Skip to main content

A Guide to OpenTelemetry - Part 5: The Challenges

Pete Goldin
APMdigest

While OpenTelemetry offers many advantages, the experts point out several challenges as well.

Start with: A Guide to OpenTelemetry - Part 1

Start with: A Guide to OpenTelemetry - Part 2: When Will OTel Be Ready?

Start with: A Guide to OpenTelemetry - Part 3: The Advantages

Start with: A Guide to OpenTelemetry - Part 4: The Results

The Project is Not Mature

Maybe the greatest challenge for OpenTelemetry is that the project is not mature. While the tracing component is fairly well advanced, the metrics and logging parts are still being formed.

"Currently, the project is not mature enough to support every stack, language, and signal," says Michael Haberman, CTO and Co-Founder of Aspecto. "While we believe it'll get there, the road to full stability is long."

"OpenTelemetry remains a young project in many ways, and many components are still in alpha or beta," explains Austin Parker, Head of Developer Relations at Lightstep by ServiceNow. "There is still work being done to bring in new signals such as profiling, logging, or real user monitoring (RUM), and breaking changes in those signals can be frequent."

"Logs and metrics are slowly catching up, but the API is still unstable which can be an issue," adds Vladimir Mihailenco, Co-Founder of Uptrace. "Logs and metrics are not stable yet so using them is more bumpy and requires some involvement with OpenTelemetry development and reading various changelogs."

Varying Quality

"While the existing OpenTelemetry libraries are already viable for manual and automatic instrumentation, which is a key part of any observability solution, it varies in quality," says Daniel Khan, Director of Product Management (Telemetry) at Sentry. "With new versions of libraries being released almost daily, it is up to the Open Source community to reverse engineer and adapt the instrumentation for every new version. This is not sustainable. Now is the time when library and framework maintainers have to start adding OpenTelemetry to their code. If this doesn't happen, the production use-case for OpenTelemetry will stay rather limited."

"The maturity of documentation, specification, libraries, and collector varies. One's experience might be very different depending on what they want to achieve," Marcin "Perk" Stożek, Software Engineering Manager of Open Source Collection, Sumo Logic, adds.

Bugs

"OpenTelemetry is developing at a fast rate, and the instrumentation is rapidly changing. This can lead to frustrating bugs at times. But the community is actively taking steps to address concerns around instrumentation stability," says Pranay Prateek, Co-Founder of SigNoz.

Does Not Provide Backend Storage, Analysis or Visualization

Another important challenge to be aware of: OpenTelemetry does not provide any backend storage, analysis or visualization, so to gain full value of the project you need to implement these components on your own or with the help of a service provider.

"Without the proper tools and integrations, it can be challenging to make sense of what the data OpenTelemetry uncovers, and what was meant to provide visibility into IT performance and availability could actually end up creating more data noise instead," says Joe Byrne, VP of Technology Strategy and Executive CTO at Cisco AppDynamics.

Requires Large-Scale Initiative

To truly adopt OpenTelemetry requires a large-scale effort by an organization.

"Users will have to replace some of their existing toolchains of telemetry collection (especially for logs and metrics)," Haberman of Aspecto points out. "It will require quite a lot of effort, and usually, companies are not excited to make this large-scale shift."

"Migrating from current proprietary collection technologies to OpenTelemtry is non trivial for any large customer," adds Nitin Navare, CTO of LogicMonitor.

Difficult to Manage at Scale

"As OpenTelemetry evolves, it will become more complex and challenging to configure and manage at scale," warns Jonah Kowall, CTO of Logz.io.

Alois Reitbauer, Chief Product Officer at Dynatrace, agrees: "The challenge will be managing large-scale OpenTelemetry rollouts and monitoring their health."

Hard to Learn

"OpenTelemetry can be challenging for new developers to learn, as documentation gaps still exist due to the rapid pace of development," says Parker of Lightstep.

