> ## Documentation Index > Fetch the complete documentation index at: https://docs.odigos.io/llms.txt > Use this file to discover all available pages before exploring further. # Azure Data Explorer > Configuring the Azure Data Explorer backend (Managed) ### Getting Started ![azuredataexplorer](https://d15jtxgb40qetw.cloudfront.net/azuremonitor.svg) Odigos uses the bundled OpenTelemetry `azuredataexplorer` exporter (v0.159.0) to send traces, metrics and logs over HTTPS using the Kusto ingestion SDK. This destination is separate from Azure Monitor/Application Insights. Profiles are unsupported. ### Prepare the database and tables Create an Azure Data Explorer cluster and a database named `oteldb` (or set your own Database). The exporter does not create databases or tables. Run these commands separately in the [Azure Data Explorer web UI](https://dataexplorer.azure.com): ```kql theme={null} .create-merge table OTELLogs (Timestamp:datetime, ObservedTimestamp:datetime, TraceID:string, SpanID:string, SeverityText:string, SeverityNumber:int, Body:string, ResourceAttributes:dynamic, LogsAttributes:dynamic) .create-merge table OTELMetrics (Timestamp:datetime, MetricName:string, MetricType:string, MetricUnit:string, MetricDescription:string, MetricValue:real, Host:string, ResourceAttributes:dynamic, MetricAttributes:dynamic) .create-merge table OTELTraces (TraceID:string, SpanID:string, ParentID:string, SpanName:string, SpanStatus:string, SpanStatusMessage:string, SpanKind:string, StartTime:datetime, EndTime:datetime, ResourceAttributes:dynamic, TraceAttributes:dynamic, Events:dynamic, Links:dynamic) ``` Use the cluster **query URI**, for example `https://mycluster.region.kusto.windows.net`, rather than an `ingest-` URI or an OTLP endpoint. The collector needs outbound HTTPS access to Entra authentication, the cluster's query/ingestion endpoints and the storage/queue endpoints used by queued ingestion. ### Authentication Choose one authentication mode: * `service_principal` (default): register an application in Microsoft Entra ID, enter its application/client ID and tenant ID, and supply the **client secret value**. Odigos stores the client secret in a Kubernetes Secret and uses a destination-scoped environment reference. Grant the principal **Database Ingestor** on the target database. A browser login alone does not provide collector credentials. * `managed_identity`: set `system` for a system-assigned identity or the client ID UUID of a user-assigned identity. The identity must be available to the collector's Azure runtime and have ingestion permissions. * `default`: use the Azure SDK default credential chain inside the collector. Configure its environment or workload identity externally; Odigos does not mount workload identity tokens or propagate browser/CLI credentials automatically. Grant that identity ingestion permissions. Only the chosen mode is emitted to the collector. Missing/invalid credentials fail collector validation or authentication. Creating tables and assigning permissions requires additional administrative privileges beyond ingestion. ### Queued and managed ingestion `queued` is the default and works without a streaming policy. Azure queues and batches ingestion asynchronously; exporter success only confirms acceptance into the ingestion path. Wait for the batch policy, query the destination tables, and inspect `.show ingestion failures` when rows do not appear. `managed` uses managed streaming ingestion with queued fallback. Enable streaming ingestion on the cluster and each selected table first: ```kql theme={null} .alter table OTELLogs policy streamingingestion enable .alter table OTELMetrics policy streamingingestion enable .alter table OTELTraces policy streamingingestion enable ``` Odigos enables a bounded exporter sending queue and retries for up to five minutes. These cannot detect every asynchronous queued-ingestion failure. Check destination-side failures for missing tables, invalid mappings and insufficient permissions. ### JSON mappings and signal conversions The exporter sends newline-delimited, gzip-compressed JSON rows in the schemas above, rather than raw OTLP envelopes. Attribute maps use Kusto `dynamic` columns; log bodies are converted to strings. Traces retain identifiers, status/message, attributes, events and links. Metrics support gauges, sums, explicit histograms and summaries. Histograms become count, sum and bucket rows; summaries become count, sum and quantile rows. **Exponential histogram metrics are dropped by v0.159.0**; convert them to explicit histograms before export if needed. Profiles are unsupported. Mapping fields take the **name** of an existing JSON ingestion mapping, not JSON itself. With the default schemas, leave them empty for identity mapping. For a custom schema, create a [JSON mapping](https://learn.microsoft.com/en-us/kusto/management/json-mapping) on each table, then enter its name. For example: ```kql theme={null} .create table OTELLogs ingestion json mapping 'otel_logs_mapping' '[{"column":"Timestamp","Properties":{"Path":"$.Timestamp"}},{"column":"Body","Properties":{"Path":"$.Body"}}]' ``` This example maps only timestamp and body; define every column you need in your custom mapping. ### Microsoft Fabric The same exporter supports Microsoft Fabric Real-Time Intelligence. Create an Eventhouse/KQL database