OpenTelemetry Protocol with Apache Arrow

The OpenTelemetry with Apache Arrow project is an effort within OpenTelemetry to use Apache Arrow libraries for bulk data transport in OpenTelemetry pipelines. This repository is the home of the OpenTelemetry Protocol with Apache Arrow protocol, which we refer to as "OTAP", and reference implementations in Golang and Rust.

The OpenTelemetry Arrow project has an OpenTelemetry SIG with weekly meetings. Find our meeting schedule on the OpenTelemetry calendar.

Quick start

OTel-Arrow components are included in the OpenTelemetry Collector-Contrib repository. See the Exporter and Receiver documentation for details.

The examples in this repository use a test collector named otelarrowcol, see collector/BUILDING.md.

Phase 2 of the project is being actively developed. We are building an end-to-end OpenTelemetry Arrow pipeline in Rust. Find us in the CNCF Slack #otel-arrow channel.

Overview

OpenTelemetry and Apache Arrow have similar charters, so it was natural to think about combining them. Both projects offer vendor-neutral interfaces with a cross-language interface specification, so that their implementation will feel familiar to users as they move between programming languages, and both specify a data model that is used throughout the project.

The OpenTelemetry project defines OTLP, the "OpenTeLemetry Prototcol" as the standard form of telemetry data in OpenTelemetry, being as similar as possible to the data model underlying the project. OTLP is defined in terms of Google protocol buffer definitions.

OTLP is a stateless protocol, where export requests map directly into the data model, nothing is omitted, and little is shared. OTLP export requests do not contain external or internal references, making the data relatively simple and easy to interpret. Because of this design, users of OTLP will typically configure network compression. In environments where telemetry data will be shipped to a service provider across a wide-area network, users would like more compression than can be achieved using a row-based data model and a stateless protocol.

Project phases

Phase 1

Phase 1 of the project is complete. Our initial aim was to facilitate traffic reduction between a pair of OpenTelemetry Collectors, as illustrated in the following diagram.

The OpenTelemetry Collector-Contrib distribution includes the OTel-Arrow Receiver and Exporter. The following diagram is an overview of this integration, which supports seamless fallback from OTAP to OTLP. In this first phase, the internal representation of the telemetry data is still fundamentally row-oriented.

Phase 2

We are building an end-to-end OpenTelemetry Protocol with Apache Arrow (OTAP) pipeline and we believe this form of pipeline will have substantially lower overhead than a row-oriented architecture. See our Phase 2 design document.

These are our future milestones for OpenTelemetry and Apache Arrow integration:

Extend OpenTelemetry client SDKs to natively support the OpenTelemetry Protocol with Apache Arrow Protocol
Extend the OpenTelemetry collector with direct support for OpenTelemetry Protocol with Apache Arrow pipelines
Extend OpenTelemetry data model with native support for multi-variate metrics.
Output OpenTelemetry data to the Parquet file format, part of the Apache Arrow ecosystem

Improve network-level compression with OpenTelemetry Protocol with Apache Arrow

The first general-purpose application for the project is traffic reduction. At a high-level, this protocol performs the following steps to compactly encode and transmit telemetry using Apache Arrow.

Separate the OpenTelemetry Resource and Scope elements from the hierarchy, then encode and transmit each distinct entity once per stream lifetime.
Calculate distinct attribute sets used by Resources, Scopes, Metrics, Logs, Spans, Span Events, and Span Links, then encode and transmit each distinct entity once per stream lifetime.
Use Apache Arrow's built-in support for encoding dictionaries and leverage other purpose-built low-level facilities, such as delta-dictionaries and sorting, to encode structures compactly.

Here is a diagram showing how the protocol transforms OTLP Log Records into column-oriented data, which also makes the data more compressible.

Project status

The Phase-1 project deliverables, located in the Collector-Contrib repository, are in the Beta stability level, as defined by the OpenTelemetry collector guidelines. We do not plan to make breaking changes in this protocol without first engineering an approach that ensures forwards and backwards-compatibility for existing and new users. We believe it is safe to begin using these components for production data, non-critical workloads.

Phase-1 project deliverables

We are pleased to release two new collector components, presently housed in OpenTelemetry Collector-Contrib:

The OpenTelemetry Protocol with Apache Arrow exporter and receiver components are drop-in compatible with the core collector's OTLP exporter and receiver components. Users with an established OTLP collection pipeline between two OpenTelemetry Collectors can re-build their collectors with otelarrow components, then simply replace the component name otlp with otelarrow. The exporter and receiver both support falling back to standard OTLP in case either side does not recognize the protocol, so the upgrade should be painless. The OpenTelemetry Protocol with Apache Arrow receiver serves both OpenTelemetry Protocol with Apache Arrow and OTLP on the standard port for OTLP gRPC (4317).

See the Exporter and Receiver documentation for details and sample configurations.

Project documentation

This package is a reference implementation of the OpenTelemetry Protocol with Apache Arrow protocol specified in this OTEP, which is currently the best source of information about OpenTelemetry Protocol with Apache Arrow. The Donation request describes how the project began.

Here are several more resources that are available to learn more about OpenTelemetry Protocol with Apache Arrow.

Arrow Data Model - Mapping OTLP entities to Arrow Schemas.
Benchmark results - Based on synthetic and production data.
Validation process - Encoding/Decoding validation process.
Articles describing some of the Arrow techniques used behind the scenes to optimize compression ratio and memory usage:
- Data types, encoding, hierarchical data, denormalization
- Adaptive Schemas and Sorting to Optimize Arrow Usage

Benchmark summary

The following chart shows the compressed message size (in bytes) as a function of the batch size for metrics (univariate), logs, and traces. The bottom of the chart shows the reduction factor for both the standard OTLP protocol (with ZSTD compression) and the OpenTelemetry Protocol with Apache Arrow protocol (ZSTD) in comparison with an uncompressed OTLP protocol.

The next chart follows the same logic but shows the results for multivariate metrics (see left column).

The following heatmap represents, for different combinations of batch sizes and connection durations (expressed as the number of batches per stream), the additional percentage of compression gain between this new protocol and OTLP, both compressed with ZSTD. The data used here comes from a traffic of spans captured in a production environment. The gains are substantial in most cases. It is even interesting to note that these gains compared to OTLP+ZSTD are more significant for moderate-sized batches (e.g., 100 and 1000 spans per batch), which makes this protocol also interesting for scenarios where the additional latency introduced by batching must be minimized. There is hardly any scenario where micro-batches (e.g., 10 spans per batch) make the overhead of the Arrow schema prohibitive, and the advantage of a columnar representation becomes negligible. In other cases, this initial overhead is very quickly offset after just the first few batches. The columnar organization also lends itself better to compression. For very large batch sizes, ZSTD does an excellent job as long as the compression window is sufficiently large, but even in this case, the new protocol remains superior. As previously mentioned, these compression gains can be higher for traffic predominantly containing multivariate metrics.

For more details, see the following benchmark results page.

Contributing

For information about contributing to the project see: CONTRIBUTING.md.

We meet every other Thursday at 8AM PT. The meeting is subject to change depending on contributors' availability. Check the OpenTelemetry community calendar for specific dates and for Zoom meeting links.

Meeting notes are available as a public Google doc. If you have trouble accessing the doc, please get in touch on Slack.

The meeting is open for all to join. We invite everyone to join our meeting, regardless of your experience level. Whether you're a seasoned OpenTelemetry developer, just starting your journey, or simply curious about the work we do, you're more than welcome to participate!

References

License

Maxito7/otel-arrow

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