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Network Observability vs. DevOps Observability

Shamus McGillicuddy

If you work in an IT organization, you've likely heard the term "observability" lately. If you're a DevOps pro, you probably know exactly what vendors are talking about when they use the term. If you're a NetOps pro, you might be scratching your head.

DevOps Knows Observability

The DevOps community is very familiar with the observability concept. It refers to the ability to understand the internal state of a system by measuring its external outputs. In DevOps, the system is the application, and the outputs are metrics, logs, and traces. DevOps pros know how to navigate messaging from application performance management and cloud monitoring vendors to find solutions that can deliver the observability they need.

More recently, network monitoring vendors have started talking about network observability. Here is where things get fuzzy. In my opinion, DevOps observability and network observability are not interchangeable. Why would they be?

DevOps teams want to understand the state of applications and the infrastructure on which they reside. NetOps teams need to understand a much larger universe of networks, from the cloud to the user edge.

Both DevOps observability and network observability refer to the need to understand the internal state of a system, but that need to understand is only a problem statement. The solution to that problem is where the differences occur.

Does Anyone Have Network Observability?

First, most NetOps teams care about application performance. They want to collect data from the application environment if they can, such as hypervisors and containers. But they don't stop there. They need to monitor data center networks, wide-area networks (WANs), and campus and branch networks. More recently, they've had to worry about home office networks.

Each network they monitor has become more complex. The data center network has been virtualized and partially extended into the public cloud. The WAN has hybridized, with a mix of managed WAN connectivity, public internet, and 4G/5G. Office networks are a mix of ethernet and Wi-Fi, connected via home internet.

A network observability system must monitor and analyze an extremely diverse and ever-growing data set to understand end-to-end network state. A NetOps team might use five, ten, or even fifty tools to monitor a network by collecting packets, flows, device logs, device metrics, test data, DNS logs, routing table changes, configuration changes, synthetic traffic, and more.

It's a lot to keep track of, and it's hard to find a single tool that can handle it all. In fact, my new research on the concept of network observability found that 83% of IT organizations are interested in streaming data from their network observability tool(s) to a central data lake. Why? Nearly half of them believe a data lake will help them correlate network data across their tools.

Earlier, I wrote that network observability is a bit "fuzzy." I'd argue that it's fuzzy because the problem of network observability is much bigger and more complex than DevOps observability. It may prove impossible for any single tool to solve this problem. That's perfectly okay. But IT organizations must keep this in mind and take a comprehensive approach to network operations tools as they steer toward the promise of network observability.

To learn more about network observability, check out EMA's November 9 webinar, which will highlight market research findings on the topic.

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Network Observability vs. DevOps Observability

Shamus McGillicuddy

If you work in an IT organization, you've likely heard the term "observability" lately. If you're a DevOps pro, you probably know exactly what vendors are talking about when they use the term. If you're a NetOps pro, you might be scratching your head.

DevOps Knows Observability

The DevOps community is very familiar with the observability concept. It refers to the ability to understand the internal state of a system by measuring its external outputs. In DevOps, the system is the application, and the outputs are metrics, logs, and traces. DevOps pros know how to navigate messaging from application performance management and cloud monitoring vendors to find solutions that can deliver the observability they need.

More recently, network monitoring vendors have started talking about network observability. Here is where things get fuzzy. In my opinion, DevOps observability and network observability are not interchangeable. Why would they be?

DevOps teams want to understand the state of applications and the infrastructure on which they reside. NetOps teams need to understand a much larger universe of networks, from the cloud to the user edge.

Both DevOps observability and network observability refer to the need to understand the internal state of a system, but that need to understand is only a problem statement. The solution to that problem is where the differences occur.

Does Anyone Have Network Observability?

First, most NetOps teams care about application performance. They want to collect data from the application environment if they can, such as hypervisors and containers. But they don't stop there. They need to monitor data center networks, wide-area networks (WANs), and campus and branch networks. More recently, they've had to worry about home office networks.

Each network they monitor has become more complex. The data center network has been virtualized and partially extended into the public cloud. The WAN has hybridized, with a mix of managed WAN connectivity, public internet, and 4G/5G. Office networks are a mix of ethernet and Wi-Fi, connected via home internet.

A network observability system must monitor and analyze an extremely diverse and ever-growing data set to understand end-to-end network state. A NetOps team might use five, ten, or even fifty tools to monitor a network by collecting packets, flows, device logs, device metrics, test data, DNS logs, routing table changes, configuration changes, synthetic traffic, and more.

It's a lot to keep track of, and it's hard to find a single tool that can handle it all. In fact, my new research on the concept of network observability found that 83% of IT organizations are interested in streaming data from their network observability tool(s) to a central data lake. Why? Nearly half of them believe a data lake will help them correlate network data across their tools.

Earlier, I wrote that network observability is a bit "fuzzy." I'd argue that it's fuzzy because the problem of network observability is much bigger and more complex than DevOps observability. It may prove impossible for any single tool to solve this problem. That's perfectly okay. But IT organizations must keep this in mind and take a comprehensive approach to network operations tools as they steer toward the promise of network observability.

To learn more about network observability, check out EMA's November 9 webinar, which will highlight market research findings on the topic.

The Latest

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...

In March, New Relic published the State of Observability for Media and Entertainment Report to share insights, data, and analysis into the adoption and business value of observability across the media and entertainment industry. Here are six key takeaways from the report ...

Regardless of their scale, business decisions often take time, effort, and a lot of back-and-forth discussion to reach any sort of actionable conclusion ... Any means of streamlining this process and getting from complex problems to optimal solutions more efficiently and reliably is key. How can organizations optimize their decision-making to save time and reduce excess effort from those involved? ...

As enterprises accelerate their cloud adoption strategies, CIOs are routinely exceeding their cloud budgets — a concern that's about to face additional pressure from an unexpected direction: uncertainty over semiconductor tariffs. The CIO Cloud Trends Survey & Report from Azul reveals the extent continued cloud investment despite cost overruns, and how organizations are attempting to bring spending under control ...

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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