and these tables, use its **query URI** and database name, and grant the selected Entra principal ingestion access. Streaming and mapping requirements still apply. Fabric compatibility is documented upstream; use the Azure Data Explorer destination for it. ### Verify ingestion Send multiple batches for each enabled signal and query the corresponding table, for example: ```kql theme={null} OTELTraces | where ResourceAttributes["service.name"] == "my-service" | take 10 OTELMetrics | where ResourceAttributes["service.name"] == "my-service" | take 10 OTELLogs | where ResourceAttributes["service.name"] == "my-service" | take 10 ``` Run each query separately. Verify trace IDs, metric values and log bodies. Test an invalid credential or mapping separately and confirm rejection/failure reporting before restoring valid settings. See [Microsoft's OpenTelemetry connector setup](https://learn.microsoft.com/en-us/azure/data-explorer/open-telemetry-connector) and the [pinned exporter documentation](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/v0.159.0/exporter/azuredataexplorerexporter) for deployment and schema requirements. ### Configuring Destination Fields > [accordion] Supported Signals: > > ✅ Traces > ✅ Metrics > ✅ Logs > ❌ Profiles * **AZURE\_DATA\_EXPLORER\_CLUSTER\_URI** `string` : Cluster Query URI. HTTPS query URI of the Azure Data Explorer cluster or Fabric Eventhouse. Do not use the ingest- URI. * This field is required * **AZURE\_DATA\_EXPLORER\_DATABASE** `string` : Database. An existing database containing the telemetry tables. * This field is required and defaults to `oteldb` * **AZURE\_DATA\_EXPLORER\_AUTH\_MODE** `string` : Authentication. Default credentials must be available inside the collector. Browser login credentials are not passed to Odigos. * This field is required and defaults to `service_principal` * **AZURE\_DATA\_EXPLORER\_APPLICATION\_ID** `string` : Application (Client) ID. * This field is required * **AZURE\_DATA\_EXPLORER\_TENANT\_ID** `string` : Tenant ID. * This field is required * **AZURE\_DATA\_EXPLORER\_APPLICATION\_KEY** `string` : Client Secret. * This field is required * **AZURE\_DATA\_EXPLORER\_MANAGED\_IDENTITY\_ID** `string` : Managed Identity Client ID. Use system for system-assigned identity or the client ID UUID of a user-assigned identity available to the collector. * This field is required * **AZURE\_DATA\_EXPLORER\_INGESTION\_TYPE** `string` : Ingestion Mode. Queued ingestion is asynchronous. Managed ingestion requires streaming enabled on the cluster and selected tables. * This field is required and defaults to `queued` * **AZURE\_DATA\_EXPLORER\_TRACES\_TABLE** `string` : Traces Table. * This field is required and defaults to `OTELTraces` * **AZURE\_DATA\_EXPLORER\_TRACES\_MAPPING** `string` : Traces JSON Mapping Name. Optional name of a pre-created JSON ingestion mapping, not mapping JSON. * This field is optional * **AZURE\_DATA\_EXPLORER\_METRICS\_TABLE** `string` : Metrics Table. * This field is required and defaults to `OTELMetrics` * **AZURE\_DATA\_EXPLORER\_METRICS\_MAPPING** `string` : Metrics JSON Mapping Name. Optional name of a pre-created JSON ingestion mapping, not mapping JSON. * This field is optional * **AZURE\_DATA\_EXPLORER\_LOGS\_TABLE** `string` : Logs Table. * This field is required and defaults to `OTELLogs` * **AZURE\_DATA\_EXPLORER\_LOGS\_MAPPING** `string` : Logs JSON Mapping Name. Optional name of a pre-created JSON ingestion mapping, not mapping JSON. * This field is optional > [!WARNING] > > Create the database and telemetry tables before exporting. Exponential histogram metrics and profiles are unsupported by the bundled exporter. Queued acceptance does not guarantee successful ingestion; check KQL results and ingestion failures. ### Adding Destination to Odigos There are two primary methods for configuring destinations in Odigos: ##### **Using the UI** **Step 1** Use the [Odigos CLI](https://docs.odigos.io/cli/odigos_ui.md) to access the UI ```bash theme={null} odigos ui ``` **Step 2** Click on `Add Destination`, select `Azure Data Explorer` and follow the on-screen instructions ##### **Using Kubernetes manifests** **Step 1** Save the YAML below to a file (e.g. `azuredataexplorer.yaml`) ```yaml theme={null} apiVersion: odigos.io/v1alpha1 kind: Destination metadata: name: azuredataexplorer-example namespace: odigos-system spec: data: AZURE_DATA_EXPLORER_APPLICATION_ID: AZURE_DATA_EXPLORER_AUTH_MODE: '' AZURE_DATA_EXPLORER_CLUSTER_URI: AZURE_DATA_EXPLORER_DATABASE: '' AZURE_DATA_EXPLORER_INGESTION_TYPE: '' AZURE_DATA_EXPLORER_LOGS_TABLE: '' AZURE_DATA_EXPLORER_MANAGED_IDENTITY_ID: AZURE_DATA_EXPLORER_METRICS_TABLE: '' AZURE_DATA_EXPLORER_TENANT_ID: AZURE_DATA_EXPLORER_TRACES_TABLE: '' # Note: The commented fields below are optional. # AZURE_DATA_EXPLORER_TRACES_MAPPING: # AZURE_DATA_EXPLORER_METRICS_MAPPING: # AZURE_DATA_EXPLORER_LOGS_MAPPING: destinationName: azuredataexplorer secretRef: name: azuredataexplorer-secret signals: - TRACES - METRICS - LOGS type: azuredataexplorer --- apiVersion: v1 data: AZURE_DATA_EXPLORER_APPLICATION_KEY: kind: Secret metadata: name: azuredataexplorer-secret namespace: odigos-system type: Opaque ``` **Step 2** Apply the YAML using `kubectl` ```bash theme={null} kubectl apply -f azuredataexplorer.yaml ``` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.