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

Learn more about Honeycomb

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

Learn more about Honeycomb

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.

Hot Topics

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Agentic Remediation: Capitalizing on the New Era of Database Observability

Developers building AI applications are not just looking for fault patterns after deployment; they must detect issues quickly during development and have the ability to prevent issues after going live. Unfortunately, traditional observability tools can no longer meet the needs of AI-driven enterprise application development. AI-powered detection and auto-remediation tools designed to keep pace with rapid development are now emerging to proactively manage performance and prevent downtime ...

ZTNA 101: Common Misconceptions That Keep Companies From Adopting It

Every few years, the cybersecurity industry adopts a new buzzword. "Zero Trust" has endured longer than most — and for good reason. Its promise is simple: trust nothing by default, verify everything continuously. Yet many organizations still hesitate to implement Zero Trust Network Access (ZTNA). The problem isn't that ZTNA doesn't work. It's that it's often misunderstood ...

When Dashboards Say "Green" But Customers See Red: Why Digital Experience Still Fails at the Last Mile

For many retail brands, peak season is the annual stress test of their digital infrastructure. It's also when often technical dashboards glow green, yet customer feedback, digital experience frustration, and conversion trends tell a different story entirely. Over the past several years, we've seen the same pattern across retail, financial services, travel, and media: internal application performance metrics fail to capture the true experience of users connecting over local broadband, mobile carriers, and congested networks using multiple devices across geographies ...

Don't Fall Into These 5 PostgreSQL Traps

PostgreSQL promises greater flexibility, performance, and cost savings compared to proprietary alternatives. But successfully deploying it isn't always straightforward, and there are some hidden traps along the way that even seasoned IT leaders can stumble into. In this blog, I'll highlight five of the most common pitfalls with PostgreSQL deployment and offer guidance on how to avoid them, along with the best path forward ...

Why AI Is No Longer Optional for IT Operations

The rise of hybrid cloud environments, the explosion of IoT devices, the proliferation of remote work, and advanced cyber threats have created a monitoring challenge that traditional approaches simply cannot meet. IT teams find themselves drowning in a sea of data, struggling to identify critical threats amidst a deluge of alerts, and often reacting to incidents long after they've begun. This is where AI and ML are leveraged ...

Outages Aren't the Enemy, Complacency Is

Three practices, chaos testing, incident retrospectives, and AIOps-driven monitoring, are transforming platform teams from reactive responders into proactive builders of resilient, self-healing systems. The evolution is not just technical; it's cultural. The modern platform engineer isn't just maintaining infrastructure. They're product owners designing for reliability, observability, and continuous improvement ...

The Changing World of Application Delivery (and why it pays to have choices)

Getting applications into the hands of those who need them quickly and securely has long been the goal of a branch of IT often referred to as End User Computing (EUC). Over recent years, the way applications (and data) have been delivered to these "users" has changed noticeably. Organizations have many more choices available to them now, and there will be more to come ... But how did we get here? Where are we going? Is this all too complicated? ...

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On November 18, a single database permission change inside Cloudflare set off a chain of failures that rippled across the Internet. Traffic stalled. Authentication broke. Workers KV returned waves of 5xx errors as systems fell in and out of sync. For nearly three hours, one of the most resilient networks on the planet struggled under the weight of a change no one expected to matter ... Cloudflare recovered quickly, but the deeper lesson reaches far beyond this incident ...

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Chris Steffen and Ken Buckler from EMA discuss the Cloudflare outage and what availability means in the technology space ...

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Every modern industry is confronting the same challenge: human reaction time is no longer fast enough for real-time decision environments. Across sectors, from financial services to manufacturing to cybersecurity and beyond, the stakes mirror those of autonomous vehicles — systems operating in complex, high-risk environments where milliseconds matter ...