"Implementing OpenTelemetry across every part of the system requires deep knowledge and has a high entry point effort," adds Haberman of Aspecto. "This forces users to fully understand how OTel works and get involved in the project's updates. Though, as the project matures and the amount and quality of resources grows, adoption will get easier."

Martin Thwaites, Developer Advocate at Honeycomb, explains further: "At first glance, OpenTelemetry can be challenging to get started with, especially for certain languages that don't provide documentation for orchestration. However, even with this, early adopters were more than willing to dig deep and make it work. Therefore as focus on documentation becomes a priority, this barrier will quickly be eliminated. And, as adoption grows into the early majority and beyond, this will be more important to new users looking to come on board."

"Furthermore, looking deeper at the various language and framework SDKs are doing, it becomes harder to understand," he continues. "Providing more 'easy mode' integrations like the Agents and Kubernetes Operators will be essential to broader adoption. This will ease the issue of sampling or managing high data volume."

Developer Priorities

"It's important to consider that observability is not the fundamental goal when developing new software," explains Sajai Krishnan, General Manager, Observability, Elastic. "A software developer's primary goal may be to make the application or library they are building meet key business requirements or reduce the risk of impacting the performance of their code. Implementing observability may not be a primary goal, as developers carry on with familiar logging as has been done for decades, which could hurt the broad adoption of OpenTelemetry."

Download the 2022 Gartner Magic Quadrant for APM and Observability

Lack of Commercial Support

As with any open source solution, tech support and upgrades could be an issue for users of OpenTelemetry because it is not backed by a commercial vendor.

Vendor Enhancements

"There is also the risk that the standardization and vendor neutrality benefits of OpenTelemetry are lost by vendor enhancements beyond the standard features in their downstream distribution," says Krishnan at Elastic.

Go to: A Guide to OpenTelemetry — Part 6: OTel and APM

Pete Goldin is Editor and Publisher of APMdigest

Hot Topics

The Latest

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...

In a 2026 survey conducted by Liquibase, the research found that 96.5% of organizations reported at least one AI or LLM interaction with their production databases, often through analytics and reporting, training pipelines, internal copilots, and AI generated SQL. Only a small fraction reported no interaction at all. That means the database is no longer a downstream system that AI "might" reach later. AI is already there ...

In many organizations, IT still operates as a reactive service provider. Systems are managed through fragmented tools, teams focus heavily on operational metrics, and business leaders often see IT as a necessary cost center rather than a strategic partner. Even well-run ITIL environments can struggle to bridge the gap between operational excellence and business impact. This is where the concept of ITIL+ comes in ...

UK IT leaders are reaching a critical inflection point in how they manage observability, according to research from LogicMonitor. As infrastructure complexity grows and AI adoption accelerates, fragmented monitoring environments are driving organizations to rethink their operational strategies and consolidate tools ...

For years, many infrastructure teams treated the edge as a deployment variation. It was seen as the same cloud model, only stretched outward: more devices, more gateways, more locations and a little more latency. That assumption is proving costly. The edge is not just another place to run workloads. It is a fundamentally different operating condition ...

AI can't fix broken data. CIOs who modernize revenue data governance unlock predictable growth-those who don't risk millions in failed AI investments. For decades, CIOs kept the lights on. Revenue was someone else's problem, owned by sales, led by the CRO, measured by finance. Those days are behind us ...

Over the past few years, organizations have made enormous strides in enabling remote and hybrid work. But the foundational technologies powering today's digital workplace were never designed for the volume, velocity, and complexity that is coming next. By 2026 and beyond, three forces — 5G, the metaverse, and edge AI — will fundamentally reshape how people connect, collaborate, and access enterprise resources ... The businesses that begin preparing now will gain a competitive head start. Those that wait will find themselves trying to secure environments that have already outgrown their architecture ...

Ask where enterprise AI is making its most decisive impact, and the answer might surprise you: not marketing, not finance, not customer experience. It's IT. Across three years of industry research conducted by Digitate, one constant holds true is that IT is both the testing ground and the proving ground for enterprise AI. Last year, that position only strengthened ...

