Merge pull request #53765 from weslbo/DP-750-updates

DP-750 videos

Author: Carolyn135

learn-pr/wwl-databricks/implement-development-lifecycle-processes-in-azure-databricks/6-deploy-bundle-databricks-cli.yml

@@ -3,7 +3,7 @@ uid: learn.wwl.implement-development-lifecycle-processes-azure-databricks.deploy
 title: Deploy bundle with Databricks CLI
 metadata:
   title: Deploy Bundle with Databricks CLI
-  description: Learn how to deploy data asset bundles to Azure Databricks using CLI commands, including validation, deployment planning, and troubleshooting common issues.
+  description: Learn how to deploy data asset bundles to Azure Databricks using CLI commands, include validation, deployment planning, and troubleshoot common issues.
   ms.date: 03/09/2026
   author: weslbo
   ms.author: wedebols

learn-pr/wwl-databricks/monitor-troubleshoot-optimize-workloads-azure-databricks/1-introduction.yml

@@ -4,7 +4,7 @@ title: Introduction
 metadata:
   title: Introduction
   description: "Introduction to monitoring, troubleshooting, and optimizing workloads in Azure Databricks"
-  ms.date: 12/07/2025
+  ms.date: 03/10/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit

learn-pr/wwl-databricks/monitor-troubleshoot-optimize-workloads-azure-databricks/2-monitor-manage-cluster-consumption.yml

@@ -4,7 +4,7 @@ title: Monitor and manage cluster consumption
 metadata:
   title: Monitor and Manage Cluster Consumption
   description: Learn how to monitor and manage cluster consumption in Azure Databricks to optimize performance and cost using metrics, auto-termination, autoscaling, and budgets.
-  ms.date: 12/07/2025
+  ms.date: 03/10/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit

learn-pr/wwl-databricks/monitor-troubleshoot-optimize-workloads-azure-databricks/3-troubleshoot-repair-lakeflow-jobs.yml

@@ -4,7 +4,7 @@ title: Troubleshoot and repair Lakeflow Jobs
 metadata:
   title: Troubleshoot and Repair Lakeflow Jobs
   description: Learn how to troubleshoot, repair, restart, and stop Lakeflow Jobs in Azure Databricks to maintain reliable data pipelines.
-  ms.date: 12/07/2025
+  ms.date: 03/10/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit

learn-pr/wwl-databricks/monitor-troubleshoot-optimize-workloads-azure-databricks/4-troubleshoot-repair-spark-jobs-notebooks.yml

@@ -4,7 +4,7 @@ title: Troubleshoot Spark jobs and notebooks
 metadata:
   title: Troubleshoot Spark Jobs and Notebooks
   description: Learn how to troubleshoot and repair Apache Spark jobs and notebooks in Azure Databricks, including diagnosing performance issues, resolving resource bottlenecks, and restarting clusters.
-  ms.date: 12/07/2025
+  ms.date: 03/10/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit

learn-pr/wwl-databricks/monitor-troubleshoot-optimize-workloads-azure-databricks/5-resolve-cache-skew-spill-shuffle.yml

@@ -4,7 +4,7 @@ title: Investigate caching, skewing, spilling, shuffle
 metadata:
   title: Investigate Caching, Skewing, Spilling, Shuffle
   description: Learn how to investigate and resolve caching, skewing, spilling, and shuffle issues in Azure Databricks using the DAG, Spark UI, and query profile.
-  ms.date: 12/07/2025
+  ms.date: 03/10/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit

learn-pr/wwl-databricks/monitor-troubleshoot-optimize-workloads-azure-databricks/6-implement-log-streaming-azure-analytics.yml

@@ -4,7 +4,7 @@ title: Implement log streaming with Azure Log Analytics
 metadata:
   title: Implement Log Streaming with Azure Log Analytics
   description: Learn how to implement log streaming from Azure Databricks to Azure Log Analytics for centralized monitoring, querying with KQL, and creating alerts for proactive troubleshooting.
-  ms.date: 12/07/2025
+  ms.date: 03/10/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit

learn-pr/wwl-databricks/monitor-troubleshoot-optimize-workloads-azure-databricks/7-knowledge-check.yml

@@ -4,7 +4,7 @@ title: Module assessment
 metadata:
   title: Module assessment
   description: "Knowledge check"
-  ms.date: 12/07/2025
+  ms.date: 03/10/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit

learn-pr/wwl-databricks/monitor-troubleshoot-optimize-workloads-azure-databricks/8-summary.yml

@@ -4,7 +4,7 @@ title: Summary
 metadata:
   title: Summary
   description: "Summary"
-  ms.date: 12/07/2025
+  ms.date: 03/10/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit

learn-pr/wwl-databricks/monitor-troubleshoot-optimize-workloads-azure-databricks/includes/1-introduction.md

@@ -1,3 +1,5 @@
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=aafb4cc3-3e5a-4168-8e10-d78366db752c]
+
 Running data workloads in Azure Databricks at scale requires more than setting up clusters and writing pipelines—it demands continuous attention to resource consumption, job health, and performance optimization. When compute costs climb unexpectedly, jobs fail without clear explanations, or queries that once ran quickly now take hours, you need systematic approaches to identify problems and apply targeted fixes.
 
 Azure Databricks provides comprehensive tools for monitoring and troubleshooting across all compute types. **Cluster metrics** reveal CPU, memory, and network utilization patterns that help you right-size resources. **The Spark UI** exposes job execution details, stage-level metrics, and task distributions that pinpoint bottlenecks. **System tables** enable you to query billing data and usage patterns directly, supporting cost attribution and chargeback processes.