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Developers Can Leverage OpenTelemetry to Achieve Fuller Visibility

Michael Olechna
Guardsquare

Observability is currently a hot topic. Businesses and consumers are increasingly relying on digital apps for everyday functions, which means every company needs a high performing app or website. When you take a minute to evaluate why, the numbers quickly make sense. In 2025, the number of mobile users worldwide is projected to reach 7.49 billion. And as digital adoption continues to grow, so does users' quality expectations. Each one of those users, including developers, is expecting a frictionless, high-quality experience. As end-user experiences become more connected with an organization's bottom line, a solution to catch performance hiccups becomes necessary. Hence the adoption of front-end observability through initiatives like digital experience monitoring. And who better to execute this initiative than the developers writing the code. But there's a problem with traditional observability tools tailored for DevOps, SRE, and IT teams. Developers need a tool that can be portable and vendor agnostic, given the advent of microservices. It may be clear an issue is occurring; what may not be clear is if it's part of a distributed system or the app itself. Enter OpenTelemetry, commonly referred to as OTel, an open-source framework that provides a standardized way of collecting and exporting telemetry data (logs, metrics, and traces) from cloud-native software. Prior to the onset of OpenTelemetry, there was a lack of standardization when collecting and instrumenting telemetry data. When it came to code instrumentation, there was significant variation. Due to this variation, the result was a lack of data portability and a burden on the developer to maintain large, complex instrumentation libraries. This doesn't just add significant time and effort on the developer's part. This directly impacts visibility into app performance, potentially leading to a negative end user experience. It also creates vendor lock-in and inefficiencies that can be costly for an organization, further affecting business revenue. As the market shifts toward developer-first observability, the need for a solution like OTel becomes readily apparent — explaining its rapid rise in popularity since its launch in 2019. OTel gave developers a way to ingest, view, and export telemetry data. The best part (or one of many)? It's vendor agnostic. This unified method of collecting data makes it easier for modern development teams to get a clearer, more complete picture of their apps' health and performance. The platform also provides a rich set of APIs and SDKs that are also vendor agnostic. With full control of their data, development teams can quickly instrument cloud-native apps and get started with ease. When drilling down into specific benefits, perhaps the most important feature is OTel's versatility. In addition to being vendor agnostic, the platform supports a wide range of vendors, both commercial and open source. This is key to developers being able to leverage their telemetry data long-term because they have the ability to take it with them. Should they choose to change vendors, it's as easy as exporting their OTel data to their new vendor. This eliminates the manual and time intensive process of data re-instrumentation. When discussing use cases for these benefits, three specific examples immediately come to light. The first is faster identification of performance bottlenecks. By examining telemetry data in OTel, teams can determine performance bottlenecks by tracking the time it takes to execute individual operations. Leveraging this information provides critical context to help solve application performance issues and optimize app performance. The second use case is troubleshooting problems. OTel provides a single source of truth for all telemetry data in a distributed system. Thus, development teams can track the flow of execution through their systems by examining OTel data. Developers can track down the root cause of the issue for faster resolution and ensure they are treating the cause, not a symptom. The third use case, data control, relates to one of the key benefits — OTel's versatility. OpenTelemetry is designed to work and integrate with various observability tools and platforms. This includes backends and popular tracing systems like Jaeger, as well as other metrics and logging solutions. Again, this puts data control back in the hands of developers. They can select the tools they are comfortable with or continue using what's already in their workflow, while maintaining a clear view of their app's telemetry data. By adopting OpenTelemetry, developers gain fully contextualized visibility into their distributed applications. In turn, they're able to identify performance bottlenecks faster, get down to the root cause to debug issues, optimize their resource utilization, and improve the overall reliability and user experience of their software systems.

Michael Olechna is Product Marketing Manager at Guardsquare

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Developers Can Leverage OpenTelemetry to Achieve Fuller Visibility

Michael Olechna
Guardsquare

Observability is currently a hot topic. Businesses and consumers are increasingly relying on digital apps for everyday functions, which means every company needs a high performing app or website. When you take a minute to evaluate why, the numbers quickly make sense. In 2025, the number of mobile users worldwide is projected to reach 7.49 billion. And as digital adoption continues to grow, so does users' quality expectations. Each one of those users, including developers, is expecting a frictionless, high-quality experience. As end-user experiences become more connected with an organization's bottom line, a solution to catch performance hiccups becomes necessary. Hence the adoption of front-end observability through initiatives like digital experience monitoring. And who better to execute this initiative than the developers writing the code. But there's a problem with traditional observability tools tailored for DevOps, SRE, and IT teams. Developers need a tool that can be portable and vendor agnostic, given the advent of microservices. It may be clear an issue is occurring; what may not be clear is if it's part of a distributed system or the app itself. Enter OpenTelemetry, commonly referred to as OTel, an open-source framework that provides a standardized way of collecting and exporting telemetry data (logs, metrics, and traces) from cloud-native software. Prior to the onset of OpenTelemetry, there was a lack of standardization when collecting and instrumenting telemetry data. When it came to code instrumentation, there was significant variation. Due to this variation, the result was a lack of data portability and a burden on the developer to maintain large, complex instrumentation libraries. This doesn't just add significant time and effort on the developer's part. This directly impacts visibility into app performance, potentially leading to a negative end user experience. It also creates vendor lock-in and inefficiencies that can be costly for an organization, further affecting business revenue. As the market shifts toward developer-first observability, the need for a solution like OTel becomes readily apparent — explaining its rapid rise in popularity since its launch in 2019. OTel gave developers a way to ingest, view, and export telemetry data. The best part (or one of many)? It's vendor agnostic. This unified method of collecting data makes it easier for modern development teams to get a clearer, more complete picture of their apps' health and performance. The platform also provides a rich set of APIs and SDKs that are also vendor agnostic. With full control of their data, development teams can quickly instrument cloud-native apps and get started with ease. When drilling down into specific benefits, perhaps the most important feature is OTel's versatility. In addition to being vendor agnostic, the platform supports a wide range of vendors, both commercial and open source. This is key to developers being able to leverage their telemetry data long-term because they have the ability to take it with them. Should they choose to change vendors, it's as easy as exporting their OTel data to their new vendor. This eliminates the manual and time intensive process of data re-instrumentation. When discussing use cases for these benefits, three specific examples immediately come to light. The first is faster identification of performance bottlenecks. By examining telemetry data in OTel, teams can determine performance bottlenecks by tracking the time it takes to execute individual operations. Leveraging this information provides critical context to help solve application performance issues and optimize app performance. The second use case is troubleshooting problems. OTel provides a single source of truth for all telemetry data in a distributed system. Thus, development teams can track the flow of execution through their systems by examining OTel data. Developers can track down the root cause of the issue for faster resolution and ensure they are treating the cause, not a symptom. The third use case, data control, relates to one of the key benefits — OTel's versatility. OpenTelemetry is designed to work and integrate with various observability tools and platforms. This includes backends and popular tracing systems like Jaeger, as well as other metrics and logging solutions. Again, this puts data control back in the hands of developers. They can select the tools they are comfortable with or continue using what's already in their workflow, while maintaining a clear view of their app's telemetry data. By adopting OpenTelemetry, developers gain fully contextualized visibility into their distributed applications. In turn, they're able to identify performance bottlenecks faster, get down to the root cause to debug issues, optimize their resource utilization, and improve the overall reliability and user experience of their software systems.

Michael Olechna is Product Marketing Manager at Guardsquare

Hot Topics

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 ...