A Guide to OpenTelemetry - Part 5: The Challenges

Pete Goldin
APMdigest

While OpenTelemetry offers many advantages, the experts point out several challenges as well.

Start with: A Guide to OpenTelemetry - Part 1

Start with: A Guide to OpenTelemetry - Part 2: When Will OTel Be Ready?

Start with: A Guide to OpenTelemetry - Part 3: The Advantages

Start with: A Guide to OpenTelemetry - Part 4: The Results

The Project is Not Mature

Maybe the greatest challenge for OpenTelemetry is that the project is not mature. While the tracing component is fairly well advanced, the metrics and logging parts are still being formed.

"Currently, the project is not mature enough to support every stack, language, and signal," says Michael Haberman, CTO and Co-Founder of Aspecto. "While we believe it'll get there, the road to full stability is long."

"OpenTelemetry remains a young project in many ways, and many components are still in alpha or beta," explains Austin Parker, Head of Developer Relations at Lightstep by ServiceNow. "There is still work being done to bring in new signals such as profiling, logging, or real user monitoring (RUM), and breaking changes in those signals can be frequent."

"Logs and metrics are slowly catching up, but the API is still unstable which can be an issue," adds Vladimir Mihailenco, Co-Founder of Uptrace. "Logs and metrics are not stable yet so using them is more bumpy and requires some involvement with OpenTelemetry development and reading various changelogs."

Varying Quality

"While the existing OpenTelemetry libraries are already viable for manual and automatic instrumentation, which is a key part of any observability solution, it varies in quality," says Daniel Khan, Director of Product Management (Telemetry) at Sentry. "With new versions of libraries being released almost daily, it is up to the Open Source community to reverse engineer and adapt the instrumentation for every new version. This is not sustainable. Now is the time when library and framework maintainers have to start adding OpenTelemetry to their code. If this doesn't happen, the production use-case for OpenTelemetry will stay rather limited."

"The maturity of documentation, specification, libraries, and collector varies. One's experience might be very different depending on what they want to achieve," Marcin "Perk" Stożek, Software Engineering Manager of Open Source Collection, Sumo Logic, adds.

Bugs

"OpenTelemetry is developing at a fast rate, and the instrumentation is rapidly changing. This can lead to frustrating bugs at times. But the community is actively taking steps to address concerns around instrumentation stability," says Pranay Prateek, Co-Founder of SigNoz.

Does Not Provide Backend Storage, Analysis or Visualization

Another important challenge to be aware of: OpenTelemetry does not provide any backend storage, analysis or visualization, so to gain full value of the project you need to implement these components on your own or with the help of a service provider.

"Without the proper tools and integrations, it can be challenging to make sense of what the data OpenTelemetry uncovers, and what was meant to provide visibility into IT performance and availability could actually end up creating more data noise instead," says Joe Byrne, VP of Technology Strategy and Executive CTO at Cisco AppDynamics.

Requires Large-Scale Initiative

To truly adopt OpenTelemetry requires a large-scale effort by an organization.

"Users will have to replace some of their existing toolchains of telemetry collection (especially for logs and metrics)," Haberman of Aspecto points out. "It will require quite a lot of effort, and usually, companies are not excited to make this large-scale shift."

"Migrating from current proprietary collection technologies to OpenTelemtry is non trivial for any large customer," adds Nitin Navare, CTO of LogicMonitor.

Difficult to Manage at Scale

"As OpenTelemetry evolves, it will become more complex and challenging to configure and manage at scale," warns Jonah Kowall, CTO of Logz.io.

Alois Reitbauer, Chief Product Officer at Dynatrace, agrees: "The challenge will be managing large-scale OpenTelemetry rollouts and monitoring their health."

Hard to Learn

"OpenTelemetry can be challenging for new developers to learn, as documentation gaps still exist due to the rapid pace of development," says Parker of Lightstep.

