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If you’re still relying on SNMP for network monitoring, it’s time to think ahead.
I get it — SNMP has been around forever. Most of us have used tools like SolarWinds, PRTG, or Nagios with SNMP polling, right? But let’s be honest — it’s slow, reactive, and not built for the real-time visibility we now expect in cloud-scale, multi-vendor networks.
That’s where Model-Driven Telemetry (MDT) comes in. It’s modern, efficient, and built for automation and streaming data, not polling.
In this blog, we’ll dive deep into what makes Model-Driven Telemetry the future, compare it with SNMP, explore commands, see a working EVE-NG lab, and wrap up with FAQs and a YouTube demo. Let’s get started!
Table of Contents
Theory in Brief – SNMP vs Model-Driven Telemetry
What is SNMP?
Simple Network Management Protocol (SNMP) is a traditional protocol used to monitor and manage network devices. It works on a pull model — your NMS (like SolarWinds) polls the device for OID values at intervals.
It supports:
- Get (polling values),
- Set (configuration),
- Traps (alerts).
But SNMP is limited by:
- High latency due to polling intervals,
- CPU overhead on devices,
- Lack of real-time insights.
What is Model-Driven Telemetry (MDT)?
Model-Driven Telemetry is a push-based monitoring method that streams real-time operational data from the device to a collector using YANG models.
Instead of polling every 5 minutes, the device pushes data continuously — think of it like Netflix vs. DVD rental. It’s fast, scalable, and ideal for automation.
Core components of MDT:
- YANG data models define what to stream.
- gRPC, TCP, UDP, or HTTP/HTTPS transports.
- Collectors (like Telegraf, InfluxDB, Grafana) visualize the data.
Why Is Telemetry a Game Changer?
- It’s built for streaming and cloud.
- Highly scalable (thousands of devices).
- Less overhead on devices.
- Supports structured data via XML/JSON.
- Integrates with modern DevOps pipelines.
SNMP was great in the 90s, but telemetry is what modern data centers and service providers demand today.
SNMP vs Model-Driven Telemetry – Comparison
| Feature | SNMP | Model-Driven Telemetry |
|---|---|---|
| Data Flow | Poll-based (pull) | Stream-based (push) |
| Protocol Versions | SNMPv1/v2/v3 | gRPC, TCP, UDP, HTTP, Kafka |
| Data Format | Raw OID (numeric) | Structured (XML, JSON, GPB) |
| Real-Time Capability | No (polling delay) | Yes (real-time stream) |
| Device Load | Medium-High (poll every few mins) | Low (optimized streaming) |
| Extensibility | Limited | High (based on YANG models) |
| Security | SNMPv3 with authentication | TLS, mTLS, secure transports |
| Integration | NMS tools like SolarWinds, Nagios | Telemetry stacks (Telegraf, InfluxDB) |
| Configuration Complexity | Low | Medium (but automated) |
| Cloud-readiness | Low | High |
Pros and Cons
| Aspect | SNMP – Pros | SNMP – Cons |
|---|---|---|
| Easy to use | Widely supported | Polling-based delays |
| Compatibility | All devices support it | Lacks structured data |
| Security | SNMPv3 support | Weak in v1/v2c; harder to encrypt |
| Monitoring | Good for small networks | Not scalable for large data centers |
| Aspect | Telemetry – Pros | Telemetry – Cons |
|---|---|---|
| Real-time Data | Immediate visibility | Requires collector setup |
| Efficiency | Lower CPU overhead | Learning curve (YANG, gRPC) |
| Data Modeling | YANG models are reusable | Complex for beginners |
| Extensibility | Highly programmable | Limited support on older IOS versions |
Essential CLI Commands – SNMP & Telemetry
| Purpose | SNMP Commands (Cisco IOS) | MDT Commands (IOS XE) |
|---|---|---|
| Enable SNMP | snmp-server community public RO | N/A |
| Configure SNMP Trap | snmp-server enable traps | N/A |
| Show SNMP | show snmp | show telemetry ietf subscription |
| Debug SNMP | debug snmp packet | debug telemetry |
| Configure MDT Destination | N/A | telemetry ietf destination-group <name> |
| Configure Sensor Path | N/A | telemetry ietf sensor-group <name> |
| Subscription Config | N/A | telemetry ietf subscription <ID> |
| Verify Telemetry | N/A | show telemetry internal connection all |
Real-World Use Case
| Use Case | Details |
|---|---|
| Industry | ISP / Telecom / Financial Enterprises |
| Problem | SNMP-based monitoring was slow and missed transient spikes |
| Solution | Migrated to Model-Driven Telemetry using YANG models and gRPC |
| Outcome | Real-time monitoring, automated alerting, improved RCA timelines |
| Tools Used | Cisco IOS-XE routers, Telegraf, InfluxDB, Grafana |
Small EVE-NG Lab – Telemetry Streaming with gRPC
Lab Topology
Lab Requirements
- Cisco IOS-XE device (v16.9+)
- Ubuntu/Telemetry Host with Telegraf
- EVE-NG running both devices
- gRPC port open (57400)
Sample CLI Configuration – IOS XE
telemetry ietf subscription 1001
encoding encode-kvgpb
filter xpath /interfaces/interface/state/counters
stream yang-push
update-policy periodic 1000
receiver ip address 192.168.1.10 57400 protocol grpc-tcp
Telegraf Configuration
Edit /etc/telegraf/telegraf.conf:
[[inputs.cisco_telemetry_mdt]]
transport = "grpc"
service_address = ":57400"
redial = "10s"
max_msg_size = 1000000
Then restart:
sudo systemctl restart telegraf
Validation
- On router:
show telemetry ietf subscription - On host:
sudo journalctl -u telegraf -fto see incoming data
Troubleshooting Tips
| Issue | Cause | Fix |
|---|---|---|
| No telemetry data received | gRPC port blocked | Check firewall / ACLs |
| Subscription not appearing | Misconfigured sensor path or destination | Re-check sensor path using YANG explorer |
| High CPU on router | Excessive sensor rate | Increase interval or reduce sensor count |
| Telegraf not receiving | Incorrect config or service stopped | Restart Telegraf and re-check logs |
| Connection reset error | Wrong IP or port | Verify destination IP and gRPC port on router |
Frequently Asked Questions (FAQ)
