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This repository was archived by the owner on Sep 2, 2025. It is now read-only.
To maximize responsiveness when processing incoming metric data, Splunk Observability Cloud limits the number of :term:`metric time series` (MTS) processed in a signal
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(single plot line) on a chart or detector. If the total number of time series for the metric specified in your signal exceeds this limit, Splunk Observability Cloud displays
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an orange border around the MTS number. This border notifies you that the processed data reflects only a subset of the time series in the data.
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To maximize responsiveness when processing incoming metric data, Splunk Observability Cloud limits the number of :term:`metric time series` (MTS) processed in a signal (single plot line) on a chart, detector, or navigator. If the total number of time series for the metric specified in your signal exceeds this limit, Splunk Observability Cloud displays a message at the top of the chart, detector, or navigator. This message notifies you that the processed data reflects only a subset of the time series in the data.
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To ensure that your charts and detectors are processing all the time series in the data, apply as many filters as necessary to make the MTS number less than the maximum.
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You'll know you've succeeded when the orange outline around the MTS number and the message at the top of the chart or detector no longer appear.
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To ensure that your charts, detectors, and navigators are processing all the time series in the data, apply as many filters as necessary to make the MTS number less than the maximum. You'll know you've succeeded when the message at the top of the chart, detector, or navigator no longer appears.
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For example, suppose you want to display the sum of available disk capacity per availability zone. You might use ``df.complex.free`` as your signal,
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then apply the Sum analytics function, grouped by availability zone. If you have a large number of disks, the number of MTS returned by this signal might
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For example, suppose you want to display the sum of available disk capacity per availability zone. You might use ``df.complex.free`` as your signal, then apply the Sum analytics function, grouped by availability zone. If you have a large number of disks, the number of MTS returned by this signal might
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exceed the limit. To reduce the number of MTS, use filters and multiple plots instead of the group-by option in the Sum analytics function.
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Use filters and multiple plots on charts and detectors
To use filters and multiple plots instead of the group-by option, follow these steps:
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#. Apply a filter for the plot that selects a single availability zone, then use the Sum analytic function without the group-by option.
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#. At the end of the plot row, select :guilabel:`Configure plot` to open :guilabel:`Visualization Options`, then select a color from :guilabel:`Plot Color`.
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#. Clone the plot. To do this, open the :guilabel:`plot actions` menu at the end of the plot row in the :guilabel:`Plot Editor`,
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#. Clone the plot. To do this, open the :guilabel:`Plot actions` menu at the end of the plot row in the :guilabel:`Plot Editor`,
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then select :menuselection:`Clone`.
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#. In the cloned plot, change the availability zone filter to select another availability zone, and change the :guilabel:`Plot Color` to give the cloned
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plot a color that's different from the original plot.
@@ -31,3 +30,8 @@ To use filters and multiple plots instead of the group-by option, follow these s
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The result is one chart with a separate plot line for each availability zone. Each plot line has a distinct color.
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For more information on filtering, see :ref:`filter-signal`.
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Use filters on navigators
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=============================
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To use filters on navigators, see :ref:`add-filter`.
About Splunk OTel JS <splunk-nodejs-otel-dist.rst>
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Migrate from the SFx Tracing Library <troubleshooting/migrate-signalfx-nodejs-agent-to-otel.rst>
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.. note:: The Splunk OpenTelemetry JS version 3.0 contains a set of breaking changes. To view these changes and learn how to update to version 3.0, see :ref:`nodejs-3x-breaking-changes`.
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.. caution::
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The Splunk Distribution of OpenTelemetry JS version 2.X is deprecated as of February 28, 2025 and will reach end of support on February 28, 2026. Until then, only critical security fixes and bug fixes will be provided.
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New customers should use the Splunk OpenTelemetry JS agent version 3.0. Existing customers should consider migrating to Splunk OpenTelemetry JS 3.0 or higher. See :ref:`nodejs-3x-breaking-changes`.
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The Splunk Distribution of OpenTelemetry JS provides a Node.js SDK that automatically adds APM instrumentation to your Node.js application. The instrumentation captures traces, runtime metrics, and CPU and memory profiles and sends them to Splunk Observability Cloud.
Copy file name to clipboardExpand all lines: gdi/get-data-in/application/python/instrumentation/instrument-python-application.rst
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@@ -74,7 +74,7 @@ Follow these steps to automatically instrument your application using the Python
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.. code-block:: bash
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opentelemetry-bootstrap
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opentelemetry-bootstrap -a install
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To print the instrumentation packages to the console instead of installing them, run ``opentelemetry-bootstrap --action=requirements``. You can then add the output to your requirements or Pipfile.
- Installs instrumentation libraries and dependencies for Splunk OpenTelemetry Python.
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- Lists instrumentation libraries and dependencies for Splunk OpenTelemetry Python. To install the libraries and dependencies, use ``opentelemetry-bootstrap -a install``.
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