Designing feedback loops for progressive delivery
Datadog | The Monitor blog

Designing feedback loops for progressive delivery


Summary

This article argues against overly manual release processes ("babysitting") and advocates for using guardrail metrics – automated checks on key performance indicators – to enable faster, more reliable deployments. By defining acceptable performance thresholds before release, teams can automate go/no-go decisions and reduce the need for constant monitoring during and after deployment, ultimately increasing velocity and reducing risk. It's about shifting from reactive firefighting to proactive prevention through data-driven automation.
Read the Original Article

This article originally appeared on Datadog | The Monitor blog.

Read Full Article on Original Site

Popular from Datadog | The Monitor blog

1
DASH 2026: Guide to Datadog’s newest announcements
DASH 2026: Guide to Datadog’s newest announcements

Datadog | The Monitor blog Jun 9, 2026 210 views

2
DASH 2026 Harnessing AI: Guide to Datadog’s newest announcements
DASH 2026 Harnessing AI: Guide to Datadog’s newest announcements

Datadog | The Monitor blog Jun 9, 2026 186 views

3
Datadog LLM Observability natively supports OpenTelemetry GenAI Semantic Conventions
4
Introducing Bits AI Dev Agent for Code Security
Introducing Bits AI Dev Agent for Code Security

Datadog | The Monitor blog Mar 26, 2026 109 views

5
Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog
Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog

Datadog | The Monitor blog Apr 9, 2026 103 views