> ## Documentation Index > Fetch the complete documentation index at: https://docs.chronosphere.io/llms.txt > Use this file to discover all available pages before exploring further. # Analyze live traffic metrics The Live Telemetry Analyzer provides a real-time view of incoming metrics grouped by label, and their relative frequency. This view helps you understand how often your applications emit metrics, troubleshoot spikes in ingest rates, and ensure that the Chronosphere Collector is aware of particular metrics. Use the metrics telemetry analyzer as a first step in identifying opportunities to reduce the overall volume of metrics. Chronosphere Observability Platform adaptively adjusts the metrics sampling rate based on the current workload. This behavior means that not all metrics are immediately visible in the Live Telemetry Analyzer. [See a demo of the live telemetry analyzer.](https://app.teamwalnut.com/player/?demoId=bc370030-8fed-44bd-a261-6328bac9a00c\&screenId=b6aa4c42-4aa8-48fd-9a2a-23d3553263c9\&showGuide=true\&showGuidesToolbar=false\&showHotspots=true\&source=app) ## Capture and analyze live profiling data To use the metrics telemetry analyzer to capture live profiling data: 1. In the navigation menu, click ** Go to Admin** and then select ** Analyzers > Live Telemetry**. 2. Click either the **Metrics** or **Traces** tab, depending on the data you want to profile. 3. Click **Capture live data** to begin gathering statistics for data that Observability Platform accepted for matching. Two tables display with the following columns: * **Unique Values:** Number of unique values for the respective label key. * **Appears In:** The percentage of metrics you're viewing that have the matching label key. * **Avg. DPPS:** Average data points per second (DPPS), calculated over the previous 15 seconds. * **Current DPPS:** Current data points per second. You can make changes to the [groupings and filters](#group-and-filter-metrics) while profiling. 4. To modify the displayed data, select an option from the **Data phase** menu to show data in [different stages](#ingestion-stages-and-phases) along the pathway from ingestion to persistence. For example, select **Rejected by drop rule** to view all data that Observability Platform dropped because of a configured drop rule. 5. To display data for a specific pool only, select a pool from the **Pool** menu to choose a specific [metric pool](/control/shaping/shape-metrics/quotas/quotas-ui). Use the **Priority** menu to narrow the filter to a specific pool priority. To filter on specific labels, start typing a label name in the **Add Label Filter** text box, choose from an autocomplete list of labels, and then add a value to filter for a specific label. ### Analyze metrics When analyzing traffic, use the following methods to help narrow your analysis and find the information you need: * Review the metric names that generate the most data points per second (**Avg. DPPS** or **Current DPPS**). If those metrics are unfamiliar to you or are expensive, these might be candidates to [roll up](/control/shaping/shape-metrics/rules/rollup) or [drop](/control/shaping/shape-metrics/rules/drop-rules). * Ensure your drop and rollup rules are working as expected by reviewing your rolled up metrics, or ensuring that a dropped metric no longer displays. * [Group metrics](#group-and-filter-metrics) by job to identify the specific scrape jobs generating the most metrics. Filter for each job, and analyze the job's individual metrics to find opportunities for reduction. Metrics from the same job are often used together, letting you investigate metrics from a single job more quickly. * Review metrics isolated to single environments. For example, metrics available only in development or production environment metrics. These are likely to have different metric workload shapes from each other. ### Ingestion stages and phases Chronosphere Observability Platform profiles metrics in the following stages, which display in Live Telemetry Analyzer, in the **Data phase** menu: **Ingestion:** Metrics sent directly from the Chronosphere Collector. Ingestion includes these phases: * **Received:** Not selectable. * **Rejected By Drop Rule:** Toggle metrics dropped due to [drop rules](/control/shaping/shape-metrics/rules/drop-rules). This option is relevant only for the Ingestion phase. * **Rejected by Ingest limit:** Metrics that dropped due to exceeding the ingestion or persistence phase rate limit. * **Accepted for Matching:** Metrics which aren't dropped prior to ingestion. **Aggregation:** Metrics matching to existing aggregation rules. Select **Matched for aggregation** to focus on metrics that match an [aggregation rule](/control/shaping/shape-metrics/rules/rollup) before persisting data. To view samples of that traffic, see [Inspect matched data for aggregation](#inspect-matched-data-for-aggregation). **Persistence:** Metrics sent to the database. This stage includes aggregated metrics and the following phases: * **Rejected by Persist limit:** Metrics not sent to permanent storage due to persistence limits. * **Accepted for Storage:** Metrics sent to storage. * **Stored:** Not selectable. ### Special request metadata The Live Telemetry Analyzer generates rows for the following special non-label request metadata. This special non-label request metadata is available in the Live Telemetry Analyzer and for matching in rollup rules, but isn't stored. The following label keys display for all incoming metrics: * `__metric_type__` displays on the incoming metric's [Chronosphere metric type](/control/shaping/shape-metrics/types#observability-platform-types). Valid values are `cumulative_counter`, `delta_counter`, `gauge`, or `measurement`. This is the recommended method for determining an incoming metric's type. * `__metric_source__` displays on the incoming metric's [source format](/control/shaping/shape-metrics/types#supported-formats). Valid values are `carbon`, `chrono_gcp`, `cloudwatch_metric_stream`, `dogstatsd`, `open_metrics`, `open_telemetry`, `prometheus`, `signalfx`, `statsd`, or `wavefront`. When ingesting data with