Modern data center networks, especially those embracing hybrid cloud models, Software-Defined Data Centers (SDDC), and technologies like EVPN/VXLAN, are incredibly powerful but also inherently complex. Managing these distributed, dynamic environments effectively presents a significant challenge. Traditional network monitoring approaches, while still necessary, often fall short in providing the deep, contextual insights needed to truly understand system behavior and proactively address issues.
This is where network observability comes in. It represents an evolution beyond basic monitoring, offering a more holistic and insightful approach to understanding the health, performance, and security of complex IT systems. For organizations leveraging modern data center architectures, observability isn't just beneficial – it's essential for maintaining operational excellence. Intelligent Visibility provides comprehensive observability solutions and managed services to help clients master their complex environments.
While often used interchangeably, monitoring and observability represent different concepts:
Monitoring: Is the action of collecting and analyzing data against predefined metrics or thresholds for specific components. It answers the question, "Is this specific system or component working as expected?" (e.g., Is CPU utilization below 80%? Is this link up?). Network Performance Monitoring (NPM) tools traditionally focus here, tracking device health and network traffic metrics. Monitoring is often reactive, alerting on known failure conditions or deviations from baseline. A major limitation is the "watermelon dashboard" phenomenon – individual components appear green, but the overall service is failing, and monitoring doesn't explain why.
Observability: Is a property of a system that allows you to understand its internal state and behavior by analyzing its external outputs (telemetry data – metrics, logs, and traces). It aims to answer deeper questions like "What is happening inside the system?" and "Why is this happening?". Observability goes beyond tracking knowns; it enables exploration and diagnosis of "unknown unknowns" – unexpected issues arising from complex interactions within distributed systems. It focuses on the system as a whole, contextualizing data from various sources to provide actionable insights. This enables a more proactive and predictive approach to operations.
Gartner defines observability platforms as those ingesting diverse telemetry (logs, metrics, events, traces) to understand system health, performance, and behavior, enabling analysis and proactive remediation. They differentiate observability (contextualized, whole system health) from mere visibility (discrete parts, often isolated). While some debate the specific term "network observability" versus established terms like Network Performance Monitoring and Diagnostics (NPMD), the core principle of leveraging diverse telemetry for deeper, contextualized understanding of network behavior within the broader IT system is undeniably valuable.
This evolution from monitoring to observability is crucial because modern systems are too complex for predefined dashboards and alerts alone. You need the ability to ask new questions of your system when unexpected problems arise.
Observability relies on collecting and correlating different types of telemetry data, often referred to as the "three pillars":
Metrics: These are numerical measurements aggregated over time, providing quantitative insights into system performance and health. Examples include network throughput, latency, error rates, CPU/memory utilization, and application request rates. Metrics are excellent for dashboards, trend analysis, and alerting on known conditions when thresholds are breached. However, they often lack granular detail and context on their own, and aggregation can obscure important information.
Logs: These are timestamped, discrete records of events that occur within the system, such as errors, configuration changes, user actions, or application-specific events. Logs provide rich, detailed context for troubleshooting and root cause analysis. Challenges include the sheer volume of log data generated, storage costs, varying formats (structured vs. unstructured), and the difficulty of searching and correlating logs across many sources at scale.
Traces (Distributed Tracing): Traces track the journey of a single request as it propagates through all the different services and components in a distributed system. Each step (span) in the journey is timed, allowing teams to visualize the entire request flow, identify bottlenecks, understand dependencies, and pinpoint sources of latency or errors in complex microservice architectures. Implementing tracing often requires code instrumentation, which can add complexity.
True observability emerges when data from these three pillars is collected, integrated, and correlated. For network observability specifically, telemetry sources include traditional methods like SNMP polling, flow data (NetFlow, sFlow, IPFIX), packet capture, and modern approaches like streaming telemetry (e.g., gNMI) which push data in real-time. Correlating this network data with application traces and infrastructure logs provides the end-to-end context needed to understand how network performance impacts application behavior and user experience.
At Intelligent Visibility, we bring together a curated set of industry-leading observability platforms to help you gain complete visibility across your hybrid, multi-cloud, and on-prem environments. Our portfolio covers the full spectrum — from infrastructure and network health to application performance and cloud-native operations.
