What is network observability?

It provides IT teams with the tools and insights that they need to monitor the flow of data across an organization's entire network infrastructure, including on-premises data centers, multicloud and hybrid cloud environments.

At its core, network observability is about turning raw network data into actionable insights. However, unlike traditional network monitoring (which focuses on predefined metrics and reactive troubleshooting), network observability takes a proactive approach.

Observability tools rely on data collection from a broad range of data sources to conduct deeper analyses and accelerate issue resolution. They collect telemetry data (logs, metrics, traces and events) from various network components—including routers, switches, servers, API endpoints and cloud services—to provide development teams with a holistic view of network performance.

As such, network observability empowers IT teams to detect and address issues before they escalate. This proactive approach helps ensure seamless connectivity, minimize downtime and optimize user experiences.

In a world where businesses depend on uninterrupted connectivity and high-performing applications, network observability is a critical capability. Modern networks are increasingly complex, involving dynamic traffic flows, distributed architectures and multicloud deployments. Traditional monitoring methods are insufficient to address these complexities, making network observability a necessity for maintaining resilience and delivering exceptional user experiences.

Data-driven observability insights help organizations make informed decisions, anticipate future needs, allocate resources more efficiently and align network management strategies with business objectives. They also provide deep, end-to-end visibility into network traffic, which enables the early detection of cyberthreats and helps fortify cybersecurity defenses.

These capabilities help organizations to stay ahead of challenges, adapt to changing network demands and confidently manage their digital infrastructure, even as conditions evolve.

Network observability is built on a set of pillars—metrics, logs, traces, context and correlation—that enable organizations to monitor, analyze and optimize network performance. These pillars work together to provide IT teams with comprehensive visibility into the behavior and health of their networks. Each pillar plays a unique role in providing actionable insights into network operations.

Metrics are quantitative data points that represent the performance and behavior of various network components; as such, they provide a baseline for network monitoring. Metrics capture key performance indicators (KPIs)—such as latency, packet loss, bandwidth utilization and device CPU usage—and give developers a high-level overview of the network’s health.

Using metrics, IT teams can monitor trends over time, identify anomalies and set thresholds for alerting. Take latency spikes, as one example. An unexpected spike in latency might indicate network congestion or a hardware failure. And, if the network reaches the predetermined latency threshold, observability software can send alerts to all relevant IT personnel.

Logs are detailed records of every event or action that occurs within the network. They provide granular information about what occurred, when it occurred and where in the network it occurred, creating valuable context for troubleshooting, debugging and forensic analysis.

Logs reveal the underlying causes of network issues by detailing system events such as device configuration changes, failed authentications and dropped connections.

Traces capture the flow of data across the network, providing insights into the path and behavior of packets as they traverse multiple devices and systems. They’re essential for understanding distributed systems and diagnosing latency issues.

Traces enable IT teams to see the full journey of a transaction, end-to-end, helping pinpoint routing delays and failures within complex, multilayered environments.

Context enriches metrics, logs and traces by providing additional information about the network environment (topology, device roles and application dependencies, for instance). Without context, raw data lacks actionable meaning.

Context enables IT teams to correlate network events with specific applications, users or services, facilitating targeted troubleshooting and informed decision-making.

Correlation ties together metrics, logs, traces and contextual information to present a cohesive view of the network. It helps IT teams identify patterns, root causes and relationships between events and across different layers of the network stack.

Connecting seemingly unrelated data points through correlation enables faster root cause analysis and more effective responses to networks issues. Correlation can, for example, help teams identify the source of cascading failures across interdependent systems.

The pillars of network observability form a comprehensive framework for understanding and managing network performance. Together, they empower IT teams to move beyond reactive monitoring to proactive optimization, promoting reliability and efficiency in complex network environments.

Advanced network observability solutions are typically tailored to fit each organization’s unique networking needs. However, most tools offer a set of key features and capabilities. They include:

Network observability solutions collect, store and analyze telemetry data including packet-level details, flow records and device metrics from diverse sources across the network. Modern observability tools integrate seamlessly with network hardware, software-defined networks (SDNs), and cloud platforms to ensure comprehensive data collection.

Data analysis helps businesses better understand network function and trends, simplify reporting and compliance, and perform thorough root cause analyses.

Network observability tools provide dashboards and visualization tools that present complex data in an intuitive format. Heatmaps, traffic flow diagrams and real-time performance metrics help IT professionals quickly assess the network’s health.

Alerts are automated notifications triggered by specific network conditions or thresholds. Observability solutions provide intelligent alerting mechanisms that can distinguish between critical incidents and minor anomalies, reducing alert fatigue and helping IT teams focus on the most impactful issues.

Along with notifications, which inform stakeholders of significant events, alerts enable businesses to proactively address network issues and maintain high-availability computing networks.

