If you want to know exactly what’s on your network and how it’s all connected in real time, then network observability is the answer. Network observability pulls data from sources across your network infrastructure to model a detailed view of your systems and how they interact. This lets you understand exactly what’s happening on your network at any given moment so you can optimize performance.

What is network observability?

Network observability provides comprehensive, real-time insights into the behavior, health, and performance of your network infrastructure. It goes beyond traditional network monitoring through the collection and correlation of data from across your network, including routers, switches, firewalls, servers, and applications. 

Network observability tools process and analyze this data to provide you with a detailed understanding of what’s going on in your network, letting you quickly detect and resolve issues. 

The important aspects of network observability include:

Telemetry data collection

Network observability relies on collecting telemetry data – which provides machine-readable information about your network’s status and performance—from infrastructure and apps across your network. This includes network flow data, syslogs, router tables, performance metrics, and more.

Centralized data analysis

Collected telemetry data is aggregated and enriched in a single observability platform which correlates and analyzes the data to extract meaningful insights. Advanced analytics techniques help detect anomalies and patterns.

Contextual visualization

Network observability platforms translate raw telemetry data into intuitive dashboards, topology maps, and visualizations providing real-time and historical visibility into the state of network components.

Rapid detection and root cause analysis

By processing numerous data signals from across the network, network observability solutions can rapidly detect issues, performance changes, and security threats. Granular data facilitates quick root cause analysis.

Closed-loop integration

Network observability platforms integrate with IT operations tools like helpdesks, automation platforms, and security information and event management (SIEM) solutions. This enables seamless processes for issue resolution and security response across teams.

Network observability vs. network monitoring

Businessman looking to the future with binoculars

Observability vs. network monitoring is a classic comparison. While observability and monitoring are complementary disciplines, observability moves beyond traditional monitoring in scale and analytical sophistication.

Let’s look at some key differences:

  • Data sources: Network monitoring focuses on device metrics like bandwidth usage, latency, errors, etc. Network observability incorporates broader sources—network flow records, application logs, process data, and messages—providing richer context.
  • Analytics: Monitoring alerts when metrics cross thresholds. Observability employs advanced analytics on multiple data types to uncover trends, anomalies, and root causes. This facilitates proactive optimization.
  • Understanding: Monitoring provides visibility into the external state of network components. Observability helps understand the relationships between components by correlating telemetry data from across sources.
  • Scalability: Traditional monitoring struggles with exploding volumes of metrics data. Observability is built to scale, efficiently processing high cardinality telemetry from cloud-scale environments.

While network monitoring asks “Is the network up?”, observability answers questions like “Why is this application performing slowly?” and “Which dependencies are impacting user experience” by providing real-time and historic visibility correlated across every tier of the networked environment.

Network observability vs. DevOps observability

Network observability complements DevOps observability which focuses on understanding the behavior of applications and their supporting infrastructure. DevOps observability is delivered through logs, metrics, and traces—data types that provide code-level visibility but lack network-specific context. 

Network observability enriches understanding of environment behavior by introducing network-centric telemetry like flow records, traffic rates, routing changes, ACLs, and underlay/overlay forwarding data. This provides the additional perspective to correlate network state with application performance for faster diagnosis of issues.

Why network observability is important

Network observability delivers immense value by enabling teams to troubleshoot faster, deliver better application experiences, strengthen security, smooth cloud migrations, control costs, plan accurately, and automate network management.

Let’s explore the top reasons network observability is so critical:

Resolve performance issues quickly

When business-critical applications slow down, network issues are often the culprit. Armed with observability data, you can interactively filter to the impacted apps and analyze correlated metrics like server workloads, network latency, and application logs to swiftly pinpoint root causes instead of spending all your time in firefighting mode.

Ensure superior end-user experiences

While traditional monitoring checks if networks are merely up, observability platforms proactively test user experiences from endpoints globally. As users access web apps and APIs, platform agents measure transaction speed, DNS lookup time, TLS handshake duration, and more. Alerts trigger for locations with slowness or connectivity failures while rich RCA data accelerates diagnosis across owned and unowned networks.

