Telescope web-based log viewer update

Hacker News

Hey HN, A while back I shared Telescope - a lightweight web UI for exploring logs stored in ClickHouse using a custom query language (FlyQL). Since then, it's come a long way. Recent releases (including the latest v0.0.19) added: - Docker sources: browse logs from your running containers — straight from the Docker API - Saved views: preserve filters, layout, and other UI settings across sessions - Raw SQL mode: write plain WHERE clauses directly (access to raw mode is permission-controlled) - ClickHouse JSON support: including quoted paths and nested field access - FlyQL is now easier to read and write: supports spaces and quoted JSON paths - And a bunch of small improvements and bugfixes… that I hope you won’t notice :) It's self-hosted and open-source (MIT). Always happy for feedback, feature requests, or a GitHub star! GitHub: https://github.com/iamtelescope/telescope/ Documentation: https://docs.iamtelescope.net/ Demo: https://demo.iamtelescope.net/ Previous post: https://news.ycombinator.com/item?id=43181862

Visit product View on Hacker NewsJun 26, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: dock, new, using · Missing: mac, agents, macos

82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: clickhouse, io, including · Missing: https docs, excited, just released

77%77% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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Indie HackersIH features products with proven revenue · Strong signals: supports, including · Missing: reddit linkedin, podcasting, created

49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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