Local Dev Observability For Multiple Datasette Instances

Issue 96 Edition 2026-04-06 4 min read

General

Sources: 1 • Confidence: High • Updated: 2026-04-06 03:42

Key takeaways

After installing datasette-ports, running the command "datasette ports" produces a list of every running Datasette instance.
The author describes datasette-ports as an example of README-driven development aimed at solving a problem that may be unique to them.
The output of "datasette ports" includes each Datasette instance URL along with its Datasette version and its associated databases and plugins.
Version 0.1 of the