What is OpenTelemetry, and what is it not?

As engineering teams head into 2026, many are rethinking their observability strategies, and OpenTelemetry (OTel) keeps showing up. But for all the excitement around it, there's still a lot of confusion about what OTel is, and what it isn't. If you're responsible for observability (or, more specifically, mobile observability), do you need OTel? If so, why? This post aims to provide clarity without hype.

What is OpenTelemetry?

OpenTelemetry (OTel) is an open-source framework and software including SDKs, tracing instrumentation, and a universal collector for generating, collecting, and exporting telemetry from applications and services. It standardizes traces, metrics, and logs so teams don't have to rely on proprietary agents or vendor-specific data formats. In even simpler terms: OTel gives developers a consistent, vendor-neutral way to instrument their applications and associated infrastructure and understand how they behave in production. The core pieces of OpenTelemetry are:

• APIs and SDKs for instrumentation
• Auto-instrumentation for supported languages and frameworks
• Collector for receiving, processing, and exporting telemetry
• Semantic conventions that bring structure to telemetry data

Why OpenTelemetry matters

Observability tooling has historically been fragmented, challenged by different agents, formats, exporters, and vendor lock-in. OpenTelemetry solves that by offering:

• Consistent instrumentation across all services
• Freedom from proprietary telemetry pipelines
• Better portability between vendors
• A single standard teams can adopt and maintain

For many organizations, OTel represents an opportunity to simplify their observability architecture instead of adding more layers to it.

What OpenTelemetry is not

Let's clear up some common misconceptions about OTel:

1. OpenTelemetry is not an observability platform. It doesn't give you dashboards, alerts, analytics, or root-cause workflows. You still need downstream tools to visualize and analyze the data.
2. OpenTelemetry does not magically produce insight. OTel helps you generate data but it does not interpret it. You still end up with noise if you instrument everything without intent.
3. OpenTelemetry will not fix poorly designed observability strategies. If your approach today is "collect everything and hope clarity emerges," OTel won't save you from that. It standardizes the data; it doesn't make the data meaningful.
4. OpenTelemetry is not the foundation for mobile observability. OpenTelemetry includes very limited mobile SDKs, but these are not a primary focus of the OpenTelemetry community. They are usually heavily extended by those who incorporate them.
5. OpenTelemetry is not fully plug-and-play (yet). Auto-instrumentation (even with OpenTelemetry eBPF) is improving quickly, but many environments still require configuration, tuning, and ongoing maintenance.
6. OpenTelemetry is not the only path to telemetry data. It is one option, along with many others like vendor-native SDKs, mobile OS–level signals (like crash reports, ANRs, performance metrics), metrics-only systems, log-first pipelines, and embedded or on-device telemetry approaches.

How OpenTelemetry fits into modern observability strategies

At bitdrift, we talk about Observability 3.0 as the next, modern way to think about observability that widens the aperture, making the discipline:

• Developer-first,
• Contextual,
• Less noisy, and
• Boring to operate.

In this framing, OpenTelemetry can play a key role as one telemetry data source, just as it did in Observability 2.0. OTel's real value is that it removes friction and standardizes instrumentation and formats that can be correlated, so teams can focus on signal quality, developer experience, and meaningful insight rather than wrestling with observability plumbing. But it's not the end-all, be-all, especially if you're focused on observability across large-scale mobile applications.

Mobile observability presents unique challenges

Mobile engineers face a different set of constraints than backend engineers. (You can read about this in detail in this blog: Why no one talks about mobile observability.) You're dealing with:

• Long release cycles
• Data usage impacting customers' experience
• Sporadic connectivity
• Unplanned terminations
• Huge cardinality and cost
• Data collection limited by user-defined app permissions and capabilities
• UI performance that's affected by naive implementations of local storage for observability data

Most observability tools, including OpenTelemetry, weren't built to address mobile-specific challenges. This is where bitdrift fits in. bitdrift's first OpenTelemetry integration works by capturing and propagating trace context, such as trace_ids, so mobile sessions can be correlated with backend distributed traces when investigation requires it. Instead of relying on luck that a sampled request exists, teams can decide after the fact which sessions and flows should be traced and joined to backend telemetry. bitdrift is purpose-built for full-fidelity mobile observability. Instead of sampling telemetry on the device and shipping everything to the backend, bitdrift stores rich logs and events locally in an on-device ring buffer and only retrieves the data that matters, when it matters. This eliminates the blind spots that sampling creates, while avoiding the cost of ingest-everything pipelines.

bitdrift + OTel: best of both worlds

Most production issues don't stop at the mobile app. To understand root cause, teams often need to correlate a user's experience on a device with what happened in downstream services. Together, bitdrift and OpenTelemetry enable a hybrid model:

• 100% mobile observability without ingesting 100% of mobile telemetry
• No sampling blind spots on the front end
• Standards-based trace correlation to backend services using OpenTelemetry
• Dynamic instrumentation without waiting for app store releases
• Intentional data retrieval, not constant data shipping

For example, if users in a specific region report slow checkouts, teams can query every affected session in real time, selectively enable tracing for that cohort, and correlate those sessions to backend traces. All of this can be done without redeploying the app or hoping the right requests were sampled.

A different philosophy than "instrument everything"

OpenTelemetry is excellent at standardizing telemetry formats and transport. bitdrift focuses on when and why data should be collected in the first place, especially on mobile, where cost, release cycles, and device constraints matter. The result is a shift in mindset: From: "Ingest everything and hope you sampled the right data." To: "Observe everything, investigate only what matters."

In a nutshell

Here's a clear definition of OpenTelemetry: OpenTelemetry is an open-source standard with associated SDKs and software for generating and exporting telemetry data. It is a foundation that makes observability more consistent, portable, and maintainable, without being an observability solution itself. If you're evaluating OTel as part of your 2026 observability strategy, this is the right moment to zoom out and think more broadly about the outcomes you're actually trying to achieve. Look for more OpenTelemetry integrations from bitdrift in the future. And if mobile observability is important to you, we'd love to help: Get in touch with us for a bitdrift demo, or join the conversation in Slack.