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The State of Observability 2022

The most sophisticated observability practitioners (leaders) are able to cut downtime costs by 90%, from an estimated $23.8 million annually to just $2.5 million, compared to observability beginners, according to the State of Observability 2022 from Splunk in collaboration with the Enterprise Strategy Group.


What's more, leaders in observability are more innovative and more successful at achieving digital transformation outcomes and other initiatives:

■ Observability leaders have launched 60% more products or revenue streams from AppDev teams in the last year compared to beginners.

■ Observability leaders report a 69% better mean time to resolution for unplanned downtime or performance degradation thanks to investment in observability.

■ 66% of leaders report that their visibility into application performance is excellent (compared to just 44% of beginners). Similarly, 64% of leaders report that visibility into their security posture is excellent (versus 42% of beginners).

■ Twice as many leaders can detect problems associated with internally developed applications within minutes, resulting in an estimated 37% better MTTD.

"Our research confirms just how vital observability is for every business," said Spiros Xanthos, SVP and General Manager, Observability, Splunk. "The most sophisticated observability practitioners have given themselves an edge in digital transformation while massively cutting costs associated with downtime and boosting their ability to out-innovate the competition. These observability leaders are more competitive, more resilient and more efficient as a result."

Increased cloud complexity also highlights how imperative becoming an observability leader is for all enterprises. Organizations have been moving to the cloud for more than a decade and in more recent years, hybrid architectures and multicloud operations have complicated many organizations' cloud ecosystems.

70% of respondents are using multiple cloud services, and the shift to multicloud has increased complexity:

■ 75% of respondents have many cloud-native applications that run in multiple environments, either multiple public clouds or a combination of on-premises and public clouds.

■ Leaders are even more likely to report commonly running cloud-native applications (92% versus 68% of beginners),

■ 36% of organizations (and 47% of leaders) that use the public cloud to run internally developed applications use three or more different public clouds today, and 67% expect to do so within 24 months.

While the challenges of observability are global, the report reveals that there are significant variations across countries:

■ Canadian organizations trail in their observability journey: 79% are beginners (versus 58% averaged across other countries) and just 2% are leaders (versus 10% in the rest of the world).

■ French organizations more often report that their investments in AIOps technologies have helped them achieve lower mean time to resolution (MTTR) (58% versus 43% averaged across other countries).

■ Japanese organizations have had noteworthy success using AIOps technologies to help solve recurring issues in their environment: 74% report that this has been a benefit of AIOps, versus a 55% average across other countries.

■ Indian organizations are further along in the observability journey: Only 29% are rated as beginners, versus 62% on average across other countries.

For organizations across the globe looking to invest in observability, a lack of staff is one of the biggest hindrances in improving observability. Among respondents, 95% reported challenges in finding staff to monitor and manage infrastructure and application availability, while 81% of enterprises said a lack of staff had led to projects and initiatives failing.

"Organizations that use the right observability tools and practices and build to attract talent stand the best chance of becoming leaders in observability," said Xanthos. "By tackling data volume and variety with AI, organizations can alleviate staffing concerns, while at the same time investing in skills training to draw in the very best talent available. Consolidating vendors and rationalizing tools will also allow companies to curate the vendor and tool set that gives them the most visibility with the least drag, lessening the potential for staff burnout in the process."

Methodology: The global survey was conducted from early-February through mid-February 2022 in partnership with the Enterprise Strategy Group. The 1,250 application development and IT operations leaders who spend more than half of their time on observability issues were drawn from 11 regions: Australia, Canada, France, Germany, India, Japan, The Netherlands, New Zealand, Singapore, The United Kingdom and the United States.

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The State of Observability 2022

The most sophisticated observability practitioners (leaders) are able to cut downtime costs by 90%, from an estimated $23.8 million annually to just $2.5 million, compared to observability beginners, according to the State of Observability 2022 from Splunk in collaboration with the Enterprise Strategy Group.


What's more, leaders in observability are more innovative and more successful at achieving digital transformation outcomes and other initiatives:

■ Observability leaders have launched 60% more products or revenue streams from AppDev teams in the last year compared to beginners.

■ Observability leaders report a 69% better mean time to resolution for unplanned downtime or performance degradation thanks to investment in observability.

■ 66% of leaders report that their visibility into application performance is excellent (compared to just 44% of beginners). Similarly, 64% of leaders report that visibility into their security posture is excellent (versus 42% of beginners).

■ Twice as many leaders can detect problems associated with internally developed applications within minutes, resulting in an estimated 37% better MTTD.

"Our research confirms just how vital observability is for every business," said Spiros Xanthos, SVP and General Manager, Observability, Splunk. "The most sophisticated observability practitioners have given themselves an edge in digital transformation while massively cutting costs associated with downtime and boosting their ability to out-innovate the competition. These observability leaders are more competitive, more resilient and more efficient as a result."

Increased cloud complexity also highlights how imperative becoming an observability leader is for all enterprises. Organizations have been moving to the cloud for more than a decade and in more recent years, hybrid architectures and multicloud operations have complicated many organizations' cloud ecosystems.

70% of respondents are using multiple cloud services, and the shift to multicloud has increased complexity:

■ 75% of respondents have many cloud-native applications that run in multiple environments, either multiple public clouds or a combination of on-premises and public clouds.

■ Leaders are even more likely to report commonly running cloud-native applications (92% versus 68% of beginners),

■ 36% of organizations (and 47% of leaders) that use the public cloud to run internally developed applications use three or more different public clouds today, and 67% expect to do so within 24 months.

While the challenges of observability are global, the report reveals that there are significant variations across countries:

■ Canadian organizations trail in their observability journey: 79% are beginners (versus 58% averaged across other countries) and just 2% are leaders (versus 10% in the rest of the world).

■ French organizations more often report that their investments in AIOps technologies have helped them achieve lower mean time to resolution (MTTR) (58% versus 43% averaged across other countries).

■ Japanese organizations have had noteworthy success using AIOps technologies to help solve recurring issues in their environment: 74% report that this has been a benefit of AIOps, versus a 55% average across other countries.

■ Indian organizations are further along in the observability journey: Only 29% are rated as beginners, versus 62% on average across other countries.

For organizations across the globe looking to invest in observability, a lack of staff is one of the biggest hindrances in improving observability. Among respondents, 95% reported challenges in finding staff to monitor and manage infrastructure and application availability, while 81% of enterprises said a lack of staff had led to projects and initiatives failing.

"Organizations that use the right observability tools and practices and build to attract talent stand the best chance of becoming leaders in observability," said Xanthos. "By tackling data volume and variety with AI, organizations can alleviate staffing concerns, while at the same time investing in skills training to draw in the very best talent available. Consolidating vendors and rationalizing tools will also allow companies to curate the vendor and tool set that gives them the most visibility with the least drag, lessening the potential for staff burnout in the process."

Methodology: The global survey was conducted from early-February through mid-February 2022 in partnership with the Enterprise Strategy Group. The 1,250 application development and IT operations leaders who spend more than half of their time on observability issues were drawn from 11 regions: Australia, Canada, France, Germany, India, Japan, The Netherlands, New Zealand, Singapore, The United Kingdom and the United States.

Hot Topics

The Latest

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...