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The OpenTelemetry Getting Started Survey: Understanding Users' Observability Journeys

Ana Margarita Medina
Senior Staff Developer
ServiceNow

Organizations can face significant challenges, ranging from skill development to user adoption, when implementing new technologies. This is particularly evident in the realm of observability, an increasingly critical area for organizations striving to maintain optimal performance and reliability across digital applications. Recently, the OpenTelemetry End-User SIG surveyed more than 100 OpenTelemetry users to learn more about their observability journeys and what resources deliver the most value when establishing an observability practice.

Most respondents have initiated their observability journey, whether they are in the process of standing up an observability practice or are already well-established. Regardless of experience level, there's a clear need for more support and continued education, especially in helping those who are just starting with observability technologies. When asked what resources they wish they had when getting started with OpenTelemetry, more than half (67%) said they wanted comprehensive documentation, quickly followed by reference implementations for instrumentation (65%), and more detailed tutorials (63%).



When getting started with observability, most respondents are working with containerization technologies, with about 80% using Kubernetes and 63% using Docker.


While quite a few languages are used across organizations, more than 50% of respondents utilize JavaScript, Java, Go, and Python.


The majority of respondents stated that Traces Specification, Instrumentation APIs and SDKs, and Metrics Specification are the most important aspects of their OpenTelemetry journeys.


Observability will continue to be a cornerstone for organizations to not only measure and understand application performance, but to also build resilience into technology stacks. It's imperative for leaders to empower their teams with the necessary tools and knowledge, as they play a pivotal role in the successful adoption and implementation of observability practices. By equipping teams with the proper resources, organizations can overcome the common challenges associated with implementing new technologies, ensuring a smoother transition and maximizing the full potential of their observability initiatives.

Ana Margarita Medina is a Senior Staff Developer at ServiceNow

The Latest

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

In MEAN TIME TO INSIGHT Episode 15, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Do-It-Yourself Network Automation ... 

Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...

Traditional observability requires users to leap across different platforms or tools for metrics, logs, or traces and related issues manually, which is very time-consuming, so as to reasonably ascertain the root cause. Observability 2.0 fixes this by unifying all telemetry data, logs, metrics, and traces into a single, context-rich pipeline that flows into one smart platform. But this is far from just having a bunch of additional data; this data is actionable, predictive, and tied to revenue realization ...

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...

The OpenTelemetry Getting Started Survey: Understanding Users' Observability Journeys

Ana Margarita Medina
Senior Staff Developer
ServiceNow

Organizations can face significant challenges, ranging from skill development to user adoption, when implementing new technologies. This is particularly evident in the realm of observability, an increasingly critical area for organizations striving to maintain optimal performance and reliability across digital applications. Recently, the OpenTelemetry End-User SIG surveyed more than 100 OpenTelemetry users to learn more about their observability journeys and what resources deliver the most value when establishing an observability practice.

Most respondents have initiated their observability journey, whether they are in the process of standing up an observability practice or are already well-established. Regardless of experience level, there's a clear need for more support and continued education, especially in helping those who are just starting with observability technologies. When asked what resources they wish they had when getting started with OpenTelemetry, more than half (67%) said they wanted comprehensive documentation, quickly followed by reference implementations for instrumentation (65%), and more detailed tutorials (63%).



When getting started with observability, most respondents are working with containerization technologies, with about 80% using Kubernetes and 63% using Docker.


While quite a few languages are used across organizations, more than 50% of respondents utilize JavaScript, Java, Go, and Python.


The majority of respondents stated that Traces Specification, Instrumentation APIs and SDKs, and Metrics Specification are the most important aspects of their OpenTelemetry journeys.


Observability will continue to be a cornerstone for organizations to not only measure and understand application performance, but to also build resilience into technology stacks. It's imperative for leaders to empower their teams with the necessary tools and knowledge, as they play a pivotal role in the successful adoption and implementation of observability practices. By equipping teams with the proper resources, organizations can overcome the common challenges associated with implementing new technologies, ensuring a smoother transition and maximizing the full potential of their observability initiatives.

Ana Margarita Medina is a Senior Staff Developer at ServiceNow

The Latest

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

In MEAN TIME TO INSIGHT Episode 15, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Do-It-Yourself Network Automation ... 

Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...

Traditional observability requires users to leap across different platforms or tools for metrics, logs, or traces and related issues manually, which is very time-consuming, so as to reasonably ascertain the root cause. Observability 2.0 fixes this by unifying all telemetry data, logs, metrics, and traces into a single, context-rich pipeline that flows into one smart platform. But this is far from just having a bunch of additional data; this data is actionable, predictive, and tied to revenue realization ...

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...