You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (Pll) is leaking into certain log entry fields. All Pll entries begin with the text userinfo. You want to capture these log entries in a secure location for later review and prevent them from leaking to Stackdriver Logging. What should you do?

• A. Create a basic log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
• B. Create an advanced log filter matching userinfo, configure a log export in the Stackdriver console with Cloud Storage as a sink, and then configure a tog exclusion with userinfo as a filter.
• C. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, create an advanced log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
• D. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, and then copy the entries to a Cloud Storage bucket.

You are part of an organization that follows SRE practices and principles. You are taking over the management of a new service from the Development Team, and you conduct a Production Readiness Review (PRR). After the PRR analysis phase, you determine that the service cannot currently meet its Service Level Objectives (SLOs). You want to ensure that the service can meet its SLOs in production. What should you do next?

• A. Bring the service into production with no SLOs and build them when you have collected operational data.
• B. Notify the development team that they will have to provide production support for the service.
• C. Adjust the SLO targets to be achievable by the service so you can bring it into production.
• D. Identify recommended reliability improvements to the service to be completed before handover.

You support a multi-region web service running on Google Kubernetes Engine (GKE) behind a Global HTTP'S Cloud Load Balancer (CLB). For legacy reasons, user requests first go through a third-party Content Delivery Network (CDN). which then routes traffic to the CLB. You have already implemented an availability Service Level Indicator (SLI) at the CLB level. However, you want to increase coverage in case of a potential load balancer misconfiguration. CDN failure, or other global networking catastrophe. Where should you measure this new SLI?
Choose 2 answers

• A. Metrics exported from the application servers
• B. Your application servers' logs
• C. A synthetic client that periodically sends simulated user requests
• D. GKE health checks for your application servers
• E. Instrumentation coded directly in the client

You support a high-traffic web application that runs on Google Cloud Platform (GCP). You need to measure application reliability from a user perspective without making any engineering changes to it. What should you do?
Choose 2 answers

• A. Modify the code to capture additional information for user interaction.
• B. Review current application metrics and add new ones as needed.
• C. Analyze the web proxy logs only and capture response time of each request.
• D. Create new synthetic clients to simulate a user journey using the application.
• E. Use current and historic Request Logs to trace customer interaction with the application.

You are running a web application deployed to a Compute Engine managed instance group Ops Agent is installed on all instances You recently noticed suspicious activity from a specific IP address You need to configure Cloud Monitoring to view the number of requests from that specific IP address with minimal operational overhead. What should you do?

• A. Configure the Ops Agent with a metrics receiver
• B. Update the application to export the IP address request metrics to the Cloud Monitoring API
• C. Create a script to scrape the web server log Export the IP address request metrics to the Cloud Monitoring API
• D. Configure the Ops Agent with a logging receiver Create a logs-based metric