SONiC Switch Observability Is Leaving SNMP Behind

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In brief

Engineering guidance on SONiC Switch Observability Is Leaving SNMP Behind for Australian infrastructure teams, covering form factor tradeoffs, capacity planning.

Key takeaways

Engineering guidance on SONiC Switch Observability Is Leaving SNMP Behind for Australian infrastructure teams, covering form factor tradeoffs, capacity planning.

What Is Happening

The networking industry is accelerating a transition away from legacy SNMP polling toward streaming telemetry and model-driven configuration for network device management. This shift is particularly visible in environments running SONiC (Software for Open Networking in the Cloud), the open-source network operating system originally developed by Microsoft and now governed by the Linux Foundation’s SONiC project.

Two open protocols sit at the center of this transition:

gNMI (gRPC Network Management Interface), defined by the OpenConfig initiative, enables real-time streaming of telemetry data from switches to collector platforms using gRPC and Protocol Buffers. Unlike SNMP, which relies on periodic polling and MIB-based data models, gNMI pushes structured, YANG-modelled data to receivers on a subscription basis.
NETCONF (Network Configuration Protocol), an IETF standard (RFC 6241), provides model-driven device configuration and state retrieval using YANG data models. Combined with tools like OpenConfig YANG models or vendor-native YANG modules, NETCONF allows network automation platforms to read and write switch configuration in a structured, validated, and transactional way.

Together, these protocols represent a broader architectural pattern: separating the data model from the transport, enabling network operators to build automation pipelines that are portable across switch vendors and NOS platforms.

Why It Matters for Australian Network Teams

Australian enterprises and service providers face several converging pressures that make observability automation a strategic priority:

Data center growth. Australia’s data center market continues to expand, driven by hyperscaler investment, sovereign data requirements, and AI/ML workload deployment. As fabric scale increases — particularly in spine-leaf architectures using 100G, 400G, and 800G links — manual SNMP-based polling cannot keep pace with the volume and granularity of telemetry data operators need.
AI fabric complexity. Organizations deploying GPU clusters for training and inference require lossless, low-latency fabrics with RoCE v2, DCBX, and congestion notification. Monitoring these fabrics demands sub-second telemetry visibility into queue depths, ECN marking, buffer utilization, and PFC frame counts — data that streaming telemetry via gNMI delivers natively but SNMP struggles to provide at the required cadence.
Skills and automation alignment. Australian network engineering teams increasingly work alongside DevOps and platform engineering functions. The move to gNMI and NETCONF aligns network operations with the same API-driven, infrastructure-as-code toolchains that compute and storage teams already use (Ansible, Terraform, Python/gNMI clients, Prometheus/Grafana observability stacks).
Open networking procurement criteria. As more Australian buyers evaluate SONiC-based switches as alternatives to incumbent vendor NOS platforms, observability protocol support becomes a first-class evaluation criterion alongside forwarding performance, port density, and power consumption.

The general networking literature confirms that network devices rely on communication protocols to transmit and exchange data, and that modern networks are designed for scalability, security, and IT operations efficiency. The specific application of gNMI and NETCONF within SONiC extends these principles into the programmable, model-driven observability layer that enterprise and data center operators now require.

gNMI vs. SNMP: The Technical Shift

Understanding the practical difference between legacy and model-driven observability helps explain why this shift is gaining momentum:

Dimension	SNMP (Legacy)	gNMI Streaming Telemetry
Data model	MIB (ASN.1, vendor-specific)	YANG (structured, standardized)
Transport	UDP/161 (polling)	gRPC/TLS (subscription-based push)
Data format	OIDs, raw values	JSON or Protobuf, structured paths
Granularity	Periodic (minutes typical)	Sub-second, on-change capable
Scalability	Manager polls each device	Devices stream to collectors
Extensibility	MIB compilation required	YANG model updates, no recompilation

For SONiC-based switches, gNMI support means that network operators can subscribe to real-time state data — interface counters, BGP neighbor state, LLDP topology, system health metrics — and feed it directly into time-series databases like Prometheus or InfluxDB, and visualization platforms like Grafana.

NETCONF complements gNMI on the configuration side. Rather than using CLI screen-scraping or custom API calls, NETCONF allows automation tools to read, validate, and apply configuration changes using YANG-modeled data with transactional semantics (confirmed commits, rollback on failure). For Australian enterprises running multi-vendor or multi-site SONiC fabrics, NETCONF provides a vendor-portable configuration interface that reduces platform-specific automation code.

