- (Exam Topic 5)
A production database virtual machine on Google Compute Engine has an ext4-formatted persistent disk for data files The database is about to run out of storage space How can you remediate the problem with the least amount of downtime?

1. A. In the Cloud Platform Console, increase the size of the persistent disk and use the resize2fs command in Linux.
2. B. Shut down the virtual machine, use the Cloud Platform Console to increase the persistent disk size, then restart the virtual machine.
3. C. In the Cloud Platform Console, increase the size of the persistent disk and verify the new space is ready to use with the fdisk command in Linux.
4. D. In the Cloud Platform Console, create a new persistent disk attached to the virtual machine, format and mount it, and configure the database service to move the files to the new disk.
5. E. In the Cloud Platform Console, create a snapshot of the persistent disk, restore the snapshot to a new larger disk, unmount the old disk, mount the new disk, and restart the database service.

Correct Answer: A
On Linux instances, connect to your instance and manually resize your partitions and file systems to use the additional disk space that you added.
Extend the file system on the disk or the partition to use the added space. If you grew a partition on your disk, specify the partition. If your disk does not have a partition table, specify only the disk ID.
sudo resize2fs /dev/[DISK_ID][PARTITION_NUMBER]
where [DISK_ID] is the device name and [PARTITION_NUMBER] is the partition number for the device where you are resizing the file system.
References: https://cloud.google.com/compute/docs/disks/add-persistent-disk

- (Exam Topic 5)
Your company wants to start using Google Cloud resources but wants to retain their on-premises Active Directory domain controller for identity management. What should you do?

1. A. Use the Admin Directory API to authenticate against the Active Directory domain controller.
2. B. Use Google Cloud Directory Sync to synchronize Active Directory usernames with cloud identities and configure SAML SSO.
3. C. Use Cloud Identity-Aware Proxy configured to use the on-premises Active Directory domain controller as an identity provider.
4. D. Use Compute Engine to create an Active Directory (AD) domain controller that is a replica of the onpremises AD domain controller using Google Cloud Directory Sync.

Correct Answer: B
https://cloud.google.com/solutions/federating-gcp-with-active-directory-introduction#implementing_federation

- (Exam Topic 5)
One of the developers on your team deployed their application in Google Container Engine with the Dockerfile below. They report that their application deployments are taking too long.

You want to optimize this Dockerfile for faster deployment times without adversely affecting the app’s functionality.
Which two actions should you take? Choose 2 answers.

1. A. Remove Python after running pip.
2. B. Remove dependencies from requirements.txt.
3. C. Use a slimmed-down base image like Alpine linux.
4. D. Use larger machine types for your Google Container Engine node pools.
5. E. Copy the source after the package dependencies (Python and pip) are installed.

Correct Answer: CE
The speed of deployment can be changed by limiting the size of the uploaded app, limiting the complexity of the build necessary in the Dockerfile, if present, and by ensuring a fast and reliable internet connection.
Note: Alpine Linux is built around musl libc and busybox. This makes it smaller and more resource efficient than traditional GNU/Linux distributions. A container requires no more than 8 MB and a minimal installation to disk requires around 130 MB of storage. Not only do you get a fully-fledged Linux environment but a large selection of packages from the repository.
References: https://groups.google.com/forum/#!topic/google-appengine/hZMEkmmObDU https://www.alpinelinux.org/about/

- (Exam Topic 5)
You are moving an application that uses MySQL from on-premises to Google Cloud. The application will run on Compute Engine and will use Cloud SQL. You want to cut over to the Compute Engine deployment of the application with minimal downtime and no data loss to your customers. You want to migrate the application with minimal modification. You also need to determine the cutover strategy. What should you do?

1. A. * 1. Set up Cloud VPN to provide private network connectivity between the Compute Engine application and the on-premises MySQL server.* 2. Stop the on-premises application.* 3. Create a mysqldump of the on-premises MySQL serve
2. B. * 4.Upload the dump to a Cloud Storage bucket.* 5. Import the dump into Cloud SQL.* 6. Modify the source code of the application to write queries to both databases and read from its local database.* 7. Start the Compute Engine applicatio
3. C. 8.Stop the on-premises application.
4. D. * 1. Set up Cloud SQL proxy and MySQL proxy.* 2. Create a mysqldump of the on-premises MySQL serve
5. E. * 3. Upload the dump to a Cloud Storage bucket.* 4. Import the dump into Cloud SQ
6. F. * 5. Stop the on-premises applicatio
7. G. * 6. Start the Compute Engine application.
8. H. * 1. Set up Cloud VPN to provide private network connectivity between the Compute Engine applicationand the on-premises MySQL serve
9. I. * 2. Stop the on-premises application.* 3. Start the Compute Engine application, configured to read and write to the on-premises MySQL serve
10. J. * 4. Create the replication configuration in Cloud SQL.* 5. Configure the source database server to accept connections from the Cloud SQL replic
11. K. * 6. Finalize the Cloud SQL replica configuration.* 7. When replication has been completed, stop the Compute Engine applicatio
12. L. * 8. Promote the Cloud SQL replica to a standalone instance.* 9. Restart the Compute Engine application, configured to read and write to the Cloud SQL standalone instance.
13. M. * 1. Stop the on-premises application.* 2. Create a mysqldump of the on-premises MySQL serve
14. N. * 3. Upload the dump to a Cloud Storage bucket.* 4. Import the dump into Cloud SQL.* 5. Start the application on Compute Engine.

Correct Answer: C
External replica promotion migration In the migration strategy of external replica promotion, you create an external database replica and synchronize the existing data to that replica. This can happen with minimal downtime to the existing database. When you have a replica database, the two databases have different roles that are referred to in this document as primary and replica. After the data is synchronized, you promote the replica to be the primary in order to move the management layer with minimal impact to database uptime. In Cloud SQL, an easy way to accomplish the external replica promotion is to use the automated migration workflow. This process automates many of the steps that are needed for this type of migration.
https://cloud.google.com/architecture/migrating-mysql-to-cloudsql-concept
- The best option for migrating your MySQL database is to use an external replica promotion. In this strategy, you create a replica database and set your existing database as the primary. You wait until the two databases are in sync, and you then promote your MySQL replica database to be the primary. This process minimizes database downtime related to the database migration. https://cloud.google.com/architecture/migrating-mysql-to-cloudsql-concept#external_replica_promotion_migrat

- (Exam Topic 5)
Your company has successfully migrated to the cloud and wants to analyze their data stream to optimize operations. They do not have any existing code for this analysis, so they are exploring all their options. These options include a mix of batch and stream processing, as they are running some hourly jobs and
live-processing some data as it comes in. Which technology should they use for this?

1. A. Google Cloud Dataproc
2. B. Google Cloud Dataflow
3. C. Google Container Engine with Bigtable
4. D. Google Compute Engine with Google BigQuery

Correct Answer: B
Dataflow is for processing both the Batch and Stream.
Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or compromises needed.
References: https://cloud.google.com/dataflow/