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Navigating the Observability Landscape: Highlights From Grafana Labs’ 2024 Surveyby@grafana
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Navigating the Observability Landscape: Highlights From Grafana Labs’ 2024 Survey

by Grafana LabsMarch 21st, 2024
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To better understand where organizations are in their observability journeys — as well as the wins and losses that have come as a result — we solicited feedback from the community for our second annual Grafana Labs Observability Survey. We heard from more than 300 industry practitioners who shared their experiences, helping to provide an intriguing snapshot of where the industry is today and where it’s headed.
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Regardless of the industry they operate in or the number of people they employ, businesses with mature observability practices can respond to incidents faster — and save time and money in the process, according to the second annual Grafana Labs Observability Survey.


Organizations are making observability a critical part of their software development lifecycles as they grapple with the complexity of modern applications. However, this year’s survey makes it clear that not everyone is at the same stage of adoption, with teams that are further behind struggling to keep up with the always-on demands of today’s users.


More than 300 observability practitioners participated in the survey. They shared their thoughts on a wide range of topics, including the varying degrees of maturity, the sheer volume of tools in use, the lingering concerns about expenses, and the ubiquity of open-source tools in this still-emerging market.

Key Takeaways From the Grafana Labs Observability Survey

You can read the full survey to learn what respondents had to say about these topics and more, but for a quick assessment of the state of observability, here are the five key takeaways from the survey.

Observability Practices Are Still Maturing

We gauged where respondents were in their journeys by asking how they approached observability.  A little over half say their organization has taken a proactive approach, which points to the growth in this space. However, organizations are still more likely to be reactive than systematic, which means they often hear about problems from their customers rather than have systems in place to address issues before their users ever find out.

A breakdown of the observability maturity levels, including reactive, proactive, and systematic

(Check out our Observability Journey Maturity Model for more on these designations.)


And the different approaches can result in very different outcomes, with 65% of those with a systematic approach having saved time or money through centralized observability, compared to just 35% of those who take a reactive approach.

Tool and Data Sprawl Remains a Major Hurdle

More than two-thirds of teams use at least four observability technologies, with respondents collectively citing more than 60 technologies currently in use. In addition, half of Grafana users say they have at least six different data sources configured and actively in use in Grafana.

A chart showing the number of observability technology used at the group and company level

This can translate to considerable complexity and overhead, and the bigger the company, the more tools and data sources they have. It’s no wonder that among teams that have centralized observability, 79% say it has saved them time or money as a result.

Open Source Is the De Facto Standard

We cater to a vibrant open-source community at Grafana Labs. And while that likely skews the results in our survey, there’s no denying the impact of OSS. Eight of the 10 most popular technologies cited in our survey are open source, while an overwhelming majority of respondents are investing in Prometheus (89%) or OpenTelemetry (85%).
A chart of the most used observability technologies

Interestingly, there’s considerable overlap between the Prometheus and OpenTelemetry communities. Almost 40% of respondents use both in their operations, and more than 50% increased their usage of each project over the past year.

AI Could Play a Big Role — Eventually

AI is getting tons of attention these days, but its role in observability is largely aspirational today. Still, observability practitioners remain excited about its potential to accelerate incident response and simplify observability adoption.

A chart of the AI/ML-powered features respondents say would be most valuable to them

Anomaly detection is the most cited AI-enabled feature respondents say they would like to see, with more than three-quarters calling it out. Other top wish-list items for AI include predictive analytics and dashboard generation.

Cost Emerges as a Top Concern

More than half of respondents say cost is their biggest concern about observability, while other related topics — cardinality, unpredictable bills, and vendor lock-in — are also cited.

A chart listing the biggest concerns about observability