rerun-io/rerun
Oct 2024 – Feb 2026
17 Months active
Languages Used
PythonRustC++MarkdownTOMLFlatBuffersGitDockerfile
Technical Skills
Asynchronous ProgrammingConcurrencyData LoadingData StructuresDataframe StreamingFFI
Clement Rey
PROFILE
Clement Rey
Over 17 months, this developer delivered core backend and data infrastructure for the rerun-io/rerun repository, building scalable APIs, robust data streaming, and efficient storage systems. Their work spanned Rust, Python, and Protocol Buffers, focusing on cross-language compatibility, performance optimization, and maintainability. They implemented features such as multi-layer RRD manifests, virtualized chunk stores, and atomic dataset registration, while modernizing gRPC and cloud APIs for reliability and developer ergonomics. Through deep refactoring, CI/CD improvements, and targeted bug fixes, they enhanced data integrity, observability, and release stability, enabling faster iteration and safer deployments across distributed systems and large-scale data workflows.
Overall Statistics
Feature vs Bugs
68%Features
Repository Contributions
266Total
Bugs
57
Commits
266
Features
123
Lines of code
161,449
Activity Months17
Your Network
76 peopleWork History
February 2026
12 Commits • 4 Features
Feb 1, 2026February 2026 monthly summary for rerun: Strengthened data integrity, expanded RRD manifest capabilities, and improved codebase hygiene. Delivered atomic dataset registration/unregistration with tests, multi-layer RRD manifest support plus rrd split tooling for efficient large-recording handling, reliability and correctness fixes in data access and schemas, WorkOS email claim support, and targeted codebase maintenance. These changes deliver safer dataset lifecycles, scalable data processing, clearer diagnostics, and lower maintenance costs, supporting reliable cloud operations and faster feature delivery.
12 Commits • 4 Features
Feb 1, 2026February 2026 monthly summary for rerun: Strengthened data integrity, expanded RRD manifest capabilities, and improved codebase hygiene. Delivered atomic dataset registration/unregistration with tests, multi-layer RRD manifest support plus rrd split tooling for efficient large-recording handling, reliability and correctness fixes in data access and schemas, WorkOS email claim support, and targeted codebase maintenance. These changes deliver safer dataset lifecycles, scalable data processing, clearer diagnostics, and lower maintenance costs, supporting reliable cloud operations and faster feature delivery.
February 2026
January 2026
21 Commits • 18 Features
Jan 1, 2026Month 2026-01 — Consolidated delivery across core storage and cloud paths with a focus on memory efficiency, reliability, and scalable data workflows. Key wins include a robust Deep Chunk Slicing path to fix on-disk and in-memory bloat when slicing data, OSS-enabled GetRrdManifest flow for Rerun Cloud, and a multi-release Virtual ChunkStore with incremental improvements (shallow GC, partial query results, manifest-driven virtual store initialization, prioritized prefetching, virtual caches for range/latest-at, and virtual events/tombstones in caches). Advanced data transport efficiency achieved via DataframePart compression (LZ4 by default) and corrected compression constants. Several reliability and maintainability enhancements were completed, including undo-redo time range removal fix, store/config/interface refinements, and ensuring store events are always available to direct callers.
January 2026
21 Commits • 18 Features
Jan 1, 2026Month 2026-01 — Consolidated delivery across core storage and cloud paths with a focus on memory efficiency, reliability, and scalable data workflows. Key wins include a robust Deep Chunk Slicing path to fix on-disk and in-memory bloat when slicing data, OSS-enabled GetRrdManifest flow for Rerun Cloud, and a multi-release Virtual ChunkStore with incremental improvements (shallow GC, partial query results, manifest-driven virtual store initialization, prioritized prefetching, virtual caches for range/latest-at, and virtual events/tombstones in caches). Advanced data transport efficiency achieved via DataframePart compression (LZ4 by default) and corrected compression constants. Several reliability and maintainability enhancements were completed, including undo-redo time range removal fix, store/config/interface refinements, and ensuring store events are always available to direct callers.
December 2025
16 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for rerun: Delivered end-to-end RRD footers infrastructure with manifest catalogs, enabling manifest-based chunk access, RPC fetch, and CLI display; added encoding/decoding glue and transport/application mappings; implemented OSS-based manifest fetch and improved data governance through tests and sanity checks. Also performed focused build/config cleanup by making Tracy instrumentation optional, reducing unnecessary dependencies and enabling more flexible deployments.
