The database administration team has asked you to help them improve the performance of their new database server running on Google Compute Engine. The database is for importing and normalizing their performance statistics and is built with MySQL running on Debian Linux. They have an n1-standard-8 virtual machine with 80 GB of SSD persistent disk.
What should they change to get better performance from this system?
To improve the performance of the MySQL database running on Google Compute Engine, dynamically resizing the SSD persistent disk to 500 GB is a practical solution. Increasing the size of SSD persistent disk directly enhances its throughput and IOPS (input/output operations per second). With higher IOPS, the database can handle read and write operations more efficiently, leading to better performance. This change does not require VM downtime, making it a seamless improvement.
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.
C is ok.
Also, if you increased the memory size, it would not be a n1-standard-8 anymore. You should eventually change machine type, not simply increase memory.
C. universal truth - 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.
When you increase the memory yo need to shutdown the machine, but when you increase the disk, it is not necessary. Answer is B.
I wanted to put letter C.
there isn't "without downtime"
Since its using SQL, so there will be a Maintenance Window, so this change can be implemented during the downtime( also there is no mention that the system should be always avaliable)
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
adding memory to VM will need to be shut down which means the business will be impacted, not good for any option remember this for your exam
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
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.
Increasing disk size will also increase its performance. https://cloud.google.com/compute/docs/disks/performance#optimize_disk_performance
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
C. Dynamically resize the SSD persistent disk to 500 GB
Correct answer is C. Increased disk capacity improved I/O and direct impacts the performance
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.
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.
I would go with option E because Bulk Insert improves performance drastically unless it is been implemented already.
The answer according to Google is A. This question is part of the Google's sample questions for the certification.
Yes, it is, and says it is C.
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.
I was looking for CloudSQL in options, since it is not there, C is best
increase size will not increase performance, it either increase RAM or serverless. A or D. if no cost concern will pick D