github.com/grafana/pyroscope@v1.18.0/docs/sources/shared/use-explore-profiles.md (about)

     1  ---
     2  headless: true
     3  description: Shared file for Profiles Drilldown overview.
     4  ---
     5  
     6  [//]: # 'This file documents an introduction to Profiles Drilldown.'
     7  [//]: # 'This shared file is included in these locations:'
     8  [//]: # '/pyroscope/docs/sources/configure-client/profile-types.md'
     9  [//]: # '/pyroscope/docs/sources/introduction/profiling-types.md'
    10  [//]: #
    11  [//]: # 'If you make changes to this file, verify that the meaning and content are not changed in any place where the file is included.'
    12  [//]: # 'Any links should be fully qualified and not relative: /docs/grafana/ instead of ../grafana/.'
    13  <!-- Use Profiles Drilldown to investigate issues -->
    14  
    15  {{< docs/public-preview product="Profiles Drilldown" >}}
    16  
    17  [Grafana Profiles Drilldown](https://grafana.com/docs/grafana-cloud/visualizations/simplified-exploration/profiles/) is designed to make it easy to visualize and analyze profiling data.
    18  There are several different modes for viewing, analyzing, and comparing profiling data.
    19  
    20  The main use cases are the following:
    21  
    22  - Proactive: Cutting costs, addressing latency issues, or optimizing memory usage for applications
    23  - Reactive: Resolving incidents with line-level accuracy or debugging active latency/memory issues
    24  
    25  Profiles Drilldown provides an intuitive interface to specifically support these use cases.
    26  You get a holistic view of all of your services and how they're functioning, but also the ability to drill down for more targeted root cause analysis.
    27  
    28  ![Profiles Drilldown home screen](/media/docs/explore-profiles/explore-profiles-homescreen-v1.png)
    29  
    30  Profiles Drilldown offers a convenient platform to analyze profiles and get insights that are impossible to get from using other traditional signals like logs, metrics, or tracing.
    31  
    32  {{< youtube id="x9aPw_CbIQc" >}}
    33  
    34  {{< docs/play title="the Grafana Play site" url="https://play.grafana.org/a/grafana-pyroscope-app/profiles-explorer" >}}
    35  
    36  ## Continuous profiling
    37  
    38  While code profiling has been a long-standing practice, continuous profiling represents a modern and more advanced approach to performance monitoring.
    39  
    40  This technique adds two critical dimensions to traditional profiles:
    41  
    42  Time
    43  : Profiling data is collected _continuously_, providing a time-centric view that allows querying performance data from any point in the past.
    44  
    45  Metadata
    46  : Metadata enriches profiling data, adding contextual depth to the performance data.
    47  
    48  These dimensions, coupled with the detailed nature of performance profiles, make continuous profiling a uniquely valuable tool.
    49  
    50  ## Flame graphs
    51  
    52  <!-- vale Grafana.We = NO -->
    53  
    54  Flame graphs help you visualize resource allocation and performance bottlenecks, and you even get suggested recommendations and performance fixes via AI-driven flame graph analysis, as well as line-level insights from our GitHub integration.
    55  
    56  <!-- vale Grafana.We = YES -->
    57  
    58  On views with a flame graph, you can use **Explain flame graph** to provide an AI flame graph analysis that explains the performance bottleneck, root cause, and recommended fix.
    59  For more information, refer to [Flame graph AI](https://grafana.com/docs/grafana-cloud/monitor-applications/profiles/flamegraph-ai/).