The best options for defining triggers that indicate whether an incident requires a postmortem based on Site Reliability Engineering (SRE) practices are an external stakeholder asks for a postmortem and data is lost due to an incident. An external stakeholder is someone who is affected by or has an interest in the service, such as a customer or a partner. If an external stakeholder asks for a postmortem, it means that they are concerned about the impact or root cause of the incident, and they expect an explanation and remediation from the service provider. Therefore, this should trigger a postmortem to address their concerns and improve their satisfaction. Data loss is a serious consequence of an incident that can affect the integrity and reliability of the service. If data is lost due to an incident, it means that there was a failure in the backup or recovery mechanisms, or that there was a corruption or deletion of data. Therefore, this should trigger a postmortem to investigate the cause and impact of the data loss, and to prevent it from happening again.

Comprehensive and Detailed Explanation:
The best approach to a joint-ownership DevOps model follows SRE and DevOps best practices, where:
The DevOps team manages infrastructure and is on-call for incidents.
The Software Development team owns SLOs and submits code.
Code reviews should be a shared responsibility to ensure both teams maintain quality.
#Why not other options?
A (DevOps team reviewing all code)## Breaks DevOps best practices by making developers dependent on the DevOps team for code review.
B (DevOps does code reviews, developers handle incidents)## Developers should not handle on-call duties unless part of a shared rotation.
C (Developers manage infrastructure)## Developers should not be fully responsible for infrastructure.
#Official Reference:
SRE & DevOps Ownership Model
Shared Responsibility Model in Google Cloud

https://cloud.google.com/logging/docs/routing/overview

https://cloud.google.com/kubernetes-engine/docs/concepts/custom-and-external-metrics#custom_metrics
https://github.com/GoogleCloudPlatform/k8s-stackdriver/blob/master/custom-metrics-stackdriver-adapter
/README.md
Your application can report a custom metric to Cloud Monitoring. You can configure Kubernetes to respond to these metrics and scale your workload automatically. For example, you can scale your application based on metrics such as queries per second, writes per second, network performance, latency when communicating with a different application, or other metrics that make sense for your workload.https://cloud.google.com
/kubernetes-engine/docs/concepts/custom-and-external-metrics