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Classic Cloud Observability features will soon be replaced by new and improved unified workflows.
Ingest existing Prometheus metrics into Cloud Observability using the OpenTelemetry Collector running in a Kubernetes environemnt.
Learn how to create dashboards that can display both your metric and span data.
Group multiple Streams to create a dashboard.
You can add deployment markers to your charts to see when service versions change, and if the change affects performance in any way.
Use Cloud Observability to monitor performance of you services.
You use charts in your dashboards, notebooks, and alerts to visualize your data.
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.
Learn how Cloud Observability displays metrics.
Cloud Observability recommends using OpenTelemetry Collectors to scrape Kubernetes metrics and send them to Cloud Observability.
Easily send AWS CloudWatch metrics from multiple projects to Cloud Observability using the Cloud Observability UI.
See Azure AKS metrics ingested by Cloud Observability
Use the OpenTelemetry Collector to ingest metrics from Azure Monitor. You can then use prebuilt dashboards to display those metrics.
Configure Google Cloud metrics to report to Cloud Observability.
See Google Kubernetes Engine (GKE) metrics ingested by Cloud Observability
Configure the Datadog Agent to send traces to Cloud Observability.
Install an OpenTelemetry Collector on Kubernetes to begin collecting application and infrastructure metrics
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.
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.
Overview of how to monitor and scale the OpenTelemetry Collector.
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.
Cloud Observability offers a way to see how your deployments (even partial deployments) affect your service performance.
See the health of the key operations on your services, including latency, error rate, operation rate, and infrastructure metrics.
Create Streams to view historical span and trace data and monitor your services.
Overview of how to monitor and scale the OpenTelemetry Collector.
Ingest Prometheus metrics into Cloud Observability using the OpenTelemetry Collector running in a Kubernetes environemnt.
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.
Create Streams to view historical span and trace data and monitor your services.
This topic provides instructions for scaling the OpenTelemetry Collector deployment for tracing in Kubernetes.
Cloud Observability offers a way to quickly see how all your services and their operations are performing in one place - the Service Directory view.
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 in dashboards to dynamically filter charts on a dashboard.
Cloud Observability offers a way to see how your deployments (even partial deployments) affect your service 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.
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.
See the AWS Key Management Service (KMS) metrics ingested by Cloud Observability