Performance

About Classic Cloud Observability features

Classic Cloud Observability features will soon be replaced by new and improved unified workflows.

About ingesting Prometheus metrics

Ingest existing Prometheus metrics into Cloud Observability using the OpenTelemetry Collector running in a Kubernetes environemnt.

Create and manage dashboards

Learn how to create dashboards that can display both your metric and span data.

Create dashboards from tri-charts

Group multiple Streams to create a dashboard.

Create deployment markers

You can add deployment markers to your charts to see when service versions change, and if the change affects performance in any way.

Dashboards

Use Cloud Observability to monitor performance of you services.

Data visualizations

You use charts in your dashboards, notebooks, and alerts to visualize your data.

Find correlated areas of latency and errors

A standard method of identifying the root cause of a performance regression is to manually comb through traces and search for common system attributes associated with that regression or with errors. With Correlations, {{site.name}} helps you find attributes correlated with latency and errors automatically.

How Cloud Observability displays metrics

Learn how Cloud Observability displays metrics.

Ingest Prometheus metrics with an OpenTelemetry Collector on Kubernetes

Cloud Observability recommends using OpenTelemetry Collectors to scrape Kubernetes metrics and send them to Cloud Observability.

Ingest metrics from Amazon

Easily send AWS CloudWatch metrics from multiple projects to Cloud Observability using the Cloud Observability UI.

Ingest metrics from Azure AKS

See Azure AKS metrics ingested by Cloud Observability

Ingest metrics from Azure Monitor

Use the OpenTelemetry Collector to ingest metrics from Azure Monitor. You can then use prebuilt dashboards to display those metrics.

Ingest metrics from Google Cloud Monitoring

Configure Google Cloud metrics to report to Cloud Observability.

Ingest metrics from Google Kubernetes Engine (GKE)

See Google Kubernetes Engine (GKE) metrics ingested by Cloud Observability

Ingest traces from the Datadog Agent

Configure the Datadog Agent to send traces to Cloud Observability.

Install the OpenTelemetry Collector on Kubernetes

Install an OpenTelemetry Collector on Kubernetes to begin collecting application and infrastructure metrics

Investigate a latency regression

You can use Cloud Observability not only to monitor your services after a deploy, but also to compare performance over specific time periods and then dig into details to find the differences that caused the issue.

Investigate an error rate increase

When you notice an increase in error rate on Cloud Observability's Service Health view, you can use the analytical tools to find the source of errors.

Manage the Collector

Overview of how to monitor and scale the OpenTelemetry Collector.

Monitor Kubernetes applications

Cloud Observability can ingest Kubernetes infrastructure and application metrics using the OpenTelemetry Collector and Operator. If you're currently using Prometheus from metrics, you can also choose to replace those with the Collector and Operator.

Monitor deployments

Cloud Observability offers a way to see how your deployments (even partial deployments) affect your service performance.

Monitor service health and performance changes

See the health of the key operations on your services, including latency, error rate, operation rate, and infrastructure metrics.

Monitor span data with Streams

Create Streams to view historical span and trace data and monitor your services.

Monitor the Collector

Overview of how to monitor and scale the OpenTelemetry Collector.

OpenTelemetry Kubernetes metrics quickstart

Ingest Prometheus metrics into Cloud Observability using the OpenTelemetry Collector running in a Kubernetes environemnt.

Query real-time span data

Cloud Observability's Explorer view allows you to query all span data currently in the Microsatellites' retention window to see what's going on. You create Snapshots that are durably persisted, allowing you to view performance at a certain point in time and share that Snapshot with others. You can see real-time span data, filter and group that data, and drill down on common attributes that may be causing latency.

Retain queries with Streams

Create Streams to view historical span and trace data and monitor your services.

Scale an OpenTelemetry Collector's tracing pipeline in Kubernetes

This topic provides instructions for scaling the OpenTelemetry Collector deployment for tracing in Kubernetes.

Service health

Cloud Observability offers a way to quickly see how all your services and their operations are performing in one place - the Service Directory view.

Use dependency maps

You can add dependency maps to your dashboards and notebooks that allow you to view services and operations in context of each other, both up and downstream.

Use template variables

Use template variables in dashboards to dynamically filter charts on a dashboard.

View and compare deployed versions

Cloud Observability offers a way to see how your deployments (even partial deployments) affect your service performance.

View service hierarchy and performance

You can use Cloud Observability's Service diagram to get an aggregate view of trace data as a request travels through your system. The Service diagram provides a visual, interactive, and hierarchical representation of a system’s behavior for a given point in time.

View traces

You use the Trace view to see a full trace from beginning to end of a request. The Trace view shows you a flame graph of the full trace (each service a different color) and below that, each span is shown in a hierarchy, allowing you to see the parent-child relationship of all the spans in the trace. Errors are shown in red.

AWS Key Management Service metrics

See the AWS Key Management Service (KMS) metrics ingested by Cloud Observability