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À partir d’avant-hierFlux principal

Using Parseable with Datasette for OpenTelemetry traces

6 octobre 2026 à 21:07

TIL: Using Parseable with Datasette for OpenTelemetry traces

I saw Parseable in a Show HN today - it's a new observability platform with both an open source (AGPL) Rust implementation (a single ~180MB binary), an "Enterprise" version with extra features and a cloud hosted option.

Since Datasette 1.0a41 added OpenTelemetry support (thanks, Alex Garcia), I decided to fire up Codex and have it figure out how to run Parseable and feed it traces from Datasette.

Here's my (human-written) TIL showing the patterns that worked, and here's a screenshot of a Datasette trace displayed within the Parseable localhost web application:

Screenshot of a trace detail view in an observability web app, with a span waterfall overlaid on a dimmed navigation sidebar and filter column. Dimmed sidebar: breadcrumb "Community > Traces > datas" (cut off), search box "Search... ⌘K", nav items "Home", "Ingest telemetry", section "ANALYZE": "Keystone", "Dashboards", "SQL Editor", section "OBSERVE": "Logs", "Metrics", "Traces" (selected), "APM", "Agents", section "MONITOR": "Alerts", "Errors", section "DATA": "Datasets", and at the bottom "Settings", "Book a call", "Support". Dimmed filter column, cut off at the right edge: "Search fi", "Core", "Log format", "User agent", "Source IPs", "Error", "Service", "service.ins", "service.na", "datasett" (checked), "Span", "Database", "HTTP", "http.reque", "NULL" (unchecked), "GET" (checked), "http.respo", "http.route", "Server", "server.add", "Telemetry", "URL", "All fields". Trace panel header: "Trace detail > 6f819a2170bcd1e91c6ea3ae236ec60b" with a copy icon, a "Related logs" button and a close X. Summary: "Start time 6:56 PM, Oct 6, 2026 UTC", "Duration 40.9 ms", "Spans 247". A minimap with axis "0ns 10.2ms 20.5ms 30.7ms 40.9ms" shows many short span bars cascading diagonally from top left toward the lower middle, with a few longer bars. Below is a span table with a "Span name" header, a "Search spans..." box, collapse and expand buttons, and a timeline axis "0ns 10.2ms 20.5ms 30.7ms 40.9ms". Rows (name, service, duration): root span with collapse toggle "123", "GET /..." "datasette..." 40.9ms spanning the full timeline; then alternating rows where each "db.query" has a collapse toggle "1": db.query datasette-local 679µs, db.query.execute datasette-local 278µs, db.query datasette-local 341µs, db.query.execute datasette-local 55µs, db.query datasette-local 357µs, db.query.execute datasette-local 197µs, db.query datasette-local 330µs, db.query.execute datasette-local 73µs, db.query datasette-local 2.26ms, db.query.execute datasette-local 2.02ms, db.query datasette-local 232µs, db.query.execute datasette-local 64µs, db.query datasette-local 207µs, db.query.execute datasette-local 71µs, db.query datasette-local 6.11ms. The child span bars start progressively later across the early part of the timeline.

Tags: datasette, observability, alex-garcia, opentelemetry

datasette 1.0a40

17 septembre 2026 à 01:51

Release: datasette 1.0a40

Same security fix as 0.65.5, plus some neat new features and bug fixes:

  • Plugins can now launch and manage background tasks using the new datasette.add_background_task() method. Thanks, Alex Garcia.
  • I've migrated Datasette to httpx2 for features like the internal datasette.client.get() method.
  • A whole lot of bug fixes, many of them stemming from a recent effort to triage issues for a 1.0 stable release.

Tags: security, datasette

Datasette 1.0a39 and 0.65.4 security releases

11 septembre 2026 à 05:27

Datasette 1.0a39 and 0.65.4 security releases

Today we're releasing two new security patch versions of Datasette: 1.0a39 and 0.65.4 - one for the current alpha series and one for the stable 0.65.x family.

These are security fixes which you should apply if you are running a Datasette instance on the public web - in particular if that instance mixes both public and private tables.

Following issues reported by Sevban Dönmez, Alex Garcia and I ran an extensive audit of Datasette using Claude Fable 5.1, GPT-5.6, and GPT-6 Astra. We then spent almost a week collaborating on and reviewing the fixes.

They helped find some very subtle bugs. We'll be incorporating security audits by frontier models into all of our development work going forward.

Alex came up with a way of splitting the work which I found extremely productive:

Alex Garcia and I worked together running and then responding to the audit, working in a shared private repository. For most of the issues we split the work: one of us would create the automated tests highlighting the issue, then the other would implement the fix. This ensured that two separate humans had eyes on each of the issues, in addition to our coding agents running different models.

Tags: releases, security, ai, datasette, generative-ai, llms, agentic-engineering, ai-security-research

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