]> 2026-09-08T17:55:08+09:00 Lesson:loom efficient capture and querying of high frequency telemetry bbcbd611 3000 ko Single-host recent high-frequency telemetry and interactive debugging. Limits: Loom targets recent situational analysis rather than long-term storage, has finite ingest capacity, and may lose the active in-memory block (for example 64 MiB) on machine failure. Loom combines append-only hybrid logs spanning memory and persistent storage with layered sparse timestamp/chunk indexes, coordination-avoiding concurrent queries, and bounded single-thread query operators. S3ResearchAgent high Venue: SOSP. Year: 2025. High-frequency telemetry can produce millions of records per second; sampling or read-optimized indexing can drop rare events or add probe effect. Verification: full_text; confidence=high. 2026-07-16T15:05:29Z 2461238.1288079 Loom: Efficient Capture and Querying of High-Frequency Telemetry. Complete HFT capture, interactive queries, and low probe effect can coexist when the write path uses cheap append-only logging and only sparse observability-oriented indexes are maintained. Loom: Efficient Capture and Querying of High-Frequency Telemetry workloads=single-host Redis/eBPF motivating scenario and two real-world high-frequency telemetry workloads; baselines=InfluxDB, FishStore, and raw-file capture; metrics=ingest rate, data-drop rate, query latency, CPU/memory probe effect; results=Loom sustains up to 9M records/s without dropping data. InfluxDB drops 38–93% and answers queries 7–160× slower; versus FishStore, Loom improves query latency 1.5–17× while exceeding ingest performance. Its ingest and probe effect are comparable to raw-file capture. How can operators capture, correlate, and interactively query complete high-frequency telemetry without pre-aggregation? lab For high-rate observability, bound write-path index work, index immutable chunks sparsely, and let queries scan a small active/unindexed tail instead of sampling away rare events. Draft 2026-07-18T15:00:26Z 2461240.1253009 2026-07-18T15:00:27Z 2461240.1253125 loom efficient capture and querying of high frequency telemetry bbcbd611 3000 ev_e613c01030bd451c 2026-07-16T15:05:30Z 2461238.1288194 S3ResearchAgent Loom: Efficient Capture and Querying of High-Frequency Telemetry. paper Bibliographic paper record. not_recorded loom efficient capture and querying of high frequency telemetry bbcbd611# aaa3c63f5adf07b1b7abdbb6834b357e 3000 verified-content-v1-0146 2026-07-16T18:58:16Z 2461238.290463 S3ResearchAgent Franco Solleza; Shihang Li; William Sun; Richard Tang; Malte Schwarzkopf; Andrew Crotty; David Cohen; Nesime Tatbul; Stan Zdonik. Loom: Efficient Capture and Querying of High-Frequency Telemetry. SOSP, 2025. paper Verification: official DOI/SOSP metadata and first-author project summary; confidence=medium. Canonical title: Loom: Efficient Capture and Querying of High-Frequency Telemetry Question: How can operators capture, correlate, and interactively query complete high-frequency telemetry without pre-aggregation? Context: Telemetry sources emit at high rates, forcing systems to sample or aggregate away details needed for debugging. Method: Loom combines an efficient ingest path with lightweight indexes across multiple telemetry sources. Evaluation: workloads=multiple high-frequency telemetry streams; baselines=; metrics=ingest rate and query response time; results=qualitative high-rate ingest with interactive complete-data queries Interpretation: A telemetry system can preserve raw correlation value if ingestion and indexing are co-designed. Reusable lesson: Optimize the write path and defer heavyweight structure while retaining queryable cross-source keys. Applicability: Performance debugging and observability for high-frequency systems. Limits: Quantitative workloads, rates, and baselines were not recoverable from accessible primary text. not_recorded loom efficient capture and querying of high frequency telemetry bbcbd611# 0e1b5c32730d6e6095aed2255812543a 3000 canonical-paper-v2-bbcbd611 2026-07-18T05:28:03Z 2461239.7278125 S3ResearchAgent Franco Solleza; Shihang Li; William Sun; Richard Tang; Malte Schwarzkopf; Andrew Crotty; David Cohen; Nesime Tatbul; Stan Zdonik. Loom: Efficient Capture and Querying of High-Frequency Telemetry. SOSP, 2025. paper Verification: official DOI/SOSP metadata and first-author project summary; confidence=medium. Canonical title: Loom: Efficient Capture and Querying of High-Frequency Telemetry Question: How can operators capture, correlate, and interactively query complete high-frequency telemetry without pre-aggregation? Context: Telemetry sources emit at high rates, forcing systems to sample or aggregate away details needed for debugging. Method: Loom combines an efficient ingest path with lightweight indexes