Topic 1 Question 196
Your company wants to migrate their 10-TB on-premises database export into Cloud Storage. You want to minimize the time it takes to complete this activity and the overall cost. The bandwidth between the on-premises environment and Google Cloud is 1 Gbps. You want to follow Google-recommended practices. What should you do?
Develop a Dataflow job to read data directly from the database and write it into Cloud Storage.
Use the Data Transfer appliance to perform an offline migration.
Use a commercial partner ETL solution to extract the data from the on-premises database and upload it into Cloud Storage.
Upload the data with gcloud storage cp.
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コメント(17)
- 正解だと思う選択肢: D
This Transfer Appliance docs says it is suitable when "It would take more than one week to upload your data over the network" Since 10TB would take way less than a week for that bandwidth, I would go for D https://cloud.google.com/transfer-appliance/docs/4.0/overview#suitability
👍 6cchiaramelli2023/10/29 Vote D. The bandwidth is 1 Gbps. It will only take less than 3 hours to complete the upload of 10TB data by using copy command. The Data Transfer appliance can take several days to weeks. The question ask to minimize the time and the overall cost, so D is suitable.
👍 4sheucm892023/09/25- 正解だと思う選択肢: B
option B (Use the Data Transfer appliance to perform an offline migration) seems to be the most appropriate. It addresses the need for a speedy transfer of a large amount of data and is a cost-effective solution recommended by Google for large-scale data migrations. This option circumvents potential network bandwidth limitations and provides a reliable way to transfer large datasets.
Why option D is not a good choice : D. Upload the data with gcloud storage cp: This method uses the gcloud command-line tool to copy files to Cloud Storage. While simple, it might not be the most efficient for a 10-TB migration given the 1 Gbps bandwidth. The process could be slow and may require additional handling for potential interruptions and resuming uploads.
👍 4Nora92023/11/16
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