Continuous performance analysis involves the ongoing measurement of key performance metrics across different segments of the network. Ongoing performance assessments provide insights into network trends across time, enabling IT teams to make informed decisions about upgrades, optimizations and capacity planning.

Topology mapping provides visual representations of the network's architecture, illustrating how various components are interconnected across cloud, virtual and on-premises environments. In many cases, mapping features can dynamically update topology maps as changes occur, providing developers with a comprehensive, up-to-date view of the network.

These features help improve and automate strategic planning by offering insights into how changes impact the overall architecture.

AI and machine learning (ML) technologies enable observability tools to analyze the massive quantities of data computing networks generate and quickly detect anomalous patterns and system behaviors. AI-driven features can automatically correlate telemetry data across devices and layers to accelerate and fine-tune root cause analysis.

And, by using ML models, observability solutions can leverage predictive analytics to anticipate and rectify network performance issues before they create larger problems.

Change monitoring enables teams to track network modifications—such as configuration updates, software patches and hardware changes—in real time, so they can assess their impact on network performance.

This approach helps developers quickly identify any disruptions or degradations caused by new configurations or updates. However, observability tools are most effective when they correlate change data with performance data, and teams can see what changes occurred and why they affected network performance.

Network observability tools often integrate with other monitoring, logging and alerting systems (application performance monitoring services, for example). These integrations help provide IT personnel comprehensive insights across the entire technology stack, enhancing overall network visibility.

Organizations need effective tools to ensure sustained network reliability and performance in complex networks. Both network observability and network performance monitoring (NPM) can provide these tools. However, they differ significantly in approach, depth and capabilities.

Using simple network management protocol (SNMP) and other protocols, NPM tools collect and analyze predefined metrics to evaluate the performance of network devices, links and applications. It is a more traditional approach that primarily aims to identify and troubleshoot performance issues.

NPM tools focus on standard network metrics such as latency, throughput, jitter, packet loss and device resource utilization. They typically monitor individual devices or network segments without providing end-to-end visibility across distributed environments and often rely on static thresholds. If a metric exceeds the threshold, the NPM solution triggers an alert. However, static thresholds are preconfigured and might not adapt well to dynamic network conditions.

Furthermore, NPM tools typically detect and report issues after they occur, making them suitable for diagnosing—but not necessarily preventing—problems. And because NPM is limited to narrow monitoring parameters, NPM tools can fail to capture the full context of network behavior or provide actionable insights.

Whereas NPM focuses on measuring and reporting predefined metrics, network observability is a broader, more proactive approach that goes beyond metrics to provide a comprehensive, end-to-end view of network behavior. It provides deeper insights into the network's behavior by leveraging telemetry, context and advanced analytics. Observability tools can also adapt to changing network conditions, detecting anomalies without relying on static thresholds.

Crucially, network observability solutions can correlate data across layers, which helps accelerate root cause identification and resolution. These solutions are designed to clarify “what” is happening and explain “why” and “how” issues occur.

Observability tools can also map entire workflows or transactions, identifying issues across devices, clouds services and applications. And, using AI technologies and machine learning (ML) algorithms, observability tools can implement predictive analytics to forecast bottlenecks and failures, and enable proactive network optimization.

While network performance monitoring provides essential visibility into metrics and device health, it falls short in addressing the dynamic and complex nature of modern networks. Network observability builds upon NPM by offering deeper insights, richer context and advanced analytics to proactively ensure performance and reliability.

Network observability and DevOps observability are vital components of modern IT operations, each serving distinct yet complementary roles in maintaining computer networks.

DevOps observability focuses on the software development lifecycle (SDLC)—including applications, infrastructure and code—and aims to diagnose issues that arise during software development, deployment and operation. In a DevOps environment, observability is essential for maintaining visibility into feature and application delivery and performance, whether it’s for on-premises applications or cloud-native applications and associated orchestration tools.

DevOps observability solutions use a range of tools and techniques—including application performance management (APM), log management and distributed tracing—to optimize CI/CD pipelines and facilitate rapid detection of application issues. DevOps observability also ensures that development and operations teams have access to observability insights. This broad visibility helps simplify collaboration across teams and accelerate software releases.

However, DevOps observability tools aren’t designed to provide visibility into network performance. They don’t account for network-specific data (such as topology and overlays) and are therefore incapable of demonstrating how app performance correlates with underlying infrastructure performance in complex, distributed network architectures.

Network observability bridges the gap by enabling visibility into the performance of network infrastructure and its components. It’s primarily concerned with maintaining network reliability and resolving network-related issues. But network observability tools can also correlate application performance data with network telemetry and business objectives to provide a complete picture of enterprise computing environments.

Despite their differences, both types of observability are integral to ensuring the seamless performance of IT systems. Using both DevOps and network observability practices can help ensure that software applications, and the networks they rely on, perform optimally. These practices also help ensure that businesses can continue to adapt their computing environments as user needs and market conditions change.

