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Every Configuration & Change Counts

When it comes to preventing and troubleshooting incidents, you can’t allow yourself to miss any little change across your entire environment.


End-to-end Environment

Most Granular Level

All Change Types

Near Real-Time


End-to-end Environment

Most Granular Level

All Change Types

Near Real-Time



We Blend Well With Others

Knowing what changed enables valuable insights not available before. But it doesn’t stop there, Evolven correlates and analyzes the configuration changes we collect with the tools you already have.

Machine Learning Analytics

Powerful risk-based analytics that rely on machine learning, anomaly detection and domain specific heuristics deliver actionable insights.

Position 10

Policy: Not compliant with expected policy

Position 6

Host Type: Happened in production environment

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Authorized: Automatically authorized deployment

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Operation type: Configuration item was updated

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Filter - Production environments in Online Loans application

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Impact: Critically impacts system security

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Time Anomaly: Typically overnight changes happened at noon

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State: Change is still open

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Consistency: Inconsistent with similar systems

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Loneliness: Change happened outside of most change clusters

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Frequency: Change in rarely modified configuration item
  • Noise reduction: automatically exclude irrelevant, noisy and low significance changes and differences
  • Correlation: correlate data within and between multiple data sources
  • Risk calculation: calculate risk scores for each change and difference dimension
  • Multi-dimensional risk analysis: combine all risk scores into the total risk for prioritizing changes and differences



Webinar: Top 5 IT Ops Challenges - How Machine Learning Can Help

resources video itopsMachine learning can help IT teams unlock the value hidden in huge volumes of operations data, reducing the time to troubleshoot and prevent issues.