Managed Service for Prometheus

Related topics

• GKE works with Managed Service for Prometheus From the official documentation: “The GKE cluster is configured with [Google Cloud Managed Service for Prometheus](/stackdriver/docs/managed-prometheus), which enables collection of metrics in the Prometheus format.”
• Cloud Logging works with Managed Service for Prometheus From the official documentation: “The Managed Service for Prometheus sidecar writes logs to Cloud Logging.”
• Cloud Monitoring depends on Managed Service for Prometheus From the official documentation: “To use the dashboard in Cloud Monitoring, you must enable [Google Cloud Managed Service for Prometheus](/stackdriver/docs/managed-prometheus), which collects the metrics from vLLM, in your GKE cluster.”
• Cloud Monitoring works with Managed Service for Prometheus From the official documentation: “The Managed Service for Prometheus sidecar reports the following metrics about itself to Cloud Monitoring:”
• Cloud Run works with Managed Service for Prometheus From the official documentation: “You deployed a Cloud Run service that reports custom OTLP metrics to Google Cloud Managed Service For Prometheus.”
• Google Kubernetes Engine works with Managed Service for Prometheus From the official documentation: “This document describes how to configure your Google Kubernetes Engine deployment so that you can use Google Cloud Managed Service for Prometheus to collect metrics from Redis.”
• Managed Service for Prometheus is part of Cloud Monitoring From the official documentation: “Google Cloud Managed Service for Prometheus is part of Cloud Monitoring and is available as an option for system components.”
• Managed Service for Prometheus depends on Cloud Monitoring From the official documentation: “We recommend that you use Google Cloud Managed Service for Prometheus, which is based in Cloud Monitoring, for all your monitoring needs.”
• Managed Service for Prometheus depends on Cloud Monitoring API From the official documentation: “Managed Service for Prometheus captures metric data by using the Cloud Monitoring API.”
• Application Default Credentials secures BigQuery From the official documentation: “To authenticate to BigQuery, set up Application Default Credentials.”
• BigQuery depends on Application Default Credentials From the official documentation: “To authenticate to BigQuery, set up Application Default Credentials.”
• BigQuery works with Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• Application Default Credentials works with BigQuery From the official documentation: “Create a BigQuery client using application default credentials.”
• Application Default Credentials works with Compute Engine From the official documentation: “To authenticate to Compute Engine, set up Application Default Credentials.”
• BigQuery works with Cloud Monitoring From the official documentation: “You can use Monitoring to export your metrics to BigQuery.”
• Application Default Credentials secures Compute Engine From the official documentation: “To authenticate to Compute Engine, set up Application Default Credentials.”
• Cloud Logging works with GKE From the official documentation: “Enable Cloud Logging on GKE Clusters”
• Compute Engine is an alternative to GKE From the official documentation: “To use TPU7x, you can use Google Kubernetes Engine (GKE) or Compute Engine.”
• Cloud Logging works with Cloud Service Mesh From the official documentation: “Cloud Service Mesh stores the dry-run results to Cloud Logging in the following labels:”
• Cloud Monitoring depends on Application Default Credentials From the official documentation: “To authenticate to Monitoring, set up Application Default Credentials.”
• Cloud Monitoring works with Cloud Service Mesh From the official documentation: “Mesh telemetry is no longer automatically ingested into Cloud Monitoring.”
• Cloud Monitoring works with GKE From the official documentation: “Enable Cloud Monitoring on GKE Clusters”
• Cloud Run works with Cloud Service Mesh From the official documentation: “This section shows you how to troubleshoot common errors with Cloud Service Mesh and Cloud Run.”
• Cloud Run depends on Application Default Credentials From the official documentation: “To authenticate to Cloud Run, set up Application Default Credentials.”
• Cloud Run is an alternative to GKE From the official documentation: “The app uses Cloud SQL, Vertex AI, and either Google Kubernetes Engine (GKE) or Cloud Run.”
• App Engine is an alternative to Cloud Run From the official documentation: “App Engine and Cloud Run are Google Cloud platforms for hosting apps and services.”
• Application Default Credentials works with Cloud Run From the official documentation: “To authenticate to Cloud Run, set up Application Default Credentials.”
• Artifact Registry works with Cloud Run From the official documentation: “Cloud Run recommends using Artifact Registry.”
• Cloud Logging depends on Application Default Credentials From the official documentation: “To authenticate to Logging, set up Application Default Credentials.”
• Cloud Service Mesh depends on GKE From the official documentation: “Provision managed Cloud Service Mesh on a GKE cluster.”
