For network and cloud operations leaders, the challenge has evolved far beyond "keeping the lights on.” Today’s telecommunications infrastructure is an intricate, multi-cloud beast. However, while the complexity and demands continue to expand, the tools used to manage the infrastructure often remain stuck in a simpler era.
Consequently, it’s no surprise that 87% of IT teams say that internet and cloud dependencies create network blind spots.
Why is traditional network monitoring failing modern telcos?
Traditional monitoring solutions are often static, fragmented, and labor-intensive. They create sprawling "data lakes" that generate more noise than clarity. Ultimately, these tools leave teams drowning in alerts while struggling to pinpoint root causes.
These disconnected tools also create operational silos, turning root-cause analysis into a multi-week "archaeological dig." When you can’t correlate network performance with user experience, every minute spent chasing symptoms instead of failures erodes your mean time to resolution (MTTR) and inflates operating expenses.
How can telcos move from reactive monitoring to proactive observability?
Modern networks demand the precision of a Formula 1 pit wall. You don’t just need a speedometer; you need real-time telemetry correlating every variable to know why performance is lagging. Quite simply, you need to move from network monitoring to network observability.
Network Observability by Broadcom acts as a "codebreaker," transforming disparate sources of telemetry into AI-enabled intelligence. It provides a single source of truth across four critical pillars:
- Fault analytics. Employ automated, service-centric root cause analysis that enables you to instantly drill down from a service issue to the specific topology.
- Performance analytics. Leverage advanced anomaly detection and automated baselining so you can preempt service degradations before they have an impact on users.
- User experience insights. Link customer-facing symptoms directly to infrastructure faults, ensuring staff are notified before subscribers even report an issue.
- Configuration and flow. Enforce "golden" configurations and gain end-to-end traffic visibility to optimize resource allocation and promote service monetization.
How does unified network observability enable business growth?
This platform is a strategic business enabler, not just a troubleshooting tool. By adopting a data-centric strategy—similar to market leaders like BT Ireland—telcos can achieve these primary objectives:
- Unlock high-quality services. Use deep visibility to back premium SLA tiers and gain differentiation in a crowded market.
- Minimize multi-cloud risk. Bridge the gap between legacy and cloud-native infrastructure to deliver resilient managed services.
- Monetize network intelligence. Turn high‑fidelity telemetry into a revenue‑aligned asset by streaming real‑time network insights to customer AI tools and business systems.
- Improve profitability. Reduce operating expense by using AI-enabled diagnostics to automate heavy lifting and minimize unnecessary service tickets.
- Enhance client trust. Deliver customizable service views and real‑time health reports that provide transparent, business‑level visibility, so you can demonstrate reliability and strengthen trust.
Ready to break the reactive loop?
Don’t let operational silos stifle your network team’s performance. The complexities of hybrid cloud and multi-tenant services require a new architectural blueprint.
Frequently Asked Questions
What is the difference between network monitoring and network observability for telcos?
Traditional monitoring tracks predefined KPIs and SNMP traps to alert on threshold breaches. Conversely, network observability provides deep context by correlating telemetry across distributed architectures and multi-cloud edges. It empowers Telcos to resolve "why" a service is degraded—rather than just "what" device is down—by unifying subscriber experience, hop-by-hop traffic flows, and virtualized infrastructure into a single, actionable source of truth.
How does AI-driven root cause analysis (RCA) reduce MTTR in multi-cloud networks?
AI-driven root cause analysis leverages machine learning to suppress "event storms" from fragmented telemetry, pinpointing the specific topological shift or configuration change causing failure. By automating high-cardinality data correlation, Telcos bypass manual "war rooms" to initiate immediate remediation. This accelerates mean time to resolution (MTTR), safeguarding SLOs across complex, software-defined underlays and third-party cloud environments.
Why is user experience visibility critical for modern network operations?
In modern distributed ecosystems, a network can appear "healthy" via backend metrics while subscribers suffer from latency or jitter. Integrating user experience insights into the NOC allows teams to observe the network through the subscriber’s lens. This proactive strategy links infrastructure health to subscriber-centric outcomes, enabling operators to resolve gaps in assuring the service quality experience they trigger support tickets, drive churn, or impact service-level commitments.
