resolved merge conflict

Author: Tracey Carter

_images/images-slo/custom-metric-slo-scenario.png

@@ -25,7 +25,8 @@ Splunk Synthetic Monitoring offers metrics you can use to track your subscriptio
      - Total number of synthetic runs by organization. To filter by test type:
         - ``test_type=browser``
         - ``test_type=API``
-        - ``test_type=uptime`` 
+        - ``test_type=http`` 
+        - ``test_type=port`` 
 
 
 See also

admin/subscription-usage/synthetics-usage.rst

@@ -19,7 +19,7 @@ Follow these steps to create an SLO.
 #. From the landing page of Splunk Observability Cloud, go to :strong:`Detectors & SLOs`.
 #. Select the :strong:`SLOs` tab.
 #. Select :guilabel:`Create SLO`.
-#. Configure the service level indicator (SLI) for your SLO.
+#. Configure the service level indicator (SLI) for your SLO. You can use a service or any metric of your choice as the system health indicator.
 
     To use a service as the system health indicator for your SLI configuration, follow these steps:
 
@@ -46,21 +46,22 @@ Follow these steps to create an SLO.
           * - :guilabel:`Filters`
             - Enter any additional dimension names and values you want to apply this SLO to. Alternatively, use the ``NOT`` filter, represented by an exclamation point ( ! ), to exclude any dimension values from this SLO configuration.
 
-    To use a custom metric as the system health indicator for your SLI configuration, follow these steps:
+    To use a metric of your choice as the system health indicator for your SLI configuration, follow these steps:
 
-        .. list-table::
-          :header-rows: 1
-          :widths: 40 60
-          :width: 100%
+        #. For the :guilabel:`Metric type` field, select :guilabel:`Custom metric` from the dropdown menu. The SignalFlow editor appears.
+        #. In the SignalFlow editor, you can see the following code sample:
 
-          * - :strong:`Field name`
-            - :strong:`Actions`
-          * - :guilabel:`Metric type`
-            - Select :guilabel:`Custom metric` from the dropdown menu
-          * - :guilabel:`Good events (numerator)`
-            - Search for the metric you want to use for the success request count
-          * - :guilabel:`Total events (denominator)`
-            - Search for the metric you want to use for the total request count
+              .. code-block:: python
+
+                  G = data('good.metric', filter=filter('sf_error', 'false'))
+                  T = data('total.metric')
+              
+              * Line 1 defines ``G`` as a data stream of ``good.metric`` metric time series (MTS). The SignalFlow ``filter()`` function queries for a collection of MTS with value ``false`` for the ``sf_error`` dimension. The filter distinguishes successful requests from total requests, making ``G`` the good events variable.
+              * Line 2 defines ``T`` as a data stream ``total.metric`` MTS. ``T`` is the total events variable.
+
+           Replace the code sample with your own SignalFlow program. You can define good events and total events variables using any metric and supported SignalFlow function. For more information, see :new-page:`Analyze data using SignalFlow <https://dev.splunk.com/observability/docs/signalflow>` in the Splunk Observability Cloud Developer Guide.
+        
+        #. Select appropriate variable names for the :guilabel:`Good events (numerator)` and :guilabel:`Total events (denominator)` dropdown menus.
 
         .. note:: Custom metric SLO works by calculating the percentage of successful requests over a given compliance period. This calculation works better for counter and histogram metrics than for gauge metrics. Gauge metrics are not suitable for custom metric SLO, so you might get confusing data when selecting gauge metrics in your configuration.
 

alerts-detectors-notifications/slo/create-slo.rst

@@ -17,32 +17,22 @@ Use custom metric as service level indicator (SLI)
 
 From the :guilabel:`Detectors & SLOs` page, Kai configures the SLI and sets up a target for their SLO. Kai follows these steps: 
 
-#. Kai wants to use custom metrics as the system health indicators, so they select the :guilabel:`Custom metric` from the :guilabel:`Metric type` menu.
-#. Kai enters the custom metrics they want to measure in the following fields:
+#. Kai wants to use a Synthetics metric as the system health indicators, so they select the :guilabel:`Custom metric` from the :guilabel:`Metric type` menu.
+#. Kai enters following program into the SignalFlow editor:
 
-    .. list-table::
-        :header-rows: 1
-        :widths: 10 20 30 40
+      .. code-block:: python
 
-        * - Field
-          - Metric name
-          - Filters
-          - Description 
+          G = data('synthetics.run.count', filter=filter('test', 'Monitoring Services - Emby check') and filter('success', 'true'))
+          T = data('synthetics.run.count', filter=filter('test', 'Monitoring Services - Emby check'))
 