16 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for rerun: Delivered end-to-end RRD footers infrastructure with manifest catalogs, enabling manifest-based chunk access, RPC fetch, and CLI display; added encoding/decoding glue and transport/application mappings; implemented OSS-based manifest fetch and improved data governance through tests and sanity checks. Also performed focused build/config cleanup by making Tracy instrumentation optional, reducing unnecessary dependencies and enabling more flexible deployments.
December 2025
November 2025
7 Commits • 2 Features
Nov 1, 2025November 2025 (2025-11) performance-focused update highlighting stability, API extension, and developer experience improvements across the core rerun platform. Delivered concrete value for data teams: easier index management, more reliable data processing, and clearer terminal outputs, all while tightening compatibility with upstream dependencies.
November 2025
7 Commits • 2 Features
Nov 1, 2025November 2025 (2025-11) performance-focused update highlighting stability, API extension, and developer experience improvements across the core rerun platform. Delivered concrete value for data teams: easier index management, more reliable data processing, and clearer terminal outputs, all while tightening compatibility with upstream dependencies.
October 2025
22 Commits • 11 Features
Oct 1, 2025October 2025 delivered cross-cutting enhancements to telemetry, encoding, and data streaming in rerun, with a strong emphasis on reliability, consistency, and developer ergonomics. Key features include late-binding for telemetry service names, autopropagating versioning headers across components, end-to-end out-of-band entry headers for datasets, and the v2 upgrade of re_log_encoding, complemented by a unified StreamDecoder iterator used across the codebase. Major bugs fixed spanned header propagation improvements, out-of-order legacy store ID handling, data loader issues with virtual FDs, RRD/docs corruption, and metadata handling fixes, significantly reducing runtime risk and improving data integrity. These changes improve observability, data quality, and maintainability, enabling faster iterations and safer deployments.
22 Commits • 11 Features
Oct 1, 2025October 2025 delivered cross-cutting enhancements to telemetry, encoding, and data streaming in rerun, with a strong emphasis on reliability, consistency, and developer ergonomics. Key features include late-binding for telemetry service names, autopropagating versioning headers across components, end-to-end out-of-band entry headers for datasets, and the v2 upgrade of re_log_encoding, complemented by a unified StreamDecoder iterator used across the codebase. Major bugs fixed spanned header propagation improvements, out-of-order legacy store ID handling, data loader issues with virtual FDs, RRD/docs corruption, and metadata handling fixes, significantly reducing runtime risk and improving data integrity. These changes improve observability, data quality, and maintainability, enabling faster iterations and safer deployments.
October 2025
September 2025
6 Commits • 4 Features
Sep 1, 2025September 2025 highlights for rerun-io/rerun focused on backend stability, performance, and developer experience. Delivered four major areas: (1) Rerun Cloud data protocol and client integration improvements, including decoupling the legacy StoreHub client from the new Rerun Cloud client and introducing header-based routing and identifiers to improve data handling and service communication; (2) ScanPartitionTable endpoint server-side projection refactor to constrain projection to a dedicated columns parameter, disable pagination and filtering, enabling a new layer-compatible endpoint; (3) Protobuf breaking changes CI and developer guidance with actionable explanations to streamline rebasing, reducing onboarding friction; (4) Maintenance API improvements for dataset indexing by removing deprecated ReIndex RPC and adding optimize_indexes and retrain_indexes options for better index management. These changes improve data routing reliability, API predictability, developer experience, and index management at scale.
September 2025
6 Commits • 4 Features
Sep 1, 2025September 2025 highlights for rerun-io/rerun focused on backend stability, performance, and developer experience. Delivered four major areas: (1) Rerun Cloud data protocol and client integration improvements, including decoupling the legacy StoreHub client from the new Rerun Cloud client and introducing header-based routing and identifiers to improve data handling and service communication; (2) ScanPartitionTable endpoint server-side projection refactor to constrain projection to a dedicated columns parameter, disable pagination and filtering, enabling a new layer-compatible endpoint; (3) Protobuf breaking changes CI and developer guidance with actionable explanations to streamline rebasing, reducing onboarding friction; (4) Maintenance API improvements for dataset indexing by removing deprecated ReIndex RPC and adding optimize_indexes and retrain_indexes options for better index management. These changes improve data routing reliability, API predictability, developer experience, and index management at scale.
August 2025
4 Commits • 2 Features
Aug 1, 2025Month: 2025-08. This month’s work on the rerun repository focused on performance, API ergonomics, and cloud API modernization to deliver tangible business value while simplifying maintenance and future enhancements. Highlights include targeted memory optimization in streaming components, enhanced API capabilities for data registration, and a consolidated, decoupled cloud API surface that aligns with a single frontend service namespace.
