Observability Tools Fall Short
January 25, 2023

Shannon Weyrick

Share this

As companies generate more data across their network footprints, they need network observability tools to help find meaning in that data for better decision-making and problem solving. It seems many companies believe that adding more tools leads to better and faster insights. Earlier this year, the research firm Enterprise Management Associates (EMA) found more than 35% of organizations used 11 or more tools for network operations, and more than 50% used six or more.

And yet, observability tools aren't meeting many companies' needs. In fact, adding more tools introduces new challenges. Only one in four companies say they are successful with their network observability tools, according to a recent EMA and NS1 survey of IT stakeholders, and just 15.2% can identify and fix every network issue before it harms the organization.

Observability strategies are being held back both by the strategies surrounding tool adoption, and the capabilities of the tools themselves. Companies are responding to increased data in ways that add complexity and cost, and networking teams aren't obtaining immediate insight from their observability tools, which leaves them unable to quickly find or remediate network issues.

Let's review the data surrounding these shortcomings:

More Data and More Tools Bring Growing Pains

Increasingly complex networks are now generating more data — 85% of firms report that they have recently increased the amount of data they collect — and many companies are eager to take advantage of this increase. But companies can quickly run out of quota or storage space, resulting in either short retention times or substantial cost increases, and 43.5% of respondents say that data storage is now a major challenge.

Networking teams often respond to more data with more tools because their current ones aren't sufficient. More than 50% of respondents said they don't believe they have a single network observability tool that can fully answer any network question. Yet adding more tools often requires expensive customization, according to 54% of respondents, and even once set up is done, 46% say that conflicts between observability tools are a major problem.

Actionable Insights Remain a Work in Progress

Networking teams need observability tools to provide them with immediate insight so they can take action, but in practice, getting insights often requires excessive time and effort. Only one-third of respondents say obtaining a global view of network operations is very easy, and four in five say they are not fully satisfied with the ability to obtain insights from the tools they use. It's no surprise that 84.8% of respondents cannot detect every network issue before problems arise, and 88.8% cannot remediate every issue before problems occur.

Another significant problem is the high rate of false alarms — tool alerts that are ultimately meaningless but require investigation anyway. Remarkably, respondents report that 53% of all alerts are false alarms. This represents a tremendous time sink that likely contributes to three in four respondents saying they are not fully satisfied with their network tooling.

For companies overwhelmed by data storage and a failure to obtain insight, it may be worth deploying observability agents on the edge where data is generated. Such agents can analyze data in real time, so networking teams can bypass the challenges associated with backhauling potentially unused raw data and obtain real-time insight for rapid issue detection and remediation.

Moving forward, it is essential for the people who build network observability tools to understand what networking teams need. This includes deep but dynamically defined data collection with meaningful insights, especially regarding network and application performance, network security, and the end-user experience.

Shannon Weyrick is VP of Research at NS1
Share this

The Latest

June 20, 2024

The total cost of downtime for Global 2000 companies is $400 billion annually — or 9% of profits — when digital environments fail unexpectedly, according to The Hidden Costs of Downtime, a new report from Splunk ...

June 18, 2024

With the rise of digital transformation and the increasing reliance on applications for business operations, the need for application performance management (APM) has become more critical ... This blog explains what APM is all about, its significance and key features ...

June 17, 2024

Generative AI (GenAI) has captured significant attention by redefining content creation and automation processes. Despite this surge in GenAI's popularity, it's crucial to highlight the continuous, vital role of machine learning (ML) in underpinning crucial business functions. This era is not about GenAI replacing ML; rather, it's about these technologies collaborating to supercharge intelligent automation across industries ...

June 13, 2024

As organizations continue to navigate their digital transformation journeys, the need for efficient, secure, and scalable data movement strategies has never been more critical ... In an era when enterprise IT landscapes are continually evolving, the strategic movement of data has become a cornerstone of maintaining agility, competitive edge, and operational efficiency ...

June 12, 2024

In May, New Relic published the State of Observability for IT and Telecommunications Report to share insights, statistics, and analysis on the adoption and business value of observability for the IT and telecommunications industries. Here are five key takeaways from the report ...

June 11, 2024
Over the past decade, the pace of technological progress has reached unprecedented levels, where fads both quickly rise and shrink in popularity. From AI and composability to augmented reality and quantum computing, the toolkit of emerging technologies is continuing to expand, creating a complex set of opportunities and challenges for businesses to address. In order to keep pace with competitors, avoiding new models and ideas is not an option. It's critical for organizations to determine whether an idea has transformative properties or is just a flash in the pan — a challenge tackled in Endava's new 2024 Emerging Tech Unpacked Report ...
June 10, 2024

The rapidly evolving nature of the industry, particularly with the recent surge in generative AI, can catch firms off-guard, leaving them scrambling to adapt to new trends without the necessary funds ... This blog will discuss effective strategies for optimizing cloud expenses to free up funds for emerging AI technologies, ensuring companies can adapt and thrive without financial strain ...

June 06, 2024

Software developers are spending more than 57% of their time being dragged into "war rooms" to solve application performance issues, rather than investing their time developing new, cutting-edge software applications as part of their organization's innovation strategy, according to a new report from Cisco ...

June 05, 2024

Generative Artificial Intelligence (GenAI) is continuing to see massive adoption and expanding use cases, despite some ongoing concerns related to bias and performance. This is clear from the results of Applause's 2024 GenAI Survey, which examined how digital quality professionals use and experience GenAI technology ... Here's what we found ...

June 04, 2024

Many times customers want to know why their measured performance doesn't match the speed advertised (by the platform vendor, software vendor, network vendor, etc). Assuming the advertised speeds are (a) within the realm of physical possibility and obeys the laws of physics, and (b) are real achievable speeds and not "click-bait," there are at least ten reasons for being unable to achieve advertised speeds. In situations where customer expectations and measured performance don't align, use the following checklist to help determine the reason(s) why ...