1. What is the fundamental difference between SNMP and Model-Driven Telemetry (MDT)?
Answer:
SNMP is a traditional polling-based protocol where the NMS (Network Management System) queries network devices at regular intervals. In contrast, Model-Driven Telemetry (MDT) is push-based. Devices stream real-time data to collectors based on predefined models and subscriptions. This eliminates the delay and inefficiency of polling, making telemetry more scalable and suitable for modern networks.
2. Why is Model-Driven Telemetry considered more efficient than SNMP?
Answer:
Model-Driven Telemetry uses a streaming architecture where data is sent only when needed or when a change occurs. It reduces:
- CPU overhead on devices (no repeated SNMP polling).
- Network traffic, as only relevant data is pushed.
- Data loss, because it supports high-frequency updates (as low as milliseconds).
This makes MDT ideal for real-time analytics, SDN, and automation frameworks.
3. What transport protocols does Model-Driven Telemetry use compared to SNMP?
Answer:
- SNMP relies on UDP (usually port 161) which is lightweight but unreliable.
- MDT supports multiple modern transport protocols like:
- gRPC (Google Remote Procedure Call) – preferred for low latency, streaming, and TLS support.
- Kafka, TCP, and HTTP/HTTPS for integration with cloud and big data pipelines.
4. What is a YANG model and how is it related to Model-Driven Telemetry?
Answer:
YANG (Yet Another Next Generation) is a data modeling language used to define the structure of configuration and operational data. Model-Driven Telemetry uses YANG models to determine what data to stream, in contrast to SNMP’s rigid MIBs. This vendor-neutral, machine-readable, and human-friendly structure makes telemetry highly customizable and extensible.
5. Is Model-Driven Telemetry vendor-specific or multi-vendor compatible?
Answer:
MDT is standards-based, leveraging YANG models and open transport protocols, which enhances multi-vendor support. Cisco, Juniper, Arista, and others support MDT, making it suitable for diverse networks. However, implementation details and supported YANG models may vary across vendors.
6. Can Model-Driven Telemetry completely replace SNMP?
Answer:
Not entirely yet. While MDT is technically superior, SNMP is deeply entrenched in legacy systems, tools, and monitoring software. Many NMS platforms still rely heavily on SNMP. However, newer tools (like Cisco DNA Center, Telegraf + InfluxDB, Prometheus) support MDT. So, we’re currently in a coexistence phase where both are often used in parallel.
7. What are the key use cases of Model-Driven Telemetry in enterprise networks?
Answer:
Model-Driven Telemetry is ideal for:
- Real-time performance monitoring (CPU, memory, interface stats).
- Security telemetry (ACL hits, netflows).
- Network automation feedback loops.
- Predictive analytics and AI/ML models.
- Closed-loop assurance systems.
It enables proactive operations rather than reactive SNMP-style alerts.
8. What tools and platforms support collecting and visualizing telemetry data?
Answer:
Popular telemetry collectors and visualization platforms include:
- Telegraf + InfluxDB + Grafana – open-source stack.
- Cisco DNA Center – built-in telemetry support.
- Kafka + Elasticsearch – for large-scale, distributed environments.
- Prometheus + Grafana – especially in cloud-native setups.
- Splunk, ThousandEyes, and AppDynamics – for deep analytics and AIOps.
9. What are the challenges in adopting Model-Driven Telemetry?
Answer:
Key challenges include:
- Initial complexity: Requires understanding YANG, gRPC, and streaming collectors.
- Tool compatibility: Not all legacy tools support MDT.
- YANG model inconsistencies: Different vendors may use custom models.
- Resource demand: High-frequency streaming may need optimized infrastructure and storage.
However, with proper planning and tooling, these challenges can be mitigated.
10. How does learning MDT align with CCNP and DevNet certifications?
Answer:
Model-Driven Telemetry is a core topic in both CCNP Enterprise (ENA/ENARSI) and Cisco DevNet Associate/Professional certifications. Cisco emphasizes programmability, model-based monitoring, and automation. Mastering MDT gives you an edge in:
- Infrastructure as Code (IaC) environments.
- DevOps for Networks.
- Next-gen monitoring systems.
This aligns well with industry demand for NetDevOps and Automation Engineers.
YouTube Link
Watch the Complete CCNP Enterprise: Model-Driven Telemetry vs SNMP – Rethinking Network Monitoring Lab Demo & Explanation on our channel:
Final Note
Understanding how to differentiate and implement Model-Driven Telemetry vs SNMP – Rethinking Network Monitoring is critical for anyone pursuing CCNP Enterprise (ENCOR) certification or working in enterprise network roles. Use this guide in your practice labs, real-world projects, and interviews to show a solid grasp of architectural planning and CLI-level configuration skills.
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