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.

Add inferred services

Create project-based rules to add inferred services (external services, libraries, or dependencies that haven’t been instrumented) to your dependency maps.

Create and manage dashboards

Learn how to create dashboards that can display both your log, 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

Use panels in dashboards, notebooks, and alerts to visualize data.

Explore logs

Get insights and learn from your logs.

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 logs from the Datadog Agent

Configure the Datadog Agent to send logs 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 telemetry data from the Datadog Agent

Configure the Datadog Agent to send telemetry data to 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

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 span data with Streams

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

Query real-time span data

Cloud Observability's Explorer view allows you to query all span data currently in the retention window. 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 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 dashboard workflow links

Dashboard workflow links allow you to add links from a dashboard to external applications or sites (like Slack or GitHub) or to other places in Cloud Observability. Like the workflow links used on the Trace view, these links can take attributes as values in the link, allowing you to scope the link for context. In addition, they can also use template variables allowing you to carry context over to another dashboard. You can create links for a dashboard or for a single panel.

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 panels on a dashboard.

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