Turning OpenTelemetry into a Governed Enterprise Data Asset

The useful part

Turning OpenTelemetry into an Enterprise Data Asset Deepti Bhutani One of the most interesting shifts I've seen working with customers at Snowflake is the evolution of our conversations about observability. Today, OpenTelemetry and modern observability platforms such as Observe by Snowflake are making many of these questions easier to answer. Observability conversations can now start with business metrics and outcomes, not logs, metrics and traces.

How it works

• The goal is no longer just to understand what's happening in distributed systems but to connect technical data to what it means for the business.
• The engineering team had answered "What broke?" The executive team, however, immediately began asking follow-up questions:
• At this point, observability stopped being only an operational problem and became a data problem.
• The same data that helps engineers restore production can also help leaders understand customer impact, identify long-term reliability trends, improve engineering decisions and power AI.
• The next question is how to retain, govern and reuse observability data across analytics, AI and operational workflows.

What to take from it

Like many digital businesses, even a few minutes of degraded performance can affect customer experience, increase support volume and put revenue at risk. Rather than stopping at root cause analysis, the team could quantify the impact on its customers, estimate revenue at risk and prioritize remediation based on business outcomes. Continue the observability conversation Telemetry is no longer just operational data — it is enterprise data.

Example or evidence

• Disclosures This article contains forward-looking statements, including about our future product offerings, and are not commitments to deliver any product offerings.
• They emerge as soon as an incident's technical impact becomes a question of customer churn, revenue and business impact.
• Observability doesn't end when the incident ends Consider a hypothetical large financial services company serving millions of customers.
• During a production incident, the engineering team noticed elevated latency in a customer-facing payment service.

Details worth keeping

How do we gain better visibility into increasingly complex systems? How do we connect operational data with customer and business data? How do we ensure observability data remains open and under our control?

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