LogicMonitor: A powerful SaaS-based platform offering hybrid observability across on-premises and cloud environments. LogicMonitor provides automated discovery, 2000+ integrations, network topology mapping, unified log and metric collection, and AI-driven anomaly detection with Edwin AI. It delivers comprehensive insights into infrastructure, network, and cloud performance, making it ideal for modern data center and hybrid cloud operations.
AppDynamics: An enterprise-grade application performance monitoring (APM) solution designed to provide deep, code-level visibility into application behavior, transactions, and user experience. AppDynamics enables teams to monitor business-critical apps, trace issues across distributed environments, and tie performance insights directly to business outcomes.
Splunk: A market-leading platform for log aggregation, search, and analysis, Splunk is a cornerstone of modern observability and security (SIEM) strategies. We help clients leverage Splunk to collect and analyze massive volumes of machine data, enabling real-time troubleshooting, operational intelligence, and security event monitoring across the stack.
Arista CloudVision: More than just a network automation platform, CloudVision delivers advanced network observability using real-time streaming telemetry from Arista switches (NetDB). With its Universal Network Observability (CV UNO) capabilities, it provides end-to-end application-to-network visibility, proactive risk and impact analysis, and seamless integration with ecosystem partners — all without the need for host agents.
Grafana: A leading open-source visualization and analytics platform, Grafana empowers teams to create dynamic, customizable dashboards that bring metrics, logs, and traces to life. We help organizations deploy Grafana as a unified observability interface, integrating it with back-end tools like Prometheus, Elasticsearch, and others for powerful data exploration and alerting.
Cribl: A modern observability pipeline solution that helps route, reduce, enrich, and shape telemetry data before it hits your downstream analytics and monitoring tools. Cribl enables cost-effective observability by optimizing data flows into platforms like Splunk and Elastic, ensuring you get actionable insights without overloading your systems or budgets.
AWS Native Observability Tools: For organizations operating in AWS, we help maximize the value of native services like Amazon CloudWatch, AWS X-Ray, AWS CloudTrail, and AWS Config. These tools offer rich metrics, logs, traces, and audit capabilities — giving you a first-class view into your cloud workloads, performance, and compliance.
These platforms increasingly leverage AIOps (Artificial Intelligence for IT Operations), using machine learning and analytics on the collected telemetry data to provide predictive insights, automate root cause analysis, reduce alert noise, and even trigger automated remediation actions. LogicMonitor's Edwin AI is a prime example of this trend.
At Intelligent Visibility, we recognize that effective operations in today's complex data center and hybrid cloud environments depend on deep, actionable insights. That's why observability is central to our solutions and services:
Comprehensive Solutions: We offer tailored Observability & Monitoring solutions, underpinned by our Aegis PM (Performance Monitoring) managed service, which delivers full-stack observability across network, infrastructure, cloud, and applications. We leverage real-time observability platforms to provide this unified view.
Tackling Complexity: Our solutions directly address the visibility gaps inherent in modern architectures like SDDC, EVPN/VXLAN, and hybrid cloud. By correlating data across domains, we help ensure the performance, security, and scalability of the advanced networks we design and manage.
Proactive Operations: We don't just monitor; we observe. Using AI-driven analytics and anomaly detection on observability data, we proactively identify and troubleshoot issues, often before they impact users. This aligns with our Aegis IR (Incident Response) service, enabling faster, more accurate resolution.
Co-Managed Expertise: Through our co-managed services model, we bring observability tools and the expertise to interpret the data, augmenting your internal team. We provide the insights and optimization recommendations, helping you manage performance and security effectively while retaining full control.
The shift from traditional monitoring to comprehensive observability is essential for managing the complexity and dynamism of modern data center networks and hybrid cloud environments. By leveraging the three pillars – metrics, logs, and traces – and correlating this telemetry data, organizations gain the deep understanding needed to move beyond reactive firefighting. Observability enables faster troubleshooting, improves system performance and reliability, strengthens security posture by uncovering hidden threats, enhances user experience, and paves the way for intelligent automation through AIOps. Intelligent Visibility provides the platforms, services, and expertise to help you harness the power of observability and achieve operational excellence.
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