-        * - :guilabel:`Good events (numerator)`
-          - :strong:`synthetics.run.count`
-          - Kai adds the following filters for this metric:
-            
-              * :strong:`test = Emby check`
-              * :strong:`success = true`
-          - Kai uses the :strong:`success = true` filter to count the number of successful requests for the Emby service on the Buttercup Games website.
+   Kai defines variables ``G`` and ``T`` as two streams of ``synthetics.run.count`` metric time series (MTS) measuring the health of requests sent to the Emby service. To distinguish between the two data streams, Kai applies an additional filter on the ``success`` dimension in the definition for ``G``. This filter queries for a specific collection of MTS that track successful requests for the Emby service. In Kai's SignalFlow program, ``G`` is a data stream of good events and ``T`` is a data stream of total events.
 
-        * - :guilabel:`Total events (denominator)`
-          - :strong:`synthetics.run.count`
-          - Kai adds the following filter for this metric:
+      .. image:: /_images/images-slo/custom-metric-slo-scenario.png
+          :width: 100%
+          :alt: This image shows Kai's SLO configuration using the ``synthetics.run.count`` metric and appropriate filters.
 
-              * :strong:`test = Emby check`
-          - Kai uses the same metric name and the :strong:`test = Emby check` filter to track the same Synthetics Browser test. However, Kai doesn't include the :strong:`success = true` dimension filter in order to count the number of total requests for the Emby service on the Buttercup Games website.
+
+#. Kai assigns ``G`` to the :guilabel:`Good events (numerator)` dropdown menu and ``T`` to the :guilabel:`Total events (denominator)` dropdown menu.
 
 #. Kai enters the following fields to define a target for their SLO:
 
@@ -64,11 +54,6 @@ From the :guilabel:`Detectors & SLOs` page, Kai configures the SLI and sets up a
 
 #. Kai subscribes to receive an alert whenever there is a breach event for the SLO target.
 
-.. image:: /_images/images-slo/custom-metric-slo-scenario.png
-    :width: 100%
-    :alt: This image shows Kai's SLO configuration using the ``synthetics.run.count`` metric and appropriate filters.
-
-
 Summary
 =======================
 
@@ -80,3 +65,5 @@ Learn more
 For more information about creating an SLO, see :ref:`create-slo`. 
 
 For more information about the Synthetics Browser test, see :ref:`browser-test`.
+
+For more information on SignalFlow, see :new-page:`Analyze data using SignalFlow <https://dev.splunk.com/observability/docs/signalflow>` in the Splunk Observability Cloud Developer Guide.

alerts-detectors-notifications/slo/custom-metric-scenario.rst

@@ -8,6 +8,8 @@ Introduction to Splunk APM
 
 Collect :ref:`traces and spans<apm-traces-spans>` to monitor your distributed applications with Splunk Application Performance Monitoring (APM). A trace is a collection of actions, or spans, that occur to complete a transaction. Splunk APM collects and analyzes every span and trace from each of the services that you have connected to Splunk Observability Cloud to give you full-fidelity access to all of your application data.
 
+To keep up to date with changes in APM, see the Splunk Observability Cloud :ref:`release notes <release-notes-overview>`.
+
 For scenarios using Splunk APM, see :ref:`apm-scenarios-intro`.
 
 .. raw:: html

apm/intro-to-apm.rst

@@ -259,6 +259,12 @@ Collect traces :ref:`get-started-cpp`
 :strong:`All supported integrations`
 View a list of all supported integrations :ref:`supported-data-sources`
 
+.. role:: icon-info
+.. rst-class:: newparawithicon
+
+:icon-info:`.` :strong:`Release notes`
+To keep up to date with changes in the products, see the Splunk Observability Cloud :ref:`release notes <release-notes-overview>`.
+
 .. ----- This comment separates the landing page from the TOC -----
 
 .. toctree::
@@ -886,7 +892,13 @@ View a list of all supported integrations :ref:`supported-data-sources`
 .. toctree::
    :maxdepth:   3
 
-   Integrations with Splunk On-Call TOGGLE <sp-oncall/spoc-integrations/integrations-main>   
+   Integrations with Splunk On-Call TOGGLE <sp-oncall/spoc-integrations/integrations-main>
+
+.. toctree::
+   :caption: Release notes
+   :maxdepth:   3
+
+   Release notes overview TOGGLE <release-notes/release-notes-overview.rst>   
 
 .. toctree::
    :caption: Reference and Legal

index.rst

@@ -10,6 +10,7 @@ Introduction to Splunk Infrastructure Monitoring
 
 Gain insights into and perform powerful, capable analytics on your infrastructure and resources across hybrid and multi-cloud environments with Splunk Infrastructure Monitoring. Infrastructure Monitoring offers support for a broad range of integrations for collecting all kinds of data, from system metrics for infrastructure components to custom data from your applications.
 
