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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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For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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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

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...