You support a user-facing web application When analyzing the application's error budget over the previous six months you notice that the application never consumed more than 5% of its error budget You hold a SLO review with business stakeholders and confirm that the SLO is set appropriately You want your application's reliability to more closely reflect its SLO What steps can you take to further that goal while balancing velocity, reliability, and business needs?
Choose 2 answers

• A. Implement and measure all other available SLIs for the application
• B. Tighten the SLO to match the application's observed reliability
• C. Add more serving capacity to all of your application's zones
• D. Have more frequent or potentially risky application releases
• E. Announce planned downtime to consume more error budget and ensure that users are not depending on a tighter SLO

Your team is building a service that performs compute-heavy processing on batches of data The data is processed faster based on the speed and number of CPUs on the machine These batches of data vary in size and may arrive at any time from multiple third-party sources You need to ensure that third partiesare able to upload their data securely. You want to minimize costs while ensuring that the data is processed as quickly as possible What should you do?

• A. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provideappropriate Identity and Access Management (1AM) access to the bucket* Use a standard Google Kubernetes Engine (GKE) cluster and maintain two services one that processes the batches of data and one that monitors Cloud Storage for new batches of data* Stop the processing service when there are no batches of data to process
• B. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate identity and Access Management (1AM) access to the bucket* Create a Cloud Function with a google, storage, object .finalise Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group* Use an image pre-loaded with the data processing software that terminates the instances when processing completes
• C. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provideappropriate Identity and Access Management (1AM) access to the bucket* Use Cloud Monitoring to detect new batches of data in the bucket and trigger a Cloud Function that processes the data* Set a Cloud Function to use the largest CPU possible to minimize the runtime of the processing
• D. * Provide a secure file transfer protocol (SFTP) server on a Compute Engine instance so that thirdparties can upload batches of data and provide appropriate credentials to the server* Create a Cloud Function with a google.storage, object, finalize Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group* Use an image pre-loaded with the data processing software that terminates the instances when processing completes

You are configuring your CI/CD pipeline natively on Google Cloud. You want builds in a pre-production Google Kubernetes Engine (GKE) environment to be automatically load-tested before being promoted to the production GKE environment. You need to ensure that only builds that have passed this test are deployed to production. You want to follow Google-recommended practices. How should you configure this pipeline with Binary Authorization?

• A. Create an attestation for the builds that pass the load test by requiring the lead quality assurance engineer to sign the attestation by using a key stored in Cloud Key Management Service (Cloud KMS).
• B. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) authenticated through Workload Identity.
• C. Create an attestation for the builds that pass the load test by requiring the lead quality assurance engineer to sign the attestation by using their personal private key.
• D. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) with a service account JSON key stored as a Kubernetes Secret.

You are building and running client applications in Cloud Run and Cloud Functions Your client requires that all logs must be available for one year so that the client can import the logs into their logging service You must minimize required code changes What should you do?

• A. Create a storage bucket and appropriate VPC firewall rules Update all images in Cloud Run and allfunctions in Cloud Functions to send logs to a file within the storage bucket
• B. Create a logs bucket and logging sink. Set the retention on the logs bucket to 365 days Configure thelogging sink to send logs to the bucket Give your client access to the bucket to retrieve the logs
• C. Update all images in Cloud Run and all functions in Cloud Functions to send logs to both Cloud Logging andthe client's logging service Ensure that all the ports required to send logs are open in the VPC firewall
• D. Create a Pub/Sub topic subscription and logging sink Configure the logging sink to send all logs into thetopic Give your client access to the topic to retrieve the logs