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Which can be Scaled independently of the number of CPUs in an Autonomous Database?
Correct Answer: A
Recent Comments (The most recent comments are at the top.)
Burak Yoleri - May 09, 2020
The answer is D. You simply specify the number of OCPUs and the storage capacity in TB's for the database. At any time, you may scale, increase or decrease either the OCPUs or the storage capacity.
Let's see how to start and stop and scale an Autonomous Database. The Autonomous Database Instance can be scaled on demand without tedious, manual steps. Autonomous Database allows for independently scaling of compute or storage, resizing occurs instantly, fully online, memory IO bandwidth concurrency scales linearly with CPU, so when CPUs are scaled, the system automatically adjusts other resources to match, stopping an instance on demand to conserve resources, starting an instance on demand. Starting, stopping, and scaling can be done by clicking through the console. See examples in the following slides or through API calls, such as will be covered in the next module.
To scale the Autonomous Database from the console, select the database to be scaled. This will place you in the database console. Select scale up or down button. The scaling window appears. In the CPU count box, enter the number of CPUs you want provisioned in your environment. The default entry has the current value of CPUs provisioned on the environment. In this case, there is one CPU provisioned. So, in this example, we scaled the database up to four CPUs.
You can also scale the storage in terabytes of database space allocated by updating the storage parameter. When the parameters are updated, select Update. And you will be placed back on the database console where the database will show as Scaling in Progress. Please notice that the color of the database icon remains green because database scaling operations do not require system outages. When the scaling is complete, the status will change to Available, and the CPU core count will be updated to the selected CPU account during the scaling process.
Recent Comments (The most recent comments are at the top.)
The answer is D. You simply specify the number of OCPUs and the storage capacity in TB's for the database. At any time, you may scale, increase or decrease either the OCPUs or the storage capacity.
https://www.oracle.com/database/technologies/datawarehouse-bigdata/adb-faqs.html
Is correct D.
Let's see how to start and stop and scale an Autonomous Database. The Autonomous Database Instance can be scaled on demand without tedious, manual steps. Autonomous Database allows for independently scaling of compute or storage, resizing occurs instantly, fully online, memory IO bandwidth concurrency scales linearly with CPU, so when CPUs are scaled, the system automatically adjusts other resources to match, stopping an instance on demand to conserve resources, starting an instance on demand. Starting, stopping, and scaling can be done by clicking through the console. See examples in the following slides or through API calls, such as will be covered in the next module.
To scale the Autonomous Database from the console, select the database to be scaled. This will place you in the database console. Select scale up or down button. The scaling window appears. In the CPU count box, enter the number of CPUs you want provisioned in your environment. The default entry has the current value of CPUs provisioned on the environment. In this case, there is one CPU provisioned. So, in this example, we scaled the database up to four CPUs.
You can also scale the storage in terabytes of database space allocated by updating the storage parameter. When the parameters are updated, select Update. And you will be placed back on the database console where the database will show as Scaling in Progress. Please notice that the color of the database icon remains green because database scaling operations do not require system outages. When the scaling is complete, the status will change to Available, and the CPU core count will be updated to the selected CPU account during the scaling process.