Prometheus, the following label keys display: * `__m3_prom_type__` displays the incoming metric's [Prometheus metric type](/control/shaping/shape-metrics/types#prometheus). Valid values are `counter`, `gauge`, `histogram`, `gauge_histogram`, `summary`, `info`, `state_set`, or `quantile`. When ingesting data with OpenTelemetry, the following label keys display: * `__otel_type__` displays the incoming metric's [OpenTelemetry metric type](/control/shaping/shape-metrics/types#opentelemetry). Valid values are `sum`, `monotonic_sum`, `gauge`, `histogram`, `exp_histogram`, or `summary`. * `__otel_temporality__` displays the incoming metric's [OpenTelemetry temporality](/control/shaping/shape-metrics/types#opentelemetry). Valid values are `delta` or `cumulative`. * DEPRECATED: `__m3_type__` displays on the incoming metric's legacy M3 type, if any. Valid values are `counter`, `gauge`, or `timer`. ## Inspect matched data for aggregation In Live Telemetry Analyzer, the aggregation stage provides deeper visibility into how data is matched to aggregation rules for improved debugging and validation. Live Telemetry Analyzer adds dimensions such as `__rollup_name__` and `__rollup_rule_slug__` in this phase so you can relate samples back to the series being matched that go into rules. This behavior is similar to how you use `__rollup_rule_slug__` under **Accepted for storage** when [identifying rules that generate metrics](#identify-rules-that-generate-metrics). The **Label values** tab summarizes how often each label value appears. You can still use [groupings and filters](#group-and-filter-metrics) from the **Labels** and **Label values** tables while **Matched for aggregation** is selected. To capture and review samples: 1. In the navigation menu, click ** Go to Admin** and then select ** Analyzers > Live Telemetry**. 2. Select the **Metrics** tab, and click **Capture live data**. 3. In the **Data phase** menu, under **Aggregation**, select **Matched for aggregation**. 4. To add data to the table, type in the **Filter** field using `key=value` pairs. ## Group and filter metrics The initial view displays two tables, which list all labels for all metrics. The **Labels** table lists all labels collected during the capture. Use the **Search** text box to find a specific label. The **Search** text box filters as you type, reducing the label list displayed. Live Telemetry Analyzer uses [glob syntax](/investigate/querying/glob-syntax). Observability Platform glob syntax doesn't support using two asterisks where one of them is in the middle of a string. For example, `*k8s*staging` isn't valid. Select the checkbox next to any label to filter the **Label Values** table by the selected value. The right table shows the **Label Values**. Click a label value to add it to the **Add Label Filter** text box. Filter both tables by adding label `key:value` pairs to the **Add Label Filter** field by selecting them from the table on the left, or type in the field. Typing in the field displays a **Label** and **Value** text box. The **Label** field displays a matching list of label keys as you type. Select an option from the list at any time. Click the check icon when finished. Click any label value to edit it. Click the arrow in any of the columns to sort by that data to help interpret the results. For example, a high total percentage in the **Appears In** column with low unique values gives you a high-level breakdown of where to attribute metrics. You can also sort by the **Unique Values** column, which helps identify high-cardinality labels. Consider the following metrics as an example: ```text theme={null} sign_up{location="placeA"} sign_up{location="placeB"} login{version="v0.1.0"} ``` With these metrics, the Live Telemetry Analyzer generates three rows, based on the three labels: `__name__`, `location`, and `version`. Because every metric has a `__name__` label, the percentage for that label is 100%. There are only two unique values for `__name__`, which are `sign_up` and `login`, causing the **Unique Values** column to display `2`. Only two metrics have the `location` label, which is `66%`, and there are two unique values for this label (`placeA` and `placeB`). The same applies for `version`. | Label Keys | Unique Values | Appears In | | ---------- | ------------- | ---------- | | `__name__` | 2 | 100% | | `location` | 2 | 66% | | `version` | 1 | 33% | ## Identify rules that generate metrics When using the Live Telemetry Analyzer, you can view which metrics were rejected by a drop rule or impacted by an aggregation rule. You can also view the specific rollup rule or drop rule that caused a metric to be aggregated or dropped. Use this information to help understand why metrics are missing, and why results are formatted in a particular way. You can also click the rule name to go directly to the rule in Observability Platform. The Live Telemetry Analyzer displays all matching aggregation rules, which helps to identify duplicates. To understand which drop rules are dropping certain metrics: 1. In the **Data phase** menu, select **Rejected by drop rule**. 2. Under the **Labels** section, select the `__drop_rule_slug__` label. The drop rule slug names display in the **Label values** table. 3. Click the **** arrow icon to navigate directly to the drop rule that caused the metrics to be dropped. To understand which aggregation rules are producing aggregated metrics: 1. In the **Data phase** menu, select **Accepted for storage**. 2. Under the **Labels** section, select the `__rollup_rule_slug__` label. The aggregation rule slug names display in the **Label values** table. 3. Click the **** arrow icon to navigate directly to the aggregation rule that produced the aggregated metric. ## Troubleshoot missing metrics If metrics don't display when running the Live Telemetry Analyzer: * Examine the filters to ensure they're not dropping the metrics you're searching for. * Review the **Collectors** dashboard and ensure metrics are being scraped by the [Collectors](/ingest/metrics-traces/collector). * See [metric limits](/administer/limits-licensing/limits/metric-limits) for more information.