List of the Top 3 Telemetry Software for Honeycomb in 2025

Langtrace serves as a comprehensive open-source observability tool aimed at collecting and analyzing traces and metrics to improve the performance of your LLM applications. With a strong emphasis on security, it boasts a cloud platform that holds SOC 2 Type II certification, guaranteeing that your data is safeguarded effectively. This versatile tool is designed to work seamlessly with a range of widely used LLMs, frameworks, and vector databases. Moreover, Langtrace supports self-hosting options and follows the OpenTelemetry standard, enabling you to use traces across any observability platforms you choose, thus preventing vendor lock-in. Achieve thorough visibility and valuable insights into your entire ML pipeline, regardless of whether you are utilizing a RAG or a finely tuned model, as it adeptly captures traces and logs from various frameworks, vector databases, and LLM interactions. By generating annotated golden datasets through recorded LLM interactions, you can continuously test and refine your AI applications. Langtrace is also equipped with heuristic, statistical, and model-based evaluations to streamline this enhancement journey, ensuring that your systems keep pace with cutting-edge technological developments. Ultimately, the robust capabilities of Langtrace empower developers to sustain high levels of performance and dependability within their machine learning initiatives, fostering innovation and improvement in their projects.

Small Hours operates as an AI-enhanced observability platform that identifies server exceptions, assesses their significance, and routes them to the proper team or individual. By leveraging Markdown or your existing runbook, you can enhance our tool's ability to troubleshoot a variety of issues effectively. Our platform ensures seamless integration with any technology stack through support for OpenTelemetry. You can also link to your current alert systems to quickly identify pressing issues. By connecting your codebases and runbooks, you provide essential context and directives that facilitate smoother operations. Your code and data are kept secure and are never stored, giving you peace of mind. The platform adeptly categorizes problems and can even create pull requests when necessary. It is finely tuned for performance and speed, particularly in enterprise environments. With our continuous automated root cause analysis, you can effectively minimize downtime and enhance operational efficiency, guaranteeing that your systems operate seamlessly at all times. Additionally, the intuitive interface allows users to navigate and utilize the platform with ease, ensuring that teams can respond rapidly to any challenges that arise.

AppScope presents an innovative approach to black-box instrumentation, delivering thorough and uniform telemetry from any Linux executable by simply prefixing the command with "scope." Customers engaged in Application Performance Management frequently share their appreciation for the tool while expressing concerns about its limited applicability to additional applications, with typically only about 10% of their software portfolio integrated with APM, leaving the remaining 90% relying on rudimentary metrics. This naturally leads to the inquiry: what is the fate of that other 80%? Here, AppScope plays a crucial role, as it removes the necessity for language-specific instrumentation and does not depend on contributions from application developers. Functioning as a language-agnostic solution that operates entirely in userland, AppScope can be applied to any application and effortlessly scales from command-line utilities to extensive production systems. Users have the flexibility to direct AppScope data into any established monitoring tool, time-series database, or logging framework. Additionally, AppScope equips Site Reliability Engineers and Operations teams with the capability to meticulously examine live applications, providing valuable insights into their functionality and performance across diverse deployment environments, such as on-premises, in the cloud, or within containerized applications. This feature not only improves the monitoring process but also promotes a richer comprehension of application dynamics, ultimately leading to enhanced performance management and optimization strategies for organizations.