Detect and block security threats

Threat actors exploit network vulnerabilities, breach data, and unleash ransomware. Network observability strengthens defenses by continuously baseline-profiling traffic patterns. Sudden traffic spikes, anomalies, and suspicious DNS lookups trigger alerts for rapid incident response. Integrations with firewalls and SIEM solutions also help teams quickly quarantine detected threats.

Optimize cloud migrations

Migrating systems to the cloud risks performance, security, and compliance pitfalls. Leverage network observability to baseline on-prem application response times, bandwidth needs, and security rules. After migration, monitor metrics across network tiers to verify capacity, availability, and access controls, as well as fix issues like packet loss that degrade performance.

Control runaway cloud costs

While shifting to clouds promises agility and savings, costs can unexpectedly soar due to overprovisioning, unused instances, data transfer fees, and more. Network observability provides visibility into traffic and resource usage trends enabling teams to right-size cloud commitments by decommissioning unused environments, re-architecting inefficient data routes, and renegotiating transit contracts based on actual network needs.

Forecast and plan network capacity

Forecasting network capacity needs used to involve guesswork leading to bandwidth shortfalls or overbuilding. Leverage historical traffic data and synthesis testing from network observability platforms to accurately model capacity requirements for the near to medium term. Growth patterns across locations, protocols, and applications ensure network expansions precisely align with your business roadmap.

Accelerate root cause analysis

Determining the exact cause of network issues can mean hopping between tools and piecing together data. Network observability solutions save precious troubleshooting time by automatically pulling and correlating cross-domain data to provide context for events. Teams can swiftly trace root causes instead of just reacting to alerts.

Automate manual management tasks

Mundane network admin tasks like configuring new gear, documenting inventory, assessing firmware versions, and validating redundancy consume massive time. Network observability platforms integrate with network controllers and IT systems to fully automate device provisioning, backups, failover tests, and compliance reporting. This frees up teams for more impactful projects.

Network observability tools and techniques

Network observability tools employ various techniques to collect, analyze, and visualize telemetry data from across your network environment. The resulting network visibility of your network’s essential components is key to understanding how systems relate and are connected to one another. Some of the core techniques and technologies enabling modern network observability include:

Flow analysis

Flow analysis refers to using network flow records – which provide aggregated data about IP communications between devices – to understand traffic patterns and bandwidth utilization across the network. Flow records, exported in protocols like NetFlow, IPFIX, or sFlow, can be collected from routers, switches, and other infrastructure and synthesized to deliver insights into top applications, traffic volumes, geo-distribution, and changes.

Packet capture

Packet capture (PCAP) provides deep visibility into network behavior by recording data packets verbatim as they are transmitted over links. While flow records provide metadata, packet capture allows every single packet—along with payload data—to be inspected. This level of granular data facilitates diagnosing connectivity issues and security events. Packet capture helps validate flow analytics and enables capacity planning.

Log analysis

System, application, security, and network logs contain valuable details about the transactions, events, errors, and state changes occurring across the IT environment. Centralizing and correlating logs from servers, containers, network gear and other infrastructure in a unified analytics platform helps connect the dots during root cause investigation. Parsing unstructured log data to extract key attributes speeds monitoring.

Distributed tracing

Microservices application architectures have surged in complexity with dozens of interconnected services distributed across environments. Distributed tracing instruments code running throughout all services with unique identifiers so requests can be followed as they flow through the entire system. Gathering distributed traces in the observability platform provides a precise transaction-centric view to optimize complex applications.

Network topology mapping

Observability platforms automatically map network infrastructure elements along with the real-time status and metrics for devices and links. This provides a single contextual topology view for visualizing the connections and relationships between servers, containers, network switches, firewalls, load balancers, and application delivery components. Integrated topology maps speed diagnosis of issues and planning.