The Observability Automation Stack

For teams evaluating SONiC-based switches with gNMI and NETCONF support, the typical open-source observability automation pipeline looks like this:

Switch layer: SONiC NOS with gNMI server (telelemetryd) and NETCONF server exposing YANG-modeled state and configuration.
Collection layer: gNMI collectors (e.g., gnmic, Telegraf with gNMI input plugin) subscribe to telemetry streams and write to time-series databases.
Storage and query layer: Prometheus, InfluxDB, or VictoriaMetrics store time-series telemetry data.
Visualization and alerting layer: Grafana dashboards display real-time fabric health; Alertmanager triggers notifications on threshold breaches or anomaly detection.
Configuration automation layer: Ansible with NETCONF modules, Nornir with ncclient, or Terraform providers push validated configuration changes to SONiC switches.

This stack mirrors the observability patterns that IBM and other enterprise infrastructure providers describe for cloud networking environments, where automation, real-time monitoring, and AI-assisted anomaly detection are increasingly standard requirements. The IBM reference notes that AI and machine learning are transforming networking by enabling smarter, more adaptive systems that automate network management and optimize performance by predicting and responding to traffic patterns in real time — a capability that depends on having high-quality, high-frequency telemetry data in the first place.

For Australian buyers, the key evaluation question becomes: does the switch platform and its SONiC build provide the gNMI telemetry coverage and NETCONF configuration depth to support this full stack, or does it require proprietary extensions that lock the operator back into a single-vendor toolchain?

xSONiC Buyer Angle for Australia

For Australian enterprise and data center buyers evaluating xSONiC open networking platforms, the observability and automation story is a differentiator that should be tested during proof-of-concept trials:

Data center AI switches. Buyers deploying spine-leaf fabrics for AI/ML clusters should verify that gNMI telemetry covers RoCE v2 counters, PFC statistics, ECN marking, queue depth monitoring, and INT/IPTPath data paths. Real-time visibility into fabric congestion is a prerequisite for lossless RDMA operations.
Access and aggregation switches. Campus network teams should confirm NETCONF/YANG coverage for VLAN, PoE, ACL, MC-LAG, and policy-based routing configuration, and that gNMI telemetry streams cover interface status, PoE power budgets, and client session data.
Packet brokers. For network visibility deployments, telemetry automation enables dynamic filter rule management and traffic replication monitoring through the same model-driven interfaces used for the switching fabric.
AIDC Controller integration. Buyers using xSONiC’s AIDC Controller should ask how the controller consumes gNMI telemetry and pushes NETCONF configuration, and whether it provides a unified observability layer across mixed switch deployments.

The Australian market context matters here. With limited local network engineering talent pools compared to the US or Europe, automation and model-driven operations reduce the operational burden on smaller teams. Open, standards-based telemetry and configuration protocols also protect against vendor lock-in — a concern that becomes more acute as fabric scale grows and multi-year TCO calculations favor platforms that can be managed with portable toolchains.

What to Watch Next

Several developments are worth tracking for their impact on SONiC observability and automation in Australia:

SONiC community gNMI and NETCONF feature maturation. The SONiC project continues to expand YANG model coverage and improve telemetry density with each release. Buyers should track release notes for gNMI path additions and NETCONF capability updates.
OpenConfig model adoption. As OpenConfig YANG models gain wider adoption across NOS platforms, the portability benefits of model-driven telemetry increase. Australian buyers evaluating multi-vendor strategies should prioritize platforms with OpenConfig alignment.
AI-assisted network operations. The convergence of streaming telemetry with AI/ML-powered anomaly detection and intent-based networking is an active area of development. Platforms that provide clean, structured telemetry data now will be better positioned to leverage these capabilities as they mature.
Australian regulatory context. Data sovereignty and operational resilience requirements in sectors such as financial services, government, and healthcare may favor open, auditable observability stacks over proprietary NMS platforms. Standards-based telemetry supports compliance and audit workflows.

Engineering FAQ

How should NVMe form factor selection be made? Start with workload profile, usable capacity, serviceability, thermal envelope, write endurance, PCIe generation, slot layout, and replacement process. U.2, E1.S, M.2, and AIC devices solve different mechanical and operational problems.

What matters more than peak sequential speed? Sustained performance, thermal throttling behaviour, write endurance, latency under load, firmware stability, power-loss protection, and fleet manageability usually matter more than a single benchmark number.

How should storage be validated for AI or cloud workloads? Test the selected form factor in the real chassis with expected airflow, queue depth, write mix, temperature range, and monitoring stack. Validation should include steady-state and recovery behaviour, not only fresh-drive performance.

Sources Reviewed

Product fit

Where xSONiC fits

xSONiC can help validate the switch, optics, software image, telemetry, and support assumptions against the actual deployment before a production order is released.