Network Telemetry and Visibility Strategies for the Digital Enterprise

April 2018 · Reading time: 12 mins

Introduction

In 2018, digital transformation forces IT teams to rethink how they monitor, analyze, and respond to network behavior. Traditional SNMP polling and flow-based statistics no longer deliver the context or granularity needed to support cloud-first, mobile, and microservice-driven enterprises. As networks become more dynamic, real-time telemetry becomes a strategic enabler.

Why Legacy Monitoring Falls Short

SNMP provides limited insight into application-layer behavior. Flow-based tools like NetFlow or sFlow offer directional traffic stats but miss end-user experience. Static polling intervals, sampled data, and lack of correlation prevent IT teams from detecting issues before they affect productivity.

The Rise of Streaming Telemetry

Streaming telemetry replaces pull-based monitoring with push-based updates over protocols like gRPC, Kafka, and HTTP/JSON. Devices continuously stream interface stats, app metrics, and environmental data to collectors in near-real-time. This model reduces overhead and increases data freshness.

Telemetry in Multi-Domain Environments

Enterprises integrate telemetry across WAN, data center, cloud, and campus networks. By correlating device telemetry with cloud service status, app performance, and user identity, they build a holistic view of the digital experience. OpenConfig, model-driven telemetry, and vendor-specific extensions support multi-vendor deployments.

Key Use Cases in 2018

• Proactive Troubleshooting: Detect latency, loss, or CPU spikes before users notice
• SLA Validation: Monitor contractual performance guarantees across SD-WAN and SaaS links
• Capacity Planning: Use time-series insights to predict growth and adjust architecture
• Security Analytics: Feed enriched telemetry to SIEMs for anomaly detection

Vendor Landscape

In 2018, vendors like Cisco, Juniper, Arista, and Huawei deliver telemetry agents within network OS platforms. Cisco IOS-XE and NX-OS stream telemetry to tools like Tetration and DNA Center. Arista EOS uses gNMI and open collectors. Juniper supports model-driven telemetry via JTI into platforms like AppFormix.

Cloud and SaaS Visibility

IT extends visibility to internet and SaaS traffic using DNS metrics, HTTP latency probes, and synthetic transactions. Tools like ThousandEyes, AppNeta, and Catchpoint simulate user journeys to services like Office 365, Salesforce, and AWS. These measurements complement internal telemetry and validate user experience from edge to cloud.

Challenges Enterprises Face

• Data Overload: Raw telemetry generates terabytes of logs and counters
• Normalization: Vendors expose metrics differently, complicating cross-platform correlation
• Real-time Analysis: Teams require analytics platforms that support time-series queries, alerting, and visualization at scale
• Integration: Telemetry must feed into broader AIOps, ITSM, and security platforms

Best Practices for Success

• Start with a clear observability goal (performance, security, compliance)
• Deploy collectors close to the source to reduce backhaul and delay
• Normalize metrics using open models or translation layers
• Integrate telemetry into incident workflows and dashboards
• Continuously refine alerts to eliminate noise and focus on actionable insights

Conclusion

In April 2018, network telemetry evolves from optional enhancement to essential foundation. Enterprises that embrace streaming telemetry, integrate cross-domain data, and automate analysis position themselves to detect, diagnose, and remediate faster than ever before. Visibility becomes a key differentiator in supporting reliable and resilient digital operations.

Eduardo Wnorowski is a network infrastructure consultant and Director.
With over 23 years of experience in IT and consulting, he helps organizations maintain stable and secure environments through proactive auditing, optimization, and strategic guidance.
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