"Implementing OpenTelemetry across every part of the system requires deep knowledge and has a high entry point effort," adds Haberman of Aspecto. "This forces users to fully understand how OTel works and get involved in the project's updates. Though, as the project matures and the amount and quality of resources grows, adoption will get easier."

Martin Thwaites, Developer Advocate at Honeycomb, explains further: "At first glance, OpenTelemetry can be challenging to get started with, especially for certain languages that don't provide documentation for orchestration. However, even with this, early adopters were more than willing to dig deep and make it work. Therefore as focus on documentation becomes a priority, this barrier will quickly be eliminated. And, as adoption grows into the early majority and beyond, this will be more important to new users looking to come on board."

"Furthermore, looking deeper at the various language and framework SDKs are doing, it becomes harder to understand," he continues. "Providing more 'easy mode' integrations like the Agents and Kubernetes Operators will be essential to broader adoption. This will ease the issue of sampling or managing high data volume."

Developer Priorities

"It's important to consider that observability is not the fundamental goal when developing new software," explains Sajai Krishnan, General Manager, Observability, Elastic. "A software developer's primary goal may be to make the application or library they are building meet key business requirements or reduce the risk of impacting the performance of their code. Implementing observability may not be a primary goal, as developers carry on with familiar logging as has been done for decades, which could hurt the broad adoption of OpenTelemetry."

Download the 2022 Gartner Magic Quadrant for APM and Observability

Lack of Commercial Support

As with any open source solution, tech support and upgrades could be an issue for users of OpenTelemetry because it is not backed by a commercial vendor.

Vendor Enhancements

"There is also the risk that the standardization and vendor neutrality benefits of OpenTelemetry are lost by vendor enhancements beyond the standard features in their downstream distribution," says Krishnan at Elastic.

Go to: A Guide to OpenTelemetry — Part 6: OTel and APM

Pete Goldin is Editor and Publisher of APMdigest

Hot Topics

The Latest

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...

In a 2026 survey conducted by Liquibase, the research found that 96.5% of organizations reported at least one AI or LLM interaction with their production databases, often through analytics and reporting, training pipelines, internal copilots, and AI generated SQL. Only a small fraction reported no interaction at all. That means the database is no longer a downstream system that AI "might" reach later. AI is already there ...

In many organizations, IT still operates as a reactive service provider. Systems are managed through fragmented tools, teams focus heavily on operational metrics, and business leaders often see IT as a necessary cost center rather than a strategic partner. Even well-run ITIL environments can struggle to bridge the gap between operational excellence and business impact. This is where the concept of ITIL+ comes in ...

UK IT leaders are reaching a critical inflection point in how they manage observability, according to research from LogicMonitor. As infrastructure complexity grows and AI adoption accelerates, fragmented monitoring environments are driving organizations to rethink their operational strategies and consolidate tools ...

For years, many infrastructure teams treated the edge as a deployment variation. It was seen as the same cloud model, only stretched outward: more devices, more gateways, more locations and a little more latency. That assumption is proving costly. The edge is not just another place to run workloads. It is a fundamentally different operating condition ...

AI can't fix broken data. CIOs who modernize revenue data governance unlock predictable growth-those who don't risk millions in failed AI investments. For decades, CIOs kept the lights on. Revenue was someone else's problem, owned by sales, led by the CRO, measured by finance. Those days are behind us ...

Over the past few years, organizations have made enormous strides in enabling remote and hybrid work. But the foundational technologies powering today's digital workplace were never designed for the volume, velocity, and complexity that is coming next. By 2026 and beyond, three forces — 5G, the metaverse, and edge AI — will fundamentally reshape how people connect, collaborate, and access enterprise resources ... The businesses that begin preparing now will gain a competitive head start. Those that wait will find themselves trying to secure environments that have already outgrown their architecture ...

Ask where enterprise AI is making its most decisive impact, and the answer might surprise you: not marketing, not finance, not customer experience. It's IT. Across three years of industry research conducted by Digitate, one constant holds true is that IT is both the testing ground and the proving ground for enterprise AI. Last year, that position only strengthened ...