Google Cloud Certified – Professional Cloud DevOps Engineer Exam (Professional-Cloud-DevOps-Engineer) - Google Cloud

a latency SLO is a service level objective that specifies a target level of responsiveness for a web application1. A latency SLO can be expressed as a percentile of latency over a time window, such as the 90th percentile of latency over 28 days2. A percentile of latency is the maximum amount of time that a given percentage of requests take to complete. For example, the 90th percentile of latency is<br />
the maximum amount of time that 90% of requests take to complete3.<br />
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To define a latency SLO, you need to consider the following factors24: The expectations and satisfaction of your customers. You want to set a latency SLO that reflects the level of performance that your customers are happy with and willing to pay for. The current and historical measurements of your latency. You want to set a latency SLO that is based on data and realistic for your web application. The trade-offs and costs of improving your latency. You want to set a latency SLO that balances the benefits of faster response times with the costs of engineering work, infrastructure, and complexity. Based on these factors, the best option for defining a latency SLO for your web application is option<br />
<br />
B. Option B sets the latency SLO to match the current measurement of your latency, which means<br />
that you are meeting the expectations and satisfaction of your customers. Option B also sets a realistic and achievable target for your web application, which means that you do not need to invest extra resources or effort to improve your latency. Option B also aligns with the best practice of setting conservative SLOs, which means that you have some buffer or margin for error in case your latency fluctuates or degrades5.

The best options for creating a CI/CD pipeline in Cloud Build to build an application container image and ensuring that production image builds are only run against the main branch and that the change control team approves all pushes to the main branch are to create a trigger on the Cloud Build job, set the repository event setting to Push to a branch, and configure a branch protection rule for the main branch on the repository. A trigger is a resource that starts a build when an event occurs, such as a code change. By creating a trigger on the Cloud Build job and setting the repository event setting to Push to a branch, you can ensure that the image build is only run when code is pushed to a specific branch, such as the main branch. A branch protection rule is a rule that enforces certain policies on a branch, such as requiring reviews, status checks, or approvals before merging code. By configuring a branch protection rule for the main branch on the repository, you can ensure that the change control team approves all pushes to the main branch.

https://sre.google/sre-book/service-level-objectives/

The best option for implementing a scalable solution to support global Prometheus querying and minimize management overhead is to use Google Cloud Managed Service for Prometheus. Google Cloud Managed Service for Prometheus is a fully managed service that allows you to collect, query, and visualize metrics from your GKE clusters using Prometheus-based tooling. You can use Google Cloud Managed Service for Prometheus to query metrics across multiple clusters and regions using a global view. You can also use Google Cloud Managed Service for Prometheus to integrate with other Google Cloud services, such as Cloud Monitoring, Cloud Logging, and BigQuery. By using Google Cloud ManagedService for Prometheus, you can avoid managing and scaling your own Prometheus servers and focus on your application performance.