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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

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...