Pingularity – scheduled Ookla/iperf3 speedtest dashboard, outage alerts

Hacker News

I was having intermittent issues with my ISP after switching and was looking for something that would let me easily trend downtimes, speed tests, and latency, but the existing projects out there (speedtest-tracker, myspeed, netcheck, etc.) lacked a few things I needed. I gradually put together my own, it's simple to install and supports Linux, macOS, Windows, and Docker. Interactive demo with sample data: https://demo.pingularity.dev/ Install from https://pingularity.dev then open http://localhost:9000/, local network accessible, password protectable. - Single-binary, no dependencies, self-hosted, no telemetry. - Scheduled Ookla and iperf speed tests with a wide array of settings. - Charts for visualizing download, upload, ping, jitter, and bufferbloat over time. Outage heatmap, live latency and DNS sampling. - Uptime tracking with alerts and notifications. Webhooks with native ntfy and heartbeat. - Manage retention, backups, or delete individual runs. - Prometheus/Grafana with importable dashboard and alert rules. - Customizable, change colours, disable stuff you don't want, remove chart tiles you don't care about. MIT license, https://github.com/pingular/pingularity I used Claude Code and Codex extensively throughout.

Visit product View on Hacker NewsSep 17, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, claude · Missing: agents, agent, cursor

78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · 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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr, active · Missing: mrr, revenue, profit

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: time tracking · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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