+To keep up to date with changes in Infrastructure Monitoring, see the Splunk Observability Cloud :ref:`release notes <release-notes-overview>`.
 
 ==========================================================
 Splunk Infrastructure Monitoring hierarchy

infrastructure/intro-to-infrastructure.rst

@@ -79,3 +79,4 @@ Splunk Log Observer Connect
 
 - :ref:`lo-connect-limits`
 
+To keep up to date with changes in Log Observer Connect, see the Splunk Observability Cloud :ref:`release notes <release-notes-overview>`.

logs/lo-connect-landing.rst

@@ -23,6 +23,12 @@ A
    analytics
       Analytics are the mathematical functions that can be applied to a collection of data points. For a full list of analytics that can be applied in Splunk Infrastructure Monitoring, see the :ref:`analytics-ref`.
 
+   automatic discovery
+      Automatic discovery is a feature of the Splunk Distribution of the OpenTelemetry Collector that identifies the services, such as third-party databases and web servers, running in your environment and sends telemetry data from them to Splunk Application Performance Monitoring (APM) and Infrastructure Monitoring. The Collector configures service-specific receivers that collect data from an endpoint exposed on each service. For more information, see :ref:`discovery_mode`.
+
+   automatic instrumentation
+      Automatic instrumentation allows you to instrument your applications and export telemetry data without having to modify the application source files. The language-specific instrumentation agent configures the source application to export data in a supported format to an OTLP endpoint, on either an OTLP receiver or the Splunk Observability Cloud back end. Automatic instrumentation is available for applications written in Java, Node.js, .NET, Go, Python, Ruby, and PHP and automatically collects telemetry data for code written using supported libraries in each language. For more information, see :ref:`get-started-application`.
+
 C
 ==
 

references/glossary.rst

@@ -0,0 +1,69 @@
+.. _2024-10-01-rn:
+
+***************
+October 1, 2024
+***************
+
+Splunk Observability Cloud released the following new features and enhancements on October 1, 2024. This is not an exhaustive list of changes in the observability ecosystem. For a detailed breakdown of changes in versioned components, see the :ref:`list of changelogs <changelogs>`.
+
+.. _loc-2024-10-01:
+
+Log Observer Connect
+====================
+
+.. list-table::
+   :header-rows: 1
+   :widths: 1 2
+   :width: 100%
+
+   * - New feature or enhancement
+     - Description
+   * - Splunk virtual compute (SVC) optimization
+     - You can optimize SVC, resulting in performance improvements and cost savings, by using new :guilabel:`Play`, :guilabel:`Pause`, and :guilabel:`Run` search buttons in the UI. The default limit is 150,000 logs. For more information, see :ref:`logs-keyword`.
+
+.. _ingest-2024-20-01:
+
+Data ingest
+===========
+
+.. list-table::
+   :header-rows: 1
+   :widths: 1 2
+   :width: 100%
+
+   * - New feature or enhancement
+     - Description
+   * - Kubernetes control plane metrics
+     - In a continued effort to replace Smart Agent monitors with OpenTelemetry Collector receivers, a collection of Kubernetes control plane metrics are available using OpenTelemetry Prometheus receivers that target Prometheus endpoints. For more information see :ref:`kubernetes-control-plane-prometheus`.
+
+.. _data-mngt-2024-10-01:
+
+Data management
+===============
+
+.. list-table::
+   :header-rows: 1
+   :widths: 1 2
+   :width: 100%
+
+   * - New feature or enhancement
+     - Description
+   * - Data retention for archived metrics extended from 8 to 31 days
+     - To facilitate long-term data and historical trend analysis, you can store archived metrics for up to 31 days. You can also customize your restoration time window when creating exception rules.
+   * - Terraform implementation
+     - You can use Terraform to archive metrics and create exception rules, such as routing a subset of metrics to the real-time tier rather than the archival tier.
+
+.. _slo-2024-10-01:
+
+Service level objective (SLO)
+=============================
+
+.. list-table::
+   :header-rows: 1
+   :widths: 1 2
+   :width: 100%
+
+   * - New feature or enhancement
+     - Description
+   * - SignalFlow editor for custom metrics SLO
+     - You can use SignalFlow to define metrics and filters when creating a custom metric SLO. For more information, see :ref:`create-slo`. The feature released on October 2, 2024.