Google Professional-Cloud-DevOps-Engineer Exam With Confidence Using Practice Dumps

The best option for deploying a new version of your containerized application to production on GKE and ensuring that the application does not have performance problems after deployment is to deploy the application through a continuous delivery pipeline by using canary deployments, use Cloud Monitoring to look for performance issues, and ramp up traffic as supported by the metrics. A canary deployment is a deployment strategy that involves releasing a new version of an application to a subset of users or servers and monitoring its performance and reliability. This way, you can test the new version in the production environment with real traffic and load, and gradually increase the traffic as the metrics indicate. You can use Cloud Monitoring to collect and analyze metrics from your application and GKE cluster, such as latency, error rate, CPU utilization, and memory usage. You can also use Cloud Monitoring to set up alerts and dashboards to track the performance of your application.

Reason : Incident has not occurred yet, even when development team is already pushing new features multiple times a week. The option A says, to define an error budget "policy", not to define error budget(It is already present). Just simple means to bring in all stakeholders, and decide how to consume the error budget effectively that could bring balance between feature deployment and reliability.

The goals of this policy are to: -- Protect customers from repeated SLO misses -- Provide an incentive to balance reliability with other

 The most efficient way to build an automated pipeline that deploys the application when the image is updated is to use Cloud Pub/Sub to trigger a Spinnaker pipeline. This way, you can leverage the built-in integration between GCR and Cloud Pub/Sub, and use Spinnaker as a continuous delivery platform for deploying your application .