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The application reliability team at your company has added a debug feature to their backend service to send all server events to Google Cloud Storage for eventual analysis. The event records are at least 50 KB and at most 15 MB and are expected to peak at 3,000 events per second. You want to minimize data loss.Which process should you implement?
A. • Append metadata to file body.• Compress individual files.• Name files with serverName-Timestamp.• Create a new bucket if bucket is older than 1 hour and save individual files to the new bucket. Otherwise, save files to existing bucket
B. • Batch every 10,000 events with a single manifest file for metadata.• Compress event files and manifest file into a single archive file.• Name files using serverName-EventSequence.• Create a new bucket if bucket is older than 1 day and save the single archive file to the new bucket. Otherwise, save the single archive file to existing bucket.
C. • Compress individual files.• Name files with serverName-EventSequence.• Save files to one bucket• Set custom metadata headers for each object after saving.
D. • Append metadata to file body.• Compress individual files.• Name files with a random prefix pattern.• Save files to one bucket
Your application needs to process credit card transactions. You want the smallest scope of Payment Card Industry (PCI) compliance without compromising the ability to analyze transactional data and trends relating to which payment methods are used. How should you design your architecture?
A. Create a tokenizer service and store only tokenized data.
B. Create separate projects that only process credit card data.
C. Create separate subnetworks and isolate the components that process credit card data.
D. Streamline the audit discovery phase by labeling all of the virtual machines (VMs) that process PCI data.
E. Enable Logging export to Google BigQuery and use ACLs and views to scope the data shared with the auditor.
Your solution is producing performance bugs in production that you did not see in staging and test environments. You want to adjust your test and deployment procedures to avoid this problem in the future. What should you do?
A. Deploy fewer changes to production.
B. Deploy smaller changes to production.
C. Increase the load on your test and staging environments.
D. Deploy changes to a small subset of users before rolling out to production.
You need to develop procedures to verify resilience of disaster recovery for remote recovery using GCP. Your production environment is hosted on-premises. You need to establish a secure, redundant connection between your on premises network and the GCP network.What should you do?
A. Verify that Dedicated Interconnect can replicate files to GCP. Verify that direct peering can establish a secure connection between your networks if Dedicated Interconnect fails.
B. Verify that Dedicated Interconnect can replicate files to GCP. Verify that Cloud VPN can establish a secure connection between your networks if Dedicated Interconnect fails.
C. Verify that the Transfer Appliance can replicate files to GCP. Verify that direct peering can establish a secure connection between your networks if the Transfer Appliance fails.
D. Verify that the Transfer Appliance can replicate files to GCP. Verify that Cloud VPN can establish a secure connection between your networks if the Transfer Appliance fails.
Your company captures all web traffic data in Google Analytics 260 and stores it in BigQuery. Each country has its own dataset. Each dataset has multiple tables. You want analysts from each country to be able to see and query only the data for their respective countries.How should you configure the access rights?
A. Create a group per country. Add analysts to their respective country-groups. Create a single group ‘all_analysts’, and add all country-groups as members. Grant the ‘all-analysis’ group the IAM role of BigQuery jobUser. Share the appropriate dataset with view access with each respective analyst countrygroup.
B. Create a group per country. Add analysts to their respective country-groups. Create a single group ‘all_analysts’, and add all country-groups as members. Grant the ‘all-analysis’ group the IAM role of BigQuery jobUser. Share the appropriate tables with view access with each respective analyst countrygroup.
C. Create a group per country. Add analysts to their respective country-groups. Create a single group ‘all_analysts’, and add all country-groups as members. Grant the ‘all-analysis’ group the IAM role of BigQuery dataViewer. Share the appropriate dataset with view access with each respective analyst country-group.
D. Create a group per country. Add analysts to their respective country-groups. Create a single group ‘all_analysts’, and add all country-groups as members. Grant the ‘all-analysis’ group the IAM role of BigQuery dataViewer. Share the appropriate table with view access with each respective analyst countrygroup.
Your company places a high value on being responsive and meeting customer needs quickly. Their primary business objectives are release speed and agility. You want to reduce the chance of security errors being accidentally introduced. Which two actions can you take? Choose 2 answers
A. Ensure every code check-in is peer reviewed by a security SME.
B. Use source code security analyzers as part of the CI/CD pipeline.
C. Ensure you have stubs to unit test all interfaces between components.
D. Enable code signing and a trusted binary repository integrated with your CI/CD pipeline.
E. Run a vulnerability security scanner as part of your continuous-integration /continuous-delivery (CI/CD) pipeline.
To reduce costs, the Director of Engineering has required all developers to move their development infrastructure resources from on-premises virtual machines (VMs) to Google Cloud Platform. These resources go through multiple start/stop events during the day and require state to persist. You have been asked to design the process of running a development environment in Google Cloud while providing cost visibility to the finance department. Which two steps should you take? Choose 2 answers
A. Use the --no-auto-delete flag on all persistent disks and stop the VM.
B. Use the -auto-delete flag on all persistent disks and terminate the VM.
C. Apply VM CPU utilization label and include it in the BigQuery billing export.
D. Use Google BigQuery billing export and labels to associate cost to groups.
E. Store all state into local SSD, snapshot the persistent disks, and terminate the VM.
F. Store all state in Google Cloud Storage, snapshot the persistent disks, and terminate the VM.
A recent audit that a new network was created in Your GCP project. In this network, a GCE instance has an SSH port open the world. You want to discover this network's origin. What should you do?
A. Search for Create VM entry in the Stackdriver alerting console.
B. Navigate to the Activity page in the Home section. Set category to Data Access and search for Create VM entry.
C. In the logging section of the console, specify GCE Network as the logging section. Search for the Create Insert entry.
D. Connect to the GCE instance using project SSH Keys. Identify previous logins in system logs, and match these with the project owners list.
Auditors visit your teams every 12 months and ask to review all the Google Cloud Identity and Access Management (Cloud IAM) policy changes in the previous 12 months. You want to streamline and expedite the analysis and audit process. What should you do?
A. Create custom Google Stackdriver alerts and send them to the auditor.
B. Enable Logging export to Google BigQuery and use ACLs and views to scope the data shared with the auditor.
C. Use cloud functions to transfer log entries to Google Cloud SQL and use ACLS and views to limit an auditor's view.
D. Enable Google Cloud Storage (GCS) log export to audit logs Into a GCS bucket and delegate access to the bucket.
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?
A. Google Cloud Dataproc
B. Google Cloud Dataflow
C. Google Container Engine with Bigtable
D. Google Compute Engine with Google BigQuery