From Panic to Process: Network Validation in the Wild
Network validation during deployments remains one of the most critical—and challenging—aspects of network automation. A recent discussion in the Network Automation Forum community revealed the diverse approaches engineers are taking to solve this problem, from quick-and-dirty manual checks to sophisticated automated validation systems.
The Spectrum of Validation Approaches
The "Hope and Pray" Method
Some engineers admitted to relying on what one community member called "log out immediately and see if anyone texts or calls you"—a surprisingly effective if stressful validation method. While humorous, this highlights a common reality: many organizations still lack comprehensive automated validation systems.
Basic Automated Checks
More mature approaches involve systematic pre and post-deployment checks focusing on:
Interface states: Up/down status, error counters, congestion metrics
BGP health: Neighbor adjacencies, route counts, queue depths
Traffic patterns: Comparing before/after traffic levels with reasonable variance thresholds
Service dashboards: Monitoring application-level health indicators
One practitioner described mapping checks to device roles rather than specific configuration changes, avoiding "template hell" while ensuring comprehensive coverage. This role-based approach allows for consistent validation regardless of the specific change being made.
Advanced State Management
More sophisticated implementations incorporate concepts from promise theory, continuously monitoring the operational state of high-level network abstractions. Rather than just checking individual metrics, these systems validate that composite services (like VXLAN/EVPN networks) are functioning correctly by monitoring all constituent elements and their dependencies.
The Challenge of Variance and Thresholds
A recurring theme in the discussion was determining acceptable variance in metrics. Edge devices can see significant traffic fluctuations, making it difficult to establish meaningful thresholds. Some practitioners use:
High variance thresholds: One engineer only worries about 99% variance, finding that most real problems are immediately obvious
Relative rather than absolute checks: Focusing on whether services are still receiving expected route advertisements rather than exact prefix counts
Context-aware validation: Different tolerance levels for different types of changes and network roles
The Synthetic Monitoring Debate
The community revealed an interesting split on synthetic monitoring. While some view it as essential for validation, others argued that real application traffic provides better signal than artificial probes. The key arguments against synthetic monitoring included:
Synthetic tests can pass while real applications fail (and vice versa)
Synthetic monitoring can become quadratic and create its own problems
Real flow data provides more accurate representation of user experience
However, synthetic monitoring still has its place, particularly for establishing network innocence during troubleshooting—what one member called "mean time to innocence."
Practical Implementation Patterns
Data Collection Speed
The discussion highlighted the importance of fast data collection for quick rollback decisions. While SNMP polling might take minutes, techniques like gNMI streaming telemetry or direct SSH connections can provide immediate feedback, even if they carry some CPU overhead risk.
Storage and Analysis
For storing validation snapshots, practitioners are using various approaches:
SQLite for smaller-scale operations
Parquet and DuckDB for larger datasets
Time-series databases like Mimir for continuous monitoring
Integration with Orchestration
Several community members are exploring workflow orchestration platforms like Temporal to separate network-specific logic from general orchestration concerns, allowing teams to focus on their core competencies while leveraging proven orchestration frameworks.
The Importance of Standards and Documentation
A key insight from the discussion was that validation becomes significantly easier with standardized configurations and structured documentation. When networks follow consistent patterns and roles are clearly defined, deriving appropriate validation checks becomes straightforward. As one member noted: "Standards, standards, standards and this thing called structured documentation."
Looking Forward: The Configuration-Monitoring Divide
One of the most interesting observations was about the divide between configuration tools and monitoring tools. Many organizations struggle to map operational state back to original configuration intents, especially when dealing with multi-vendor environments and abstracted services. This suggests an opportunity for better integration between configuration management and operational monitoring systems.
Key Takeaways for Practitioners
Start with role-based validation: Map checks to device roles rather than specific configuration changes
Focus on signal over noise: High variance thresholds often work better than tight tolerances
Speed matters: Fast data collection enables quick rollback decisions
Real traffic trumps synthetic: Application flow data often provides better validation than artificial probes
Standards enable automation: Consistent network designs make validation significantly easier
Integration is key: Breaking down silos between configuration and monitoring tools improves validation accuracy
The discussion reveals that while there's no one-size-fits-all solution to network validation, successful implementations share common themes: they prioritize speed and accuracy over perfection, focus on business-critical metrics rather than comprehensive monitoring, and integrate validation tightly with deployment workflows.
As one community member wisely noted: "I found out that most of the time not to overthink these things. It's pretty clear usually when we have something really bad happening." Sometimes the best validation approach is the one that actually gets implemented and used consistently, rather than the theoretically perfect system that never gets built.
This post is based on community discussions and represents the collective experience and opinions of individual practitioners, including: Ryan Shaw, Paul Schmidt, Bart Dorlandt, Mark Prosser, Steinn (Steinzi) Örvar, John Howard, Naveen Achyuta, Roman Dodin, Brian Jeggesen, Denis Mulyalin, Dennis Fanshaw. Approaches should be evaluated and adapted based on your specific network environment and requirements.