• Cloud Service Mesh works with GKE From the official documentation: “# Set up a proxyless gRPC service mesh on GKE”
• Cloud Service Mesh works with Google Kubernetes Engine From the official documentation: “A GKE Cluster with Cloud Service Mesh enabled”
• App Engine works with Application Default Credentials From the official documentation: “The Application Default Credentials (ADC) infer authentication details for App Engine apps.”
• Artifact Registry works with Compute Engine From the official documentation: “Compute Engine can pull containers directly from Artifact Registry repositories.”
• Artifact Registry works with GKE From the official documentation: “In the next tutorial, you deploy those images from the Artifact Registry repository to a GKE cluster:”
• BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• Cloud Logging works with Compute Engine From the official documentation: “Compute Engine sends you Cloud Logging events for scheduled, started, or completed maintenance.”
• Cloud Service Mesh works with Compute Engine From the official documentation: “You can run applications on the following platforms and adopt them into a global service mesh that Cloud Service Mesh configures. | Feature | Supported | | --- | --- | | Compute Engine virtual machine (VM) instances | ✔ |”
• Compute Engine is an alternative to Google Kubernetes Engine From the official documentation: “You can install MongoDB on a Compute Engine instance or you can deploy MongoDB on Google Kubernetes Engine.”
• GKE depends on Compute Engine From the official documentation: “For example, GKE deploys clusters on Compute Engine VMs.”
• App Engine works with Artifact Registry From the official documentation: “Store dependencies for your App Engine applications in Artifact Registry.”
• App Engine works with Cloud Logging From the official documentation: “App Engine automatically sends both the request logs and app logs to the [Cloud Logging](/logging/docs/overview) agent.”
• App Engine works with Cloud Monitoring From the official documentation: “This tutorial shows how to set up an uptime alert for the [Python Hello World app](/python/getting-started/hello-world) running on App Engine flexible environment using [Cloud Monitoring](/monitoring/docs).”
• App Engine works with Compute Engine From the official documentation: “Your App Engine app can communicate with services hosted on Compute Engine within the same project without going through the public internet.”
• Application Default Credentials secures Cloud Monitoring From the official documentation: “To authenticate to Monitoring, set up Application Default Credentials.”
• Application Default Credentials works with GKE From the official documentation: “To authenticate to GKE, set up Application Default Credentials.”
• BigQuery works with Cloud Run From the official documentation: “You can then use Cloud Run to transcode data present in the bucket and move it to BigQuery.”
• Cloud Logging works with Cloud Monitoring From the official documentation: “If a log entry matches the filter of the alerting policy, then Cloud Logging extracts labels and forwards the data to Cloud Monitoring.”
• Cloud Logging works with Cloud Run From the official documentation: “Cloud Logging captures, stores, and analyzes Cloud Run logs.”
• Cloud Logging works with Google Kubernetes Engine From the official documentation: “As an example, if you are using GKE, you can [use Cloud Logging to query](/logging/docs/view/building-queries) for GKE cluster audit logs.”
• Cloud Monitoring works with Cloud Run From the official documentation: “Cloud Monitoring records metrics regarding the execution of Cloud Run.”
• Cloud Monitoring works with Compute Engine From the official documentation: “Many Google services like Compute Engine send telemetry to Cloud Monitoring.”
• Cloud Run works with GKE From the official documentation: “Leverage Google Kubernetes Engine (GKE) and Cloud Run to deploy applications to the Google Cloud, optimizing costs, performance, and management overhead.”
• Cloud Run works with Google Kubernetes Engine From the official documentation: “Improved security: take advantage of automatic IAM JWT injection for more secure communication between GKE and Cloud Run.”
• Cloud Service Mesh depends on Cloud Monitoring From the official documentation: “Cloud Service Mesh uses Cloud Monitoring to provide automatic telemetry and logs.”
• Google Kubernetes Engine depends on BigQuery From the official documentation: “This happens because Google Kubernetes Engine depends on BigQuery and Managed Service for Apache Airflow inherits this dependency from the Kubernetes Engine API.”
• Google Kubernetes Engine depends on Compute Engine From the official documentation: “Other products, such as [Google Kubernetes Engine](/kubernetes-engine) and [Dataflow](/dataflow), use Compute Engine resources and therefore, can be deployed in the same regions or zone.”
• App Engine works with BigQuery From the official documentation: “App Engine - Scalable platform as a service (PaaS) solution used to call the Monitoring API and write to BigQuery.”
• App Engine works with Cloud Monitoring API From the official documentation: “App Engine - Scalable platform as a service (PaaS) solution used to call the Monitoring API and write to BigQuery.”
• App Engine works with Google Kubernetes Engine From the official documentation: “Integration with other Google Cloud services is possible through Serverless VPC Access, which allows App Engine to sit within the same VPC as Compute Engine VMs and Google Kubernetes Engine clusters.”