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

Production-ready

✓ Instant download✓ Lifetime updates✓ MIT licensed✓ MIT license✓ Secure checkout (Stripe)

📋 What's Inside 15 files

✓ README.md—
✓ manifest.json—
✓ dashboards/pipeline_health.sql—
✓ dashboards/cluster_utilization.sql—
✓ dashboards/job_failure_analysis.sql—
✓ dashboards/cost_trends.sql—
✓ dashboards/user_activity.sql—
✓ dashboards/data_freshness.sql—
✓ dashboards/query_performance.sql—
✓ dashboards/capacity_planning.sql—
✓ alerts/alert_definitions.sql—
✓ alerts/webhook_templates.json—
✓ queries/system_table_library.sql—
✓ templates/monthly_health_report.md—
✓ runbooks/common_operations.md—

📁 File Structure 15 files

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

Dashboard	Description
Pipeline Health	Success rates, failure trends, duration tracking across all pipelines
Cluster Utilization	CPU, memory, idle time, and cost attribution per cluster
Job Failure Analysis	Error categorization, root cause patterns, failure heatmaps
Cost Trends	Daily/weekly/monthly DBU spend broken down by team, workspace, SKU
User Activity	Active users, notebook execution patterns, query frequency analysis
Data Freshness	Table update timestamps vs SLA targets with breach detection
Query Performance	SQL warehouse query latency, throughput, and optimization signals
Capacity Planning	Growth 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


... preview truncated, see full README in product download.

`📄 Code Sample .sql preview`

dashboards/pipeline_health.sql-- ============================================================================
-- Pipeline Health Dashboard
-- Databricks Monitoring & Alerting Suite
-- Author: Datanest Digital (https://datanest.dev)
-- ============================================================================
-- This dashboard provides visibility into pipeline execution health including
-- success/failure rates, duration trends, and reliability metrics.
-- Prerequisites: Access to system.workflow tables and Unity Catalog.
-- ============================================================================

-- ---------------------------------------------------------------------------
-- Widget 1: Pipeline Execution Summary (Last 24 Hours)
-- ---------------------------------------------------------------------------
SELECT
  result_state,
  COUNT(*) AS run_count,
  ROUND(COUNT(*) * 100.0 / SUM(COUNT(*)) OVER (), 2) AS pct_of_total,
  ROUND(AVG(execution_duration / 1000.0), 1) AS avg_duration_sec,
  ROUND(MAX(execution_duration / 1000.0), 1) AS max_duration_sec
FROM system.lakeflow.job_run_timeline
WHERE
  period_start_time >= CURRENT_TIMESTAMP() - INTERVAL 24 HOURS
  AND result_state IS NOT NULL
GROUP BY result_state
ORDER BY run_count DESC;

-- ---------------------------------------------------------------------------
-- Widget 2: Daily Success Rate (Last 30 Days)
-- ---------------------------------------------------------------------------
SELECT
  DATE(period_start_time) AS run_date,
  COUNT(*) AS total_runs,
  SUM(CASE WHEN result_state = 'SUCCESS' THEN 1 ELSE 0 END) AS successful,
  SUM(CASE WHEN result_state != 'SUCCESS' THEN 1 ELSE 0 END) AS failed,
  ROUND(
    SUM(CASE WHEN result_state = 'SUCCESS' THEN 1 ELSE 0 END) * 100.0 / COUNT(*),
    2
  ) AS success_rate_pct
FROM system.lakeflow.job_run_timeline
WHERE

`📅 Changelog`

v1.0.0 — Initial release.

Purchases include lifetime updates. Check the product page for the latest version.

`📄 Product Preview`

Try the interactive reader and demo tools below, or get the full product with all content unlocked.

📖 Interactive Reader (Free Preview)⚙ Try Demo Tools📦 Download Free Sample

`❓ Frequently Asked Questions`

What license is this under?

MIT License. You can use it in commercial, client, and internal projects. See our license terms page for details.

How do I download after purchase?

Immediately after purchase, you'll be redirected to a download page. A download link is also sent to your email.

Do I get updates?

Yes. All products include lifetime updates at no extra cost. Re-download anytime for the latest version.

What if it doesn't work for me?

DM @DatanestDigital on X and we'll make it right.

Can I get a refund?

DM @DatanestDigital on X with your order number and we'll help.

Is there support?

DM @DatanestDigital on X. We respond within 1-2 business days.



      
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