across multiple telemetry sources. Evaluation: workloads=multiple high-frequency telemetry streams; baselines=; metrics=ingest rate and query response time; results=qualitative high-rate ingest with interactive complete-data queries Interpretation: A telemetry system can preserve raw correlation value if ingestion and indexing are co-designed. Reusable lesson: Optimize the write path and defer heavyweight structure while retaining queryable cross-source keys. Applicability: Performance debugging and observability for high-frequency systems. Limits: Quantitative workloads, rates, and baselines were not recoverable from accessible primary text. partial_source loom efficient capture and querying of high frequency telemetry bbcbd611# 1fd6876b6c93275aaa2d6a28b38f509a 3000 2026-07-18T14:58:40Z 2461240.1240741 S3ResearchAgent verify_f2e4c18e01bd74c0d8b4 metadata_only context 보존 객체는 cookie/landing page이므로 서지 위치만 확인했고 본문 주장을 검증하지 못함. inconclusive 741f8b48c5806cd52cb37f083b06b43cf29fd2096eda5a5b2c1ce7a903f33a14 R2-RESTIC:7f893ca5afd2cfb6fe320e9b61063ccc70e75a7a96589420038c8cf338b273be; archive-manifest-sha256=e28171fb69e141ce306d92dfe4b10e6cdc6e81d4fa910c30a846204dbcf8edf8; sha256=741f8b48c5806cd52cb37f083b06b43cf29fd2096eda5a5b2c1ce7a903f33a14 보존 파일 objects/sha256/74/741f8b48c5806cd52cb37f083b06b43cf29fd2096eda5a5b2c1ce7a903f33a14 ev_e613c01030bd451c 65e78f5f309c8f67c7cb701f74c6dc2ab23855451623b3706fb8d6f0b14286b0 loom efficient capture and querying of high frequency telemetry bbcbd611# 576253f969101ab03f63875ae7b4a0b9 3000 2026-07-18T14:58:41Z 2461240.1240857 S3ResearchAgent verify_429100f9cbfff384bbe0 metadata_only context 보존 객체는 cookie/landing page이므로 서지 위치만 확인했고 본문 주장을 검증하지 못함. inconclusive 741f8b48c5806cd52cb37f083b06b43cf29fd2096eda5a5b2c1ce7a903f33a14 R2-RESTIC:7f893ca5afd2cfb6fe320e9b61063ccc70e75a7a96589420038c8cf338b273be; archive-manifest-sha256=e28171fb69e141ce306d92dfe4b10e6cdc6e81d4fa910c30a846204dbcf8edf8; sha256=741f8b48c5806cd52cb37f083b06b43cf29fd2096eda5a5b2c1ce7a903f33a14 보존 파일 objects/sha256/74/741f8b48c5806cd52cb37f083b06b43cf29fd2096eda5a5b2c1ce7a903f33a14 verified-content-v1-0146 91a9e7f0fd0d244a54172149244e874b92d1d0427bc4247f01fd004957cd0f79 loom efficient capture and querying of high frequency telemetry bbcbd611# c1b6b94d1eb0cb1dcff61c456da7b167 3000 2026-07-18T14:58:41Z 2461240.1240857 S3ResearchAgent verify_c56f7de2f9dc3b399643 metadata_only context 보존 객체는 cookie/landing page이므로 서지 위치만 확인했고 본문 주장을 검증하지 못함. inconclusive 741f8b48c5806cd52cb37f083b06b43cf29fd2096eda5a5b2c1ce7a903f33a14 R2-RESTIC:7f893ca5afd2cfb6fe320e9b61063ccc70e75a7a96589420038c8cf338b273be; archive-manifest-sha256=e28171fb69e141ce306d92dfe4b10e6cdc6e81d4fa910c30a846204dbcf8edf8; sha256=741f8b48c5806cd52cb37f083b06b43cf29fd2096eda5a5b2c1ce7a903f33a14 보존 파일 objects/sha256/74/741f8b48c5806cd52cb37f083b06b43cf29fd2096eda5a5b2c1ce7a903f33a14 canonical-paper-v2-bbcbd611 a8860a0170cc7ebb7279c7894fd6905ff1f68f4e06fb93458ecbe58f8526de98 loom efficient capture and querying of high frequency telemetry bbcbd611# 29ecafba7b3e381ec07cb9bc26a9b185 3000 2026-07-18T14:58:41Z 2461240.1240857 S3ResearchAgent verify_b076845920521fa49258 full_text attempt,context,observation,interpretation,reusable_lesson,applicability Current claims are contradicted or exceed the preserved source; revision is staged at low confidence. contradicts a2bee80f7a6f71fff15c9a8cc599da0254079541731d585e1188ecaf9dd1e8a4 R2-RESTIC:7f893ca5afd2cfb6fe320e9b61063ccc70e75a7a96589420038c8cf338b273be; archive-manifest-sha256=e28171fb69e141ce306d92dfe4b10e6cdc6e81d4fa910c30a846204dbcf8edf8; sha256=a2bee80f7a6f71fff15c9a8cc599da0254079541731d585e1188ecaf9dd1e8a4; adjudicated detailed correction DETAILED-Loom SOSP 2025 abstract, §§1-5, evaluation pre-revision source locator. canonical-paper-v2-bbcbd611 a8860a0170cc7ebb7279c7894fd6905ff1f68f4e06fb93458ecbe58f8526de98 loom efficient capture and querying of high frequency telemetry bbcbd611# ed45ce4de47582f79c57f55b87c7f63a 3000 2026-07-18T14:58:42Z 2461240.1240972 S3ResearchAgent verify_c42e85daf4dbfd1d1353 full_text observation,interpretation,reusable_lesson Post-revision corrected claims are supported at the stated source scope. supports a2bee80f7a6f71fff15c9a8cc599da0254079541731d585e1188ecaf9dd1e8a4 R2-RESTIC:7f893ca5afd2cfb6fe320e9b61063ccc70e75a7a96589420038c8cf338b273be; archive-manifest-sha256=e28171fb69e141ce306d92dfe4b10e6cdc6e81d4fa910c30a846204dbcf8edf8; sha256=a2bee80f7a6f71fff15c9a8cc599da0254079541731d585e1188ecaf9dd1e8a4; adjudicated detailed correction DETAILED-Loom SOSP 2025 abstract, §§1-5, evaluation post-revision claim locator. canonical-paper-v2-bbcbd611 a8860a0170cc7ebb7279c7894fd6905ff1f68f4e06fb93458ecbe58f8526de98 loom efficient capture and querying of high frequency telemetry bbcbd611# 39409216a2704459e24480eaf41af100