You use a multiple step Cloud Build pipeline to build and deploy your application to Google Kubernetes Engine (GKE). You want to integrate with a third-party monitoring platform by performing a HTTP POST of the build information to a webhook. You want to minimize the development effort. What should you do?
The most efficient way to integrate a third-party monitoring platform by performing an HTTP POST of the build information to a webhook is to add a new step at the end of the pipeline in Cloud Build. This approach keeps the implementation straightforward and centralized, minimizing development efforts by ensuring that the HTTP POST action occurs after the completion of the build process in a single place, rather than setting up separate services or more complex subscription models.
You use Spinnaker to deploy your application and have created a canary deployment stage in the pipeline. Your application has an in-memory cache that loads objects at start time. You want to automate the comparison of the canary version against the production version. How should you configure the canary analysis?
To effectively compare the canary deployment, it is recommended to use a new deployment of the current production version as a baseline. This ensures that both the canary and the baseline are subject to the same deployment conditions and factors, such as the cache warmup time and heap size. By comparing against a new deployment that matches the canary in terms of deployment time, size, and traffic, you can isolate the version and configuration differences and make a more accurate assessment of the canary.
You support a high-traffic web application and want to ensure that the home page loads in a timely manner. As a first step, you decide to implement a Service
Level Indicator (SLI) to represent home page request latency with an acceptable page load time set to 100 ms. What is the Google-recommended way of calculating this SLI?
To calculate the Service Level Indicator (SLI) for home page request latency with an acceptable load time of 100 ms, count the number of home page requests that load in under 100 ms and then divide this by the total number of home page requests. This method provides a clear and specific measurement of the proportion of requests that meet the latency requirement, ensuring accurate monitoring of the performance objective.
You deploy a new release of an internal application during a weekend maintenance window when there is minimal user tragic. After the window ends, you learn that one of the new features isn't working as expected in the production environment. After an extended outage, you roll back the new release and deploy a fix.
You want to modify your release process to reduce the mean time to recovery so you can avoid extended outages in the future. What should you do? (Choose two.)
To reduce the mean time to recovery and avoid extended outages, adopting the blue/green deployment strategy allows for safer rollouts by having two production environments: one running the current version and another running the new version. This ensures that in case of issues, you can quickly switch back without causing extended downtime. Configuring a CI server and adding a suite of unit tests that run on commit helps to identify and fix issues early in the development cycle, thus maintaining higher code quality and reducing the likelihood of deployment issues in production.
You have a pool of application servers running on Compute Engine. You need to provide a secure solution that requires the least amount of configuration and allows developers to easily access application logs for troubleshooting. How would you implement the solution on GCP?
To provide a secure and easy-to-configure solution for accessing application logs, you should deploy the Stackdriver logging agent to the application servers and give the developers the IAM Logs Viewer role. The Logs Viewer role allows read-only access to all Logging features except Access Transparency logs and Data Access audit logs, which are not needed for basic application log troubleshooting. This solution adheres to the principle of least privilege, ensuring developers can access the necessary logs without overextending permissions.