Network observability solutions offer businesses a range of benefits, including:

By continuously monitoring network behavior, organizations can identify and resolve inefficiencies, driving optimal network performance for applications and services.

Network observability helps IT teams to detect anomalies and potential failures before they affect end users. Teams can set up filters to identify affected applications and analyze metrics (such as server workload) to quickly identify root causes, reduce network downtime and minimize mean time to resolution (MTTR).

With networks spanning on-premises and cloud environments, observability provides unified visibility, which helps ensure seamless operations across all platforms.

Traditional monitoring tools can evaluate network status, but network observability platforms can assess user experiences, regardless of where users are located. As users access web apps and APIs, network agents measure transaction speed, DNS lookup time and TLS handshake duration, alerting IT teams of any slowdowns or connectivity failures.

And with detailed root cause analyses, businesses can accelerate issue diagnosis to help ensure that users have seamless interactions with enterprise networks and services.

Bad actors often exploit network vulnerabilities to access data and deploy ransomware. However, network observability tools can fortify an organization’s security posture by continuously profiling traffic patterns.

If the system detects an anomaly—such as a sudden demand spike or a suspicious DNS lookup—it sends an alert, so teams can quickly address the issue. By integrating observability platforms with firewalls, teams can quickly quarantine security threats before they spread to other network devices.

Migrating to the cloud can pose significant performance, security and compliance risks, but observability tools can help ensure seamless operations across all platforms.

Before migration, businesses can use network observability platforms to establish baselines for on-premises application response times, bandwidth needs and security rules. And after migration, observability metrics can help teams verify capacity, availability and access controls, and address issues (such as packet loss) that negatively impact system performance.

Forecasting network capacity used to rely on guesswork, which led to bandwidth shortfalls and the overprovisioning of hardware and other resources. Leveraging historical traffic data from observability platforms (growth patterns across locations, for example) can help IT teams model capacity needs more accurately.

While cloud transitions often promise agility and savings, costs can rise significantly due to overprovisioning, unused instances and data transfer fees. Network observability tools help organizations avoid these issues by providing accurate insights into network capacity and resource usage, helping teams right-size cloud commitments and reduce expenditures.

In the financial services sector, network performance and reliability are foundational to success. Banks, insurance companies, trading platforms and other financial institutions depend on seamless connectivity to power mission-critical applications and processes (such as real-time trading, customer transactions, payment processing and regulatory compliance). Network observability plays a pivotal role in ensuring that operations remain secure and efficient.

Modern financial institutions handle millions of real-time transactions daily, ranging from credit card payments to stock trades, and latent transactions can lead to financial losses and damage reputations. For example, in high-frequency trading, a delay of just a few milliseconds can result in significant competitive disadvantages.

Network observability tools detect and address latency issues in real time, so institutions can mitigate—or avoid—such risks and maintain high-performing computing networks.

Furthermore, as financial services adopt cloud technologies to improve scalability and agility, they face the challenge of managing hybrid and multicloud environments. Network observability tools provide unified, end-to-end visibility across distributed, hybrid architectures, facilitating consistent financial platform performance throughout the network.

In the telecommunications industry, networks are the backbone of operations, supporting everything from voice calls and data services to Internet of Things (IoT) connectivity.

Telecom operators must deliver uninterrupted services to millions of customers—often across large, geographically dispersed areas—while managing increasingly dynamic network environments. Outages and performance degradations in these systems can lead to revenue losses, regulatory fines and customer churn.

Modern telecom networks often use hybrid and multicloud environments to support virtualized network functions (VNFs) and other services. And telecom operators are increasingly adopting AIOps practices and ML-driven automation to manage the scale of modern networks.

Network observability is foundational to the health of these networks. These tools help:

• Provide real-time visibility into the health and performance of network components such as base stations, fiber links and core infrastructure

• Correlate network performance metrics with customer-facing issues, such as dropped calls or slow internet speeds

• Enable self-healing networks, which integrate observability with orchestration platforms

• Track the performance of cloud-hosted VNFs, SDN elements and edge computing nodes in real time

• Generate predictive analytics, which can forecast capacity needs and potential failures

And, with the proliferation of 5G networks, telecom businesses are facing extraordinary levels of network complexity. 5G networks often rely on network slicing and edge computing capabilities and typically have very low latency requirements. Managing these components requires a deep understanding of network behavior across diverse environments.

Network observability tools can monitor 5G-specific metrics, providing insights into network slice performance and offering tailored solutions for specific use cases. For instance, telecom providers can use observability tools to ensure that a network slice dedicated to autonomous vehicles maintains ultra-reliable, low-latency performance.

They can also detect and resolve bandwidth issues in congested metropolitan areas and identify service degradation in streaming apps, enabling providers to address these issues before customer complaints arise.