Implementing network observability

Getting network observability running smoothly in your environment calls for thoughtful planning across people, processes, and technologies:

  • Define your goals first: Start by aligning on the main challenges network observability should address. Whether it’s diagnosing cloud app latency, strengthening security, or planning capacity, map out required data sources, metrics, and analytics to guide your tech selection.
  • Carefully choose the right tools: With goals established, critically assess observability tools against visibility, analytics, scalability, usability, and integration requirements. You can build a business case using ROI metrics like faster problem resolution.
  • Centralize network data gathering: Enabling thorough data collection is essential. To this end, turn on polling protocols on devices to feed monitoring platforms and aggregate logs centrally. Also, consider adding sensors to acquire packet-level details and outlining a central data architecture to store this long-term.
  • Set dynamic performance thresholds: Smart algorithms can learn normal network behavior, with teams validating thresholds for key metrics by area. Configure alerts for threshold breaches and integrate monitoring with response platforms to speed awareness.
  • Apply automation for efficiency: Feed observability data into network automation platforms enabling self-correction, like traffic rerouting during overloads. Also, integrate config tools to elastically scale capacity based on live network usage signals.
  • Bring teams together: Break down silos between network, security, and application teams for better collaboration. Provide unified troubleshooting visibility with secure access for self-service insights.
  • Continually optimize over time: Given regular change, periodically review your monitoring setup—evaluate new gear for coverage gaps, revisit reports and dashboards, and validate processes. 

Overcoming network observability challenges

Implementing network observability can entail certain challenges that you should be aware of:

  • Dealing with data silos: Disparate monitoring tools often create fragmented data sets across network tiers. You need to consolidate data in an observability platform to achieve unified visibility. Carefully evaluate existing sources and gaps.
  • Ensuring scalability: Network environments and data volumes tend to expand rapidly. Observability systems must efficiently store high-cardinality telemetry and quickly query large datasets to avoid degradation. Choose analytics-optimized platforms.
  • Achieving holistic visibility: Gaining end-to-end visibility across hybrid network infrastructure with virtualization and encryption is hard. Seek observability tools with comprehensive visibility into physical and virtual devices across data centers, clouds, and the WAN.
  • Justifying costs/ROI: While observability requires investment, the gains in productivity, performance, and security translate to hard ROI through cost avoidance in outages as well as optimized cloud usage and staff efficiency. Factor in these areas when making the business case.
  • Integrating monitoring data: To enable unified troubleshooting workflows, integrate network-centric telemetry from your observability system with event, metrics, and tracing data from broader monitoring stacks. Leverage APIs for cross-system correlation.
  • Building in-house expertise: Getting value from your observability platform relies on your team having the skills to configure monitoring, analyze outcomes, and trigger action. Formalize expertise-building through vendor training and community learning.
  • Securing network telemetry: Telemetry data can include sensitive details like customer traffic patterns and application performance characteristics. Evaluate security measures around data access, encryption, data handling policies, and access controls.

While achieving holistic, scalable, and actionable network observability has challenges, the visibility and troubleshooting superpowers it unleashes make surmounting these hurdles incredibly worthwhile for critical network operations teams.

Network observability FAQ

What is the difference between network observability and monitoring?

Network monitoring focuses on tracking performance metrics and device health to detect issues. Network observability provides a deeper, real-time analysis of interdependencies and patterns across network components to understand root causes.

What are the basic concepts of network observability?

The core concepts are real-time telemetry collection, advanced analytics for insight, and integrated workflows to enable action based on monitoring data.

What are network observability tools?

Network observability tools are software platforms that collect, analyze, and contextualize network infrastructure telemetry to provide visibility into overall behavior and health. They move beyond basic monitoring.

Why has network observability become more critical recently?

Exploding infrastructure complexity from virtualization, multi-cloud, overlays, and dynamic workloads has made troubleshooting network issues more challenging. Network observability addresses this.

How can network observability boost IT productivity?

By providing unified troubleshooting data and automation rather than having engineers piece together insights from multiple tools, issues can be diagnosed and addressed faster.

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