4 Commits • 2 Features
Aug 1, 2025Month: 2025-08. This month’s work on the rerun repository focused on performance, API ergonomics, and cloud API modernization to deliver tangible business value while simplifying maintenance and future enhancements. Highlights include targeted memory optimization in streaming components, enhanced API capabilities for data registration, and a consolidated, decoupled cloud API surface that aligns with a single frontend service namespace.
August 2025
July 2025
21 Commits • 11 Features
Jul 1, 2025July 2025 monthly summary for the rerun repository. Delivered core enhancements, reliability fixes, and developer-focused improvements that increase throughput, safety, and clarity in the API surface. The work emphasized business value by accelerating schema discovery, improving data processing efficiency, and enabling deterministic dataset creation, while reducing API surface complexity and improving operational reliability.
July 2025
21 Commits • 11 Features
Jul 1, 2025July 2025 monthly summary for the rerun repository. Delivered core enhancements, reliability fixes, and developer-focused improvements that increase throughput, safety, and clarity in the API surface. The work emphasized business value by accelerating schema discovery, improving data processing efficiency, and enabling deterministic dataset creation, while reducing API surface complexity and improving operational reliability.
June 2025
8 Commits • 4 Features
Jun 1, 2025June 2025 performance summary for rerun-io/rerun: Delivered core feature enhancements, observability improvements in CI, data handling and loading performance boosts, and fixed a critical TLS initialization issue. These efforts increased reliability, developer productivity, and data processing speed, aligning with business goals of stability and performance.
8 Commits • 4 Features
Jun 1, 2025June 2025 performance summary for rerun-io/rerun: Delivered core feature enhancements, observability improvements in CI, data handling and loading performance boosts, and fixed a critical TLS initialization issue. These efforts increased reliability, developer productivity, and data processing speed, aligning with business goals of stability and performance.
June 2025
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 Monthly Summary — rerun-io/rerun Focus: stabilize user workflows and improve developer productivity with targeted config and resilience improvements. Key features delivered and bugs fixed in the period across the rerun repository: - Developer Experience: Enable Debug Symbols Across Workspace — enabled per-crate debugging support by setting profile.debug=true in every Cargo.toml in the workspace to speed up debugging and iteration for developers. This reduces time-to-insight when diagnosing issues across multiple crates. Commit reference: 25f0bf2a90d465e12bedf5abfd19a47df98cfa95 (#9976). - Registration Schema Validation Stabilization — temporarily disabled the response schema check in RegisterWithDataset to ensure the registration flow remains functional while investigating a server-side discrepancy. This mitigated user impact and provided time to align server expectations. Commit reference: 04f82f1818964a5fff9524212684dcffd8cf4af2 (#9893). Overall impact and accomplishments: - Maintained user registration flow reliability during server-side investigation, reducing potential user-facing failures. - Improved developer productivity and debugging efficiency across the workspace, enabling faster triage and feature iteration. - Demonstrated strong collaboration between client-side stability fixes and workspace-wide configuration changes, aligning engineering efforts with business continuity goals. Technologies and skills demonstrated: - Rust, Cargo workspaces, and per-crate configuration tuning (Cargo.toml) to enable debug symbols across the repo. - Change management and impact assessment for live user flows (register path) with risk mitigation by delaying schema enforcement while discrepancies are resolved. - Issue referencing and traceability with clear commit messages and identifiers.
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 Monthly Summary — rerun-io/rerun Focus: stabilize user workflows and improve developer productivity with targeted config and resilience improvements. Key features delivered and bugs fixed in the period across the rerun repository: - Developer Experience: Enable Debug Symbols Across Workspace — enabled per-crate debugging support by setting profile.debug=true in every Cargo.toml in the workspace to speed up debugging and iteration for developers. This reduces time-to-insight when diagnosing issues across multiple crates. Commit reference: 25f0bf2a90d465e12bedf5abfd19a47df98cfa95 (#9976). - Registration Schema Validation Stabilization — temporarily disabled the response schema check in RegisterWithDataset to ensure the registration flow remains functional while investigating a server-side discrepancy. This mitigated user impact and provided time to align server expectations. Commit reference: 04f82f1818964a5fff9524212684dcffd8cf4af2 (#9893). Overall impact and accomplishments: - Maintained user registration flow reliability during server-side investigation, reducing potential user-facing failures. - Improved developer productivity and debugging efficiency across the workspace, enabling faster triage and feature iteration. - Demonstrated strong collaboration between client-side stability fixes and workspace-wide configuration changes, aligning engineering efforts with business continuity goals. Technologies and skills demonstrated: - Rust, Cargo workspaces, and per-crate configuration tuning (Cargo.toml) to enable debug symbols across the repo. - Change management and impact assessment for live user flows (register path) with risk mitigation by delaying schema enforcement while discrepancies are resolved. - Issue referencing and traceability with clear commit messages and identifiers.
April 2025
10 Commits • 2 Features
Apr 1, 20252025-04 monthly summary for rerun backend: Delivered cohesive API surface, enhanced data retrieval, and reduced technical debt across the codebase. Key features, bugs, and maintenance work focused on standardizing the RPC/API surface, enabling richer dataset queries, and cleaning up proto/schema cruft to improve maintainability and long-term velocity.
10 Commits • 2 Features
Apr 1, 20252025-04 monthly summary for rerun backend: Delivered cohesive API surface, enhanced data retrieval, and reduced technical debt across the codebase. Key features, bugs, and maintenance work focused on standardizing the RPC/API surface, enabling richer dataset queries, and cleaning up proto/schema cruft to improve maintainability and long-term velocity.
April 2025
March 2025
11 Commits • 4 Features
Mar 1, 2025March 2025 (2025-03) monthly summary for rerun repository highlighting key feature delivery, bug fixes, and engineering impact. Focused on cross-platform reliability, API modernization, and scalable data workflows with public entry points and enhanced formatting.
March 2025
11 Commits • 4 Features
Mar 1, 2025March 2025 (2025-03) monthly summary for rerun repository highlighting key feature delivery, bug fixes, and engineering impact. Focused on cross-platform reliability, API modernization, and scalable data workflows with public entry points and enhanced formatting.
February 2025
24 Commits • 16 Features
Feb 1, 2025February 2025 (2025-02) monthly summary for the rerun project. The team focused on preparing for 0.22, stabilizing core functionality, expanding automated quality gates, and enhancing CI/data infrastructure. Key activities included documenting and prepping APIs for 0.22, addressing stability issues to improve reliability, and strengthening testing and data tooling to reduce risk and accelerate feature adoption. The resulting work improves developer productivity, release readiness, and run-time reliability while optimizing CI performance and data handling.
24 Commits • 16 Features
Feb 1, 2025February 2025 (2025-02) monthly summary for the rerun project. The team focused on preparing for 0.22, stabilizing core functionality, expanding automated quality gates, and enhancing CI/data infrastructure. Key activities included documenting and prepping APIs for 0.22, addressing stability issues to improve reliability, and strengthening testing and data tooling to reduce risk and accelerate feature adoption. The resulting work improves developer productivity, release readiness, and run-time reliability while optimizing CI performance and data handling.
February 2025
January 2025
48 Commits • 21 Features
Jan 1, 2025January 2025 (2025-01) focused on stabilizing and modernizing core data flow, expanding cross-language capabilities, and delivering high-impact features that improve reproducibility, serialization, and visualization. The team completed a sweeping upgrade of the Chunk iteration APIs, migrated visualizers, and removed the legacy API surface to simplify maintenance and future upgrades. We also expanded DNA example configurability with a blueprint option and time-range override support, and advanced archetypes with eager serialization, tag-compliant descriptor methods, and partial update tooling across languages. Targeted fixes increased reliability of visualizations and data pipelines, while improving build, configuration, and API documentation hygiene. These efforts collectively drive faster feature delivery, reduced technical debt, and stronger business value through more scalable data workflows and cross-language compatibility.
January 2025
48 Commits • 21 Features
Jan 1, 2025January 2025 (2025-01) focused on stabilizing and modernizing core data flow, expanding cross-language capabilities, and delivering high-impact features that improve reproducibility, serialization, and visualization. The team completed a sweeping upgrade of the Chunk iteration APIs, migrated visualizers, and removed the legacy API surface to simplify maintenance and future upgrades. We also expanded DNA example configurability with a blueprint option and time-range override support, and advanced archetypes with eager serialization, tag-compliant descriptor methods, and partial update tooling across languages. Targeted fixes increased reliability of visualizations and data pipelines, while improving build, configuration, and API documentation hygiene. These efforts collectively drive faster feature delivery, reduced technical debt, and stronger business value through more scalable data workflows and cross-language compatibility.
December 2024
22 Commits • 11 Features
Dec 1, 2024December 2024 monthly summary: Delivered cross-language end-to-end tagging across Rust, C++, and Python, established codegen foundations and snippet index integration, and implemented strategic namespace/module refactors to improve clarity and maintainability. Strengthened reliability and performance with targeted fixes and optimizations, and advanced upgrade-readiness through migration tooling and dependency updates. The work enhances tagging accuracy, developer productivity, and platform stability, while enabling faster iteration and safer upgrades across the core rerun product.
22 Commits • 11 Features
Dec 1, 2024December 2024 monthly summary: Delivered cross-language end-to-end tagging across Rust, C++, and Python, established codegen foundations and snippet index integration, and implemented strategic namespace/module refactors to improve clarity and maintainability. Strengthened reliability and performance with targeted fixes and optimizations, and advanced upgrade-readiness through migration tooling and dependency updates. The work enhances tagging accuracy, developer productivity, and platform stability, while enabling faster iteration and safer upgrades across the core rerun product.
December 2024
November 2024
28 Commits • 9 Features
Nov 1, 2024November 2024 monthly summary for the rerun repository focusing on delivering business value, reliability, and developer productivity. Highlights include WebSocket backend enhancements, improved geospatial rendering, a structured blueprint imports workflow, and targeted stability and safety fixes across core subsystems. These efforts reduce operational risk, improve visualization clarity for end users, and accelerate blueprints-related workflows while maintaining strong developer ergonomics.
November 2024
28 Commits • 9 Features
Nov 1, 2024November 2024 monthly summary for the rerun repository focusing on delivering business value, reliability, and developer productivity. Highlights include WebSocket backend enhancements, improved geospatial rendering, a structured blueprint imports workflow, and targeted stability and safety fixes across core subsystems. These efforts reduce operational risk, improve visualization clarity for end users, and accelerate blueprints-related workflows while maintaining strong developer ergonomics.
October 2024
4 Commits • 1 Features
Oct 1, 2024During 2024-10, three key initiatives were delivered in rerun-io/rerun that jointly improve reliability, data-loading robustness, and scalability of data processing. The Release Process Integrity effort added LengthBatch test coverage to the release checklist, reducing risk of omitting components during releases. The Data Loading Robustness work reverts .rrd file handling to open semantics and standardizes decoding paths to handle drag-and-drop consistently, ensuring predictable behavior. The Streaming Data Handling and Asynchronous Query Processing initiative refactors Python FFI to enable dataframe streaming, introduces an iterator-based RecordBatch processing path, and adds fully asynchronous QueryHandle capabilities with non-blocking methods, async helpers, and stream support, including recursive read locks for parallel contexts. Overall, these changes sharpen release fidelity, improve user-facing data loading experiences, and unlock scalable, low-latency querying for large datasets. The technical work demonstrates cross-language streaming design, asynchronous programming patterns, and test-driven release validation.
4 Commits • 1 Features
Oct 1, 2024During 2024-10, three key initiatives were delivered in rerun-io/rerun that jointly improve reliability, data-loading robustness, and scalability of data processing. The Release Process Integrity effort added LengthBatch test coverage to the release checklist, reducing risk of omitting components during releases. The Data Loading Robustness work reverts .rrd file handling to open semantics and standardizes decoding paths to handle drag-and-drop consistently, ensuring predictable behavior. The Streaming Data Handling and Asynchronous Query Processing initiative refactors Python FFI to enable dataframe streaming, introduces an iterator-based RecordBatch processing path, and adds fully asynchronous QueryHandle capabilities with non-blocking methods, async helpers, and stream support, including recursive read locks for parallel contexts. Overall, these changes sharpen release fidelity, improve user-facing data loading experiences, and unlock scalable, low-latency querying for large datasets. The technical work demonstrates cross-language streaming design, asynchronous programming patterns, and test-driven release validation.
October 2024
Activity
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Quality Metrics
Correctness92.8%
Maintainability90.2%
Architecture89.6%
Performance86.0%
AI Usage23.6%
Skills & Technologies
Programming Languages
C++DockerfileFlatBuffersGitGoImHex Pattern LanguageJavaScriptMarkdownProtoProtoBuf
Technical Skills
2D Rendering3D Rendering3D TransformationsAPI DemonstrationAPI DesignAPI DevelopmentAPI IntegrationAPI RefactoringAPI designArchetype DesignArrowArrow Data FormatArrow FormatArrow2Async Programming
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline