Application Insights SDK stats publishes per-process success, dropped-item and retry counters. Retry counts represent attempts and never decrease when those items later succeed; later delivery appears in the success series. The workbook calculates drop rate from dropped items divided by dropped plus successful items. An ingestion response of 206 can split one batch between accepted and rejected items, counted separately. Sampling, aggregation intervals and delayed buffering also prevent a simple equality with request-table row counts. Microsoft Learn.
\nCheck the application’s SDK or exporter against the documented version prerequisites. Identify service instance, telemetry type, time grain and metric-name generation before combining counters. Microsoft documents different metric names for preview and generally available SDK stats; an upgrade review should account for mixed versions.
\nCorrelate retry attempts with success and dropped-item series before declaring telemetry loss. Keep retry volume distinct from a final delivery outcome in operational dashboards. When drops persist, inspect their codes and exporter logs rather than increasing retries indiscriminately. Separate application-level request success from exporter delivery success, and explain which one each chart describes. Use aligned observation intervals when comparing sources.
\nExercise a controlled delivery interruption in a test application and observe retries, later successes and any drops. Confirm that successful recovery does not require the historical retry counter to fall. For partial ingestion, examine item-level rejection evidence instead of treating the entire batch as accepted or lost. Retain the relevant dimensions and version so another reviewer can reproduce the interpretation without relying on the chart’s label alone.
\nMicrosoft Learn: SDK stats in Azure Monitor Application Insights. Source reviewed September 9, 2026.
", "content_text": "Source facts\nApplication Insights SDK stats publishes per-process success, dropped-item and retry counters. Retry counts represent attempts and never decrease when those items later succeed; later delivery appears in the success series. The workbook calculates drop rate from dropped items divided by dropped plus successful items. An ingestion response of 206 can split one batch between accepted and rejected items, counted separately. Sampling, aggregation intervals and delayed buffering also prevent a simple equality with request-table row counts. Microsoft Learn.\nApplicability\nCheck the application’s SDK or exporter against the documented version prerequisites. Identify service instance, telemetry type, time grain and metric-name generation before combining counters. Microsoft documents different metric names for preview and generally available SDK stats; an upgrade review should account for mixed versions.\nDSE recommendation\nCorrelate retry attempts with success and dropped-item series before declaring telemetry loss. Keep retry volume distinct from a final delivery outcome in operational dashboards. When drops persist, inspect their codes and exporter logs rather than increasing retries indiscriminately. Separate application-level request success from exporter delivery success, and explain which one each chart describes. Use aligned observation intervals when comparing sources.\nVerification\nExercise a controlled delivery interruption in a test application and observe retries, later successes and any drops. Confirm that successful recovery does not require the historical retry counter to fall. For partial ingestion, examine item-level rejection evidence instead of treating the entire batch as accepted or lost. Retain the relevant dimensions and version so another reviewer can reproduce the interpretation without relying on the chart’s label alone.\nOfficial references\nMicrosoft Learn: SDK stats in Azure Monitor Application Insights. Source reviewed September 9, 2026.", "content_markdown": "## Source facts\n\nApplication Insights SDK stats publishes per-process success, dropped-item and retry counters. Retry counts represent attempts and never decrease when those items later succeed; later delivery appears in the success series. The workbook calculates drop rate from dropped items divided by dropped plus successful items. An ingestion response of 206 can split one batch between accepted and rejected items, counted separately. Sampling, aggregation intervals and delayed buffering also prevent a simple equality with request-table row counts. [Microsoft Learn](https://learn.microsoft.com/en-us/azure/azure-monitor/app/sdk-stats).\n\n## Applicability\n\nCheck the application’s SDK or exporter against the documented version prerequisites. Identify service instance, telemetry type, time grain and metric-name generation before combining counters. Microsoft documents different metric names for preview and generally available SDK stats; an upgrade review should account for mixed versions.\n\n## DSE recommendation\n\nCorrelate retry attempts with success and dropped-item series before declaring telemetry loss. Keep retry volume distinct from a final delivery outcome in operational dashboards. When drops persist, inspect their codes and exporter logs rather than increasing retries indiscriminately. Separate application-level request success from exporter delivery success, and explain which one each chart describes. Use aligned observation intervals when comparing sources.\n\n## Verification\n\nExercise a controlled delivery interruption in a test application and observe retries, later successes and any drops. Confirm that successful recovery does not require the historical retry counter to fall. For partial ingestion, examine item-level rejection evidence instead of treating the entire batch as accepted or lost. Retain the relevant dimensions and version so another reviewer can reproduce the interpretation without relying on the chart’s label alone.\n\n## Official references\n\n[Microsoft Learn: SDK stats in Azure Monitor Application Insights](https://learn.microsoft.com/en-us/azure/azure-monitor/app/sdk-stats). 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Retry counts represent attempts and never decrease when those items later succeed; later delivery appears in the success series. The workbook calculates drop rate from dropped items divided by dropped plus successful items. An ingestion response of 206 can split one batch between accepted and rejected items, counted separately. Sampling, aggregation intervals and delayed buffering also prevent a simple equality with request-table row counts. Microsoft Learn.\nApplicability\nCheck the application’s SDK or exporter against the documented version prerequisites. Identify service instance, telemetry type, time grain and metric-name generation before combining counters. Microsoft documents different metric names for preview and generally available SDK stats; an upgrade review should account for mixed versions.\nDSE recommendation\nCorrelate retry attempts with success and dropped-item series before declaring telemetry loss. Keep retry volume distinct from a final delivery outcome in operational dashboards. When drops persist, inspect their codes and exporter logs rather than increasing retries indiscriminately. Separate application-level request success from exporter delivery success, and explain which one each chart describes. Use aligned observation intervals when comparing sources.\nVerification\nExercise a controlled delivery interruption in a test application and observe retries, later successes and any drops. Confirm that successful recovery does not require the historical retry counter to fall. For partial ingestion, examine item-level rejection evidence instead of treating the entire batch as accepted or lost. Retain the relevant dimensions and version so another reviewer can reproduce the interpretation without relying on the chart’s label alone.\nOfficial references\nMicrosoft Learn: SDK stats in Azure Monitor Application Insights. 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All rights reserved.", "citation": { "@type": "CreativeWork", "name": "Software Development Kit (SDK) stats in Azure Monitor Application Insights - Azure Monitor | Microsoft Learn", "url": "https://learn.microsoft.com/en-us/azure/azure-monitor/app/sdk-stats" } } ] } }