Grafana Cloud

Explore telemetry data

Entity details include pre-filtered views of logs, traces, Kubernetes metrics, continuous profiling data, and entity properties. The knowledge graph automatically correlates all telemetry to the selected entity, eliminating the need to write custom queries.

Logs

The Logs tab provides instant access to all log events from the selected entity, pre-filtered to the current time range.

What you’ll see

  • Log stream showing recent log entries
  • Severity distribution (info, warning, error)
  • Time alignment matching the service overview time range
  • Automatic filters applied for the entity’s labels

Use logs for troubleshooting

Logs are especially valuable for:

  • Error investigation - Find stack traces and error messages during incidents
  • Deployment verification - Check startup messages after deployments
  • Pattern discovery - Identify repeated warnings or unusual log patterns

The log view supports:

  • Full-text search to find specific messages
  • Severity filtering to focus on errors or warnings
  • Time range adjustment to narrow or expand the window
  • Log context - Click any log line to see surrounding entries

Logs automatically sync with the time range selected in the service overview, allowing you to correlate log events with metric anomalies.

Traces

The Traces tab shows distributed trace data for requests handled by the entity.

Duration heatmap

The primary visualization is a duration heatmap showing:

  • Request distribution over time (x-axis)
  • Duration buckets from fast to slow (y-axis)
  • Color intensity indicating request volume in each bucket

This allows you to spot:

  • Latency spikes appearing as vertical bands in slower buckets
  • Bimodal patterns when some requests are fast, others slow
  • Degradation over time with requests gradually moving to slower buckets

Trace analysis

Below the heatmap, you’ll find:

  • Sample traces from the selected time range
  • Duration statistics (P50, P95, P99)
  • Error rate for traced requests
  • Operation breakdown showing which endpoints are slowest

Click any trace to open the full trace timeline with:

  • All service hops and their durations
  • Database queries and external API calls
  • Error annotations and log correlation

When traces are most useful

Use the Traces tab to:

  • Diagnose slow requests by examining trace timelines
  • Identify downstream bottlenecks from service call durations
  • Correlate errors between services in the request path
  • Validate optimizations by comparing trace patterns before and after changes

Kubernetes metrics

For services running on Kubernetes, the Kubernetes metrics tab shows infrastructure health.

Pod metrics

  • CPU usage - Current and historical CPU consumption
  • Memory usage - Current memory with limits and requests
  • Network I/O - Bytes sent and received
  • Restart count - How many times pods have restarted

Node metrics

If viewing a node entity, you’ll see:

  • Node capacity - Total CPU and memory available
  • Pod count - Number of pods scheduled on the node
  • Disk usage - Available and used disk space
  • Network throughput - Node-level traffic

Resource saturation indicators

The Kubernetes metrics tab highlights:

  • CPU throttling when pods exceed their limits
  • Memory pressure approaching OOM conditions
  • Disk saturation nearing capacity
  • Network bottlenecks with high packet loss

These metrics help answer questions like:

  • Is the service resource-constrained?
  • Should we increase CPU or memory limits?
  • Are pods restarting due to OOM kills?
  • Is the node saturated?

Profiles

The Profiles tab provides access to continuous profiling data, showing where your application spends CPU time and allocates memory.

CPU profiles

The CPU flame graph shows:

  • Function call hierarchy with time spent in each function
  • Hot paths highlighting expensive code sections
  • Over time comparison to detect performance regressions

Use CPU profiles to:

  • Identify inefficient algorithms or loops
  • Find unexpected library overhead
  • Validate performance optimizations

Memory profiles

Memory allocation profiles show:

  • Allocation sites and their frequency
  • Memory leak detection with growing allocations
  • Garbage collection impact from excessive allocations

Memory profiles help answer:

  • Where is memory being allocated?
  • Are there memory leaks over time?
  • Can we reduce allocation pressure?

Profile availability

Continuous profiling requires:

  • Grafana Pyroscope integration enabled
  • Application instrumented for profiling (automatic for supported languages)
  • Profile data being sent to Grafana Cloud

If profiles aren’t available, the tab shows setup instructions.

Properties

The Properties tab displays all metadata and discovery information for the entity.

Entity metadata

  • Entity type - Service, Pod, Node, Database, and so on.
  • Cluster and Namespace (for Kubernetes entities)
  • Labels - All key-value labels attached to the entity
  • Annotations - Additional metadata from discovery sources

Discovery information

  • Data source - How the entity was discovered (OpenTelemetry, Istio, Prometheus exporters)
  • First seen - When the entity first appeared
  • Last updated - Most recent telemetry timestamp
  • Related entities - Connections to other entities in the graph

Custom properties

Any custom labels or properties you’ve added appear here, allowing you to:

  • Filter the entity catalog by team, environment, or version
  • Group entities for monitoring views
  • Track deployment metadata

Add entities to RCA workbench

From any tab in the entity details, you can add the entity to RCA workbench for multi-entity investigation.

Click Add to RCA workbench to:

  • Include this entity in your current RCA workbench session
  • See its insights correlated with other entities on a timeline
  • Navigate between related entities in the incident context

This is especially useful when:

  • An issue spans multiple services
  • You need to correlate infrastructure and application problems
  • You want to see which issues started at the same time

For more information, refer to Use RCA workbench.

Next steps