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Databricks Monitoring & Alerting Suite

$59

Complete monitoring and observability setup with 8 SQL dashboards, alert definitions, webhook templates, and 50+ system table queries.

📁 15 files🏷 v1.0.0
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📁 File Structure 15 files

databricks-monitoring-suite/ ├── README.md ├── alerts/ │ ├── alert_definitions.sql │ └── webhook_templates.json ├── dashboards/ │ ├── capacity_planning.sql │ ├── cluster_utilization.sql │ ├── cost_trends.sql │ ├── data_freshness.sql │ ├── job_failure_analysis.sql │ ├── pipeline_health.sql │ ├── query_performance.sql │ └── user_activity.sql ├── queries/ │ └── system_table_library.sql ├── runbooks/ │ └── common_operations.md └── templates/ └── monthly_health_report.md

📖 Documentation Preview README excerpt

Databricks Monitoring & Alerting Suite

Version: 1.0.0

Author: [Datanest Digital](https://datanest.dev)

Price: $59

Category: Databricks

Overview

A comprehensive, production-ready monitoring and alerting toolkit for Databricks workspaces. This suite provides 8 SQL dashboards, configurable alert definitions, 50+ pre-built system table queries, webhook integrations, report templates, and operational runbooks -- everything you need to achieve full observability over your Databricks environment.

What's Included

Dashboards (8)

DashboardDescription
Pipeline HealthSuccess rates, failure trends, duration tracking across all pipelines
Cluster UtilizationCPU, memory, idle time, and cost attribution per cluster
Job Failure AnalysisError categorization, root cause patterns, failure heatmaps
Cost TrendsDaily/weekly/monthly DBU spend broken down by team, workspace, SKU
User ActivityActive users, notebook execution patterns, query frequency analysis
Data FreshnessTable update timestamps vs SLA targets with breach detection
Query PerformanceSQL warehouse query latency, throughput, and optimization signals
Capacity PlanningGrowth projections, resource demand forecasting, headroom analysis

Alerts

  • Alert Definitions -- SQL-based alert rules for job failures, cost spikes, idle clusters, SLA breaches, and more
  • Webhook Templates -- Ready-to-use payload templates for Slack, Microsoft Teams, PagerDuty, and email

Queries

  • System Table Library -- 50+ pre-built queries against system.billing, system.access, system.compute, and related tables covering billing analysis, access auditing, compute profiling, and operational diagnostics

Templates & Runbooks

  • Monthly Health Report -- Markdown template with embedded query references for generating executive-level monthly reports
  • Common Operations Runbook -- Step-by-step procedures for incident response, cost optimization, capacity management, and access review

Prerequisites

  • Databricks workspace with Unity Catalog enabled
  • Access to [system tables](https://docs.databricks.com/en/administration-guide/system-tables/index.html) (system.billing, system.access, system.compute)
  • SQL warehouse (Serverless or Pro recommended)
  • Databricks SQL Alerts & Dashboards feature enabled

Quick Start

1. Import Dashboards -- Open each .sql file in dashboards/ and create a new Databricks SQL dashboard with the queries

2. Configure Alerts -- Run alerts/alert_definitions.sql to create alert rules, then configure destinations using the webhook templates in alerts/webhook_templates.json

3. Explore Queries -- Use queries/system_table_library.sql as a reference library; copy individual queries into notebooks or dashboards as needed

4. Schedule Reports -- Adapt templates/monthly_health_report.md to your organization and schedule the underlying queries

5. Adopt Runbooks -- Customize runbooks/common_operations.md with your team's escalation paths and thresholds

File Structure



*... continues with setup instructions, usage examples, and more.*

📄 Code Sample .sql preview

alerts/alert_definitions.sql -- ============================================================================ -- Alert Definitions -- Databricks Monitoring & Alerting Suite -- Author: Datanest Digital (https://datanest.dev) -- ============================================================================ -- SQL alert queries for Databricks SQL Alerts. Each query is designed to -- return rows only when the alert condition is met. Configure each as a -- Databricks SQL Alert with the specified trigger condition. -- ============================================================================ -- ========================================================================= -- ALERT 1: Job Failure Spike -- Trigger: When failure count in last hour exceeds threshold. -- Suggested schedule: Every 15 minutes -- Trigger condition: Rows > 0 -- ========================================================================= -- Alert: job_failure_spike SELECT COUNT(*) AS failures_last_hour, 5 AS threshold, CURRENT_TIMESTAMP() AS alert_time FROM system.lakeflow.job_run_timeline WHERE period_start_time >= CURRENT_TIMESTAMP() - INTERVAL 1 HOUR AND result_state = 'FAILED' HAVING COUNT(*) > 5; -- ========================================================================= -- ALERT 2: Critical Job Failure -- Trigger: When a specific critical job fails. -- Suggested schedule: Every 5 minutes -- Trigger condition: Rows > 0 -- Customize the job_id list for your critical pipelines. -- ========================================================================= -- Alert: critical_job_failure SELECT job_id, run_id, result_state, error_message, period_start_time AS failure_time FROM system.lakeflow.job_run_timeline WHERE period_start_time >= CURRENT_TIMESTAMP() - INTERVAL 10 MINUTES AND result_state = 'FAILED' AND job_id IN ( -- Replace with your critical job IDs 0 -- placeholder ); # ... 219 more lines ...
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