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Observability Maturity Brings Higher Productivity, Code Quality and End-User Satisfaction

More than half (61%) of respondents reported that their teams are practicing observability, an 8% increase from 2020, signaling that overall adoption is on the rise, according to a 2021 survey from Honeycomb with over 400 responses from across multiple industries and organization sizes.

However, the majority of respondents indicated their teams are at the earliest stages of observability maturity.

Key findings include:

Observability is gaining traction

61% of respondents reported that their teams are currently practicing observability, an increase of 8% from last year. That increase is sharply reflected across individual teams (up 7%) as opposed to entire organizations (up only 1%).

Mature teams realize more benefits

Teams on the higher end of the maturity spectrum realize more benefits than their less-mature counterparts. Teams that are mature in their observability practice realize even more impactful business outcomes, including deploying more frequently, being able to find bugs more quickly before and after pushing to production, and reduced burnout.

Mature teams deliver higher customer satisfaction

More-mature teams are also 3X more likely to deliver higher customer satisfaction. Teams that have achieved Intermediate or Advanced-level maturity reported their end-user customers are "Always Satisfied" with their service quality and capability at a rate of three times more than teams that do not practice observability.

Lack of implementation skills is a barrier

Lack of implementation skills is a disproportionate barrier for observability adoption. While interest in observability has gained significant momentum, organizations at the earliest stages of observability maturity report lack of implementation skills as the second-largest hurdle to observability adoption, indicating a need for more training options. All respondents indicated their primary hurdle was competing with other initiatives.

The Honeycomb maturity model outlines a progression of five distinct stages ranging from "Planning" or "Novice" (with limited observability capability and processes) to "Advanced" (with comprehensive processes). The highlights of this year's report indicate that:

■ 10% of those surveyed reported a combination of practices and tooling that reflect a highly observable system in the "Advanced" and "Intermediate" groups. These two groups highly prioritize observability: 50% practice observability across the organization and 43% on a team-by-team basis. Respondents also reported high public cloud use, and most work at large enterprises (57%) and in the tech industry (46%).

■ 37% of survey respondents fall into the "Novice" group. This group is more likely to self-report that they are practicing observability because they are using tools like logs, metrics, and traces. However, they also do not report having the key capabilities associated with practicing observability, such as having a comprehensive understanding of their systems, which suggests that respondents in this group may be focusing on the data needed for observability but not yet fully adopting the tools or practices of observability.

■ One in four teams are at the "Planning" stage or the very beginning of their observability journey and are starting to practice on a team-by-team basis. In this group, approximately one in five respondents do not currently practice or use observability tooling but have plans to do so within the next year.

The research verifies that teams on the higher end of the maturity spectrum are more likely to have:

■ Code that is well understood, well maintained, and fewer bugs than average.

■ The ability to follow predictable release cycles because they confidently address issues that arise.

■ Understanding of the end-to-end performance of their systems and how technical debt is costing their organization.

■ The ability to visualize context-rich events that allow efficient, focused, and actionable on-call processes.

■ The ability to prioritize responsiveness to user behavior and feedback.

■ Completely automated or mostly automated releases, resulting in reduced toil.

■ The ability to set and measure service level objectives, resulting in better alignment between engineering and business goals.

"This year, we're seeing that teams focused on building up their observability capabilities are identifying problems faster and producing better business outcomes," said Christine Yen, CEO and co-founder of Honeycomb. "Our observability maturity model can be used as a roadmap for anyone to see how organizations across the industry are approaching a fundamentally new way of understanding their production services. Teams can understand what's working, what's not, and how early investments in observability adoption are creating meaningful business impacts, so that they can achieve similar results."

Methodology: The 2021 Observability Maturity Community Research Findings study was conducted by ClearPath Strategies, an independent strategic consulting and public opinion research firm.

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Observability Maturity Brings Higher Productivity, Code Quality and End-User Satisfaction

More than half (61%) of respondents reported that their teams are practicing observability, an 8% increase from 2020, signaling that overall adoption is on the rise, according to a 2021 survey from Honeycomb with over 400 responses from across multiple industries and organization sizes.

However, the majority of respondents indicated their teams are at the earliest stages of observability maturity.

Key findings include:

Observability is gaining traction

61% of respondents reported that their teams are currently practicing observability, an increase of 8% from last year. That increase is sharply reflected across individual teams (up 7%) as opposed to entire organizations (up only 1%).

Mature teams realize more benefits

Teams on the higher end of the maturity spectrum realize more benefits than their less-mature counterparts. Teams that are mature in their observability practice realize even more impactful business outcomes, including deploying more frequently, being able to find bugs more quickly before and after pushing to production, and reduced burnout.

Mature teams deliver higher customer satisfaction

More-mature teams are also 3X more likely to deliver higher customer satisfaction. Teams that have achieved Intermediate or Advanced-level maturity reported their end-user customers are "Always Satisfied" with their service quality and capability at a rate of three times more than teams that do not practice observability.

Lack of implementation skills is a barrier

Lack of implementation skills is a disproportionate barrier for observability adoption. While interest in observability has gained significant momentum, organizations at the earliest stages of observability maturity report lack of implementation skills as the second-largest hurdle to observability adoption, indicating a need for more training options. All respondents indicated their primary hurdle was competing with other initiatives.

The Honeycomb maturity model outlines a progression of five distinct stages ranging from "Planning" or "Novice" (with limited observability capability and processes) to "Advanced" (with comprehensive processes). The highlights of this year's report indicate that:

■ 10% of those surveyed reported a combination of practices and tooling that reflect a highly observable system in the "Advanced" and "Intermediate" groups. These two groups highly prioritize observability: 50% practice observability across the organization and 43% on a team-by-team basis. Respondents also reported high public cloud use, and most work at large enterprises (57%) and in the tech industry (46%).

■ 37% of survey respondents fall into the "Novice" group. This group is more likely to self-report that they are practicing observability because they are using tools like logs, metrics, and traces. However, they also do not report having the key capabilities associated with practicing observability, such as having a comprehensive understanding of their systems, which suggests that respondents in this group may be focusing on the data needed for observability but not yet fully adopting the tools or practices of observability.

■ One in four teams are at the "Planning" stage or the very beginning of their observability journey and are starting to practice on a team-by-team basis. In this group, approximately one in five respondents do not currently practice or use observability tooling but have plans to do so within the next year.

The research verifies that teams on the higher end of the maturity spectrum are more likely to have:

■ Code that is well understood, well maintained, and fewer bugs than average.

■ The ability to follow predictable release cycles because they confidently address issues that arise.

■ Understanding of the end-to-end performance of their systems and how technical debt is costing their organization.

■ The ability to visualize context-rich events that allow efficient, focused, and actionable on-call processes.

■ The ability to prioritize responsiveness to user behavior and feedback.

■ Completely automated or mostly automated releases, resulting in reduced toil.

■ The ability to set and measure service level objectives, resulting in better alignment between engineering and business goals.

"This year, we're seeing that teams focused on building up their observability capabilities are identifying problems faster and producing better business outcomes," said Christine Yen, CEO and co-founder of Honeycomb. "Our observability maturity model can be used as a roadmap for anyone to see how organizations across the industry are approaching a fundamentally new way of understanding their production services. Teams can understand what's working, what's not, and how early investments in observability adoption are creating meaningful business impacts, so that they can achieve similar results."

Methodology: The 2021 Observability Maturity Community Research Findings study was conducted by ClearPath Strategies, an independent strategic consulting and public opinion research firm.

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The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

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 ...