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An Enterprise Guide to Network Observability

This guide will look at all components relating to network observability, explaining how it supports the digital workplace and empowers organizations.

What is Network Observability?

Network observability is the ability to actively measure performance using telemetry data, app metrics, logs, call metrics, flows, and synthetic testing to provide deep visibility into current and potential future trouble areas and the path your network traffic takes and any business risks associated with that path.

What is the Difference Between Observability and Monitoring?

Monitoring is the process of collecting, trending and analyzing system state metrics. It helps network professionals determine the health of the network. There is a clear distinction between network observability and network visibility / network monitoring.

Network Monitoring / Network Visibility

  • Monitoring is used to determine the state of applications and systems, to detect problems and anomalies, and to find the root cause of problems that you know and are measuring. For example with monitoring you need to know in advance which data points you are going to track for deviation, and the root cause is often many steps removed from the original symptom.

Network Observability

  • Observability is a superset of monitoring. It’s the ability to infer what’s happening to the internal states of various elements being observed by its outputs, going far beyond simple polling of metrics. Observability allows you to determine why problems occur in complex hybrid and cloud systems. Effective monitoring plays a significant role in enhancing observability, since observed data points come from metrics, events, logs, flows, traces, and synthetic testing.

Why is Observability Important?

With multiple technologies at play in every organization, and with a more dispersed workforce than ever before, simple monitoring will no longer suffice. Modern IT systems must be underpinned by observability tools to enable proactive and dynamic monitoring for a deep understanding of your business performance.

Monitoring and application performance tools lack the holistic view needed for the huge migration to public cloud architecture and using infrastructures that customers don’t own. IT teams need to get a better handle on things beyond their networks’ new complexity and increased service areas which almost always create gaps in visibility. The use of disparate tool sets makes it even harder to resolve problems, hence the push for machine learning, correlation, and observability.

What Is UC Observability?

UC Observability is unique to VOSS, the explosive year on year growth of cloud based UC&C services has posed challenges for many organizations due to lack of visibility into these service and cloud infrastructure. 

VOSS Insights uses NetFlow, UC monitored metrics, and synthetic testing to provide deep insight into your UC quality delivery AND allow you to proactively update problem areas before users experience issues.  

Here are three use cases for observability in the UC arena: 

  • The use of diverse UC data sources to understand what’s happening on the network and how it impacts business objectives and user experience
  • The ability to understand the quality of your UC service delivery (calls, meetings, etc.) across your network and be proactive to prevent user issues
  • The ability to understand user experience through the use of diverse data sources to see what’s happening on your network in real-time, by location

What Does UC Observability Do?

UC observability will help you answer questions like:

  • Why are my collaboration apps slow?
  • Are my collaboration apps prioritized correctly?
  • What path are my calls taking (how many hops, and latency at each hop)?
  • Is there packet loss or latency reaching cloud apps?
  • Is the network load impacting UC quality?
  • Are headsets or connected devices impacting user experience?
  • Are programed SLAs and baselines deviating?

Who Uses Observability?

Customers looking to focus on the experience of the end user and the health of a network connection rather than the individual devices along the way, will benefit from observability.

This includes network engineers looking for answers like:

  • Is there a network problem?
  • What applications are running on the network?
  • How much load are applications putting on the network?

What Are the Benefits of Observability?

According to AppDyanmics, there are four benefits of observability:

  • The ability to witness real-time system performance under various conditions
  • An abundance of telemetry data that is easily explored, searched, or referenced
  • Reduced MTTR due to the scope of information available to development and SRE teams
  • The validation and fined grained understanding that highly distributed applications and systems work as they should

Observability Tools

Observability tools give the IT team a far better insight into – and understanding of – applications. to improve delivery, performance, and customer experience.

Tech Target explains that an observability tool “provides a centralized platform for aggregating and visualizing telemetric data that has been collected from application and infrastructure components in a distributed environment. The tool monitors and analyzes application behavior and the various types of infrastructure that support application delivery, making it possible to proactively address issues before they become serious concerns.”

Observability Metrics

Network observability metrics are very useful as they focus on the end-to-end connection coupled with the experience of the end-user, rather than the individual devices along the way. A major goal of network observability is to proactively surface network dependencies or issues before they affect users and services.

How to Implement an Observability Strategy

Tech Target has defined 9 key steps to a successful Observability implementation strategy:

  1. Define your business goals
  2. Focus on the right metrics
  3. Stay on top of event logs
  4. Provide toggle switches for tools
  5. Perform diligent request tracing
  6. Create accessible data visualizations
  7. Choose the right observability platform
  8. Establish a culture of observability
  9. Use AI and machine learning to augment staff capabilities

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