15,000 IOPS = N1 8 cpu max IOPS