End-to-end Snowflake Observability is now generally available in Dynatrace

Dynatrace Snowflake Observability is now generally available, giving teams unified visibility into cost, performance, security, operations, and data quality through the Dynatrace Data Observability app. Guided onboarding, automated telemetry collection, and 14 ready-made dashboards help teams understand the health of their Snowflake environments from day one, with no blank-canvas setup required.

As enterprises expand their use of Snowflake for analytics, data pipelines, and AI workloads, the reliability, performance, quality, and cost of that data infrastructure increasingly affect the applications and business processes that depend on it. If the underlying data is stale, incomplete, delayed, unexpectedly changed, or unavailable, the AI applications built on it can fail even when the AI models function properly. That makes Snowflake observability part of a much larger AI observability story. Despite its critical role, Snowflake often remains a visibility gap, monitored but disconnected from precise, real-time, actionable business insights from Dynatrace end-to-end observability.

Performance bottlenecks often surface only after users complain. Unexpected warehouse consumption shows up in billing reports. Security findings are buried in separate tools. Understanding the root cause of an incident frequently means switching between Snowflake, monitoring tools, and spreadsheets while manually assembling the bigger picture.

That changes today with the general availability of Dynatrace Snowflake Observability.

Figure 1. The Overview screen of the Dynatrace Data Observability app with fleet-level KPI tiles and ready-made dashboards, provisioned automatically after setup.

Observability across your Snowflake estate

Once connected, Dynatrace automatically deploys dashboards across five critical observability domains:

• Costs
• Performance
• Security
• Operations
• Data Quality

Rather than starting with a blank canvas, teams gain immediate visibility into the areas that matter most.

How does Dynatrace help control Snowflake costs?

Snowflake efficiency directly impacts cloud spend, yet many organizations struggle to identify where they are consuming credits and whether governance controls are effective.

The Costs Monitoring dashboard helps teams move beyond historical spend analysis. It highlights warehouses without resource monitors, tracks consumption against configured limits, visualizes monitor health, and projects when available credits may be exhausted.

Figure 2. The Cost Monitoring dashboard shows where resource governance is and isn't in place and projects when limits will be reached.

Additional dashboards provide visibility into budget thresholds, organization-wide consumption trends, warehouse utilization, and idle resource patterns, giving FinOps and platform teams the context to act before costs become a problem.

Accelerate performance investigations

When query performance degrades, the real challenge is often finding where to start.

The Query Performance dashboard enables teams to move quickly from high-level account trends to warehouse-level investigation, surfacing query execution patterns, resource consumption, long-running workloads, and warehouse utilization in a single workflow.

Figure 3. The Query performance dashboard narrows a performance issue from account-wide trend to warehouse-level diagnosis - all without switching context.

Instead of manually combing through SQL histories, teams can use dashboard insights to help identify warehouses, users, tables, and databases contributing to performance issues.

Bring security insights into your operational workflow

Security insights frequently live outside operational workflows, making them difficult to consume continuously.

Dynatrace integrates Snowflake security telemetry directly into the observability experience. The following are continuously available alongside performance and cost insights:

• Trust Center findings
• Authentication health
• Failed login activity
• Administrative actions
• Privilege modifications
• User identity information

Figure 4. Six security dimensions in a single view - surfacing security-related telemetry and insights available from Snowflake.

This allows platform and security teams to make security posture an operational concern rather than an exercise reserved for quarterly audits. 

Surface silent data quality issues

Data quality problems rarely announce themselves loudly.

A stale dataset, missed ingestion, or unexpected schema modification can quietly disrupt analytics, reporting, and AI workloads long before anyone notices.

Figure 5. Data freshness gaps and schema change - the two leading causes of silent data quality failures - all within Dynatrace.

The Data Volume & Storage dashboard can help teams detect potential indicators of these issues by highlighting stale tables and surfacing schema changes together with responsible users and timestamps. When downstream issues appear, the necessary operational context is already available inside Dynatrace.

Built on open foundations

Dynatrace Snowflake Observability is powered by the open source Dynatrace Snowflake Observability Agent (DSOA).

The same agent, telemetry modules, and dashboard foundation used by the product experience remain publicly available and actively maintained through GitHub. Teams that prefer direct deployment or custom configurations can continue to leverage the open source project, while organizations looking for guided onboarding and a supported operational experience can use the Data Observability app as their preferred entry point.

This reflects a broader Dynatrace principle: open foundations with a first-class product experience on top. 

Connect Snowflake in minutes

Getting started with Snowflake observability should not require days of setup work. Dynatrace introduces a guided onboarding experience directly within the Data Observability app. The connection wizard walks teams through the entire process, making setup transparent while accommodating different operational requirements.

Organizations can choose between an automated deployment approach or manually executing the required Snowflake scripts when stricter change control processes are required. Before any action is taken, Dynatrace clearly shows what will be executed and verifies telemetry collection before completing onboarding. All monitoring modules are enabled automatically, and corresponding dashboards are provisioned immediately after setup.

Figure 6. The connection wizard makes the setup experience transparent - allowing you to see exactly which scripts run where.

The Snowflake agent runs directly inside your Snowflake account using a least-privilege service account. There is no external infrastructure to manage and no long-term elevated access requirements after deployment.

What's next

General availability establishes the foundation for broader data observability across the modern data stack.

Planned enhancements include:

• Granular control over individual monitoring modules after installation.
• Ready-made alert templates for critical Snowflake metrics and operational signals.

Looking further ahead, Dynatrace plans to extend visibility beyond the warehouse itself, connecting Snowflake activity with upstream pipelines and downstream applications, reports, and AI workloads that depend on the data flowing through it.

Start monitoring your Snowflake environment today

Dynatrace Snowflake Observability is available now through the Dynatrace Data Observability app with guided onboarding that gets you to full coverage across cost, performance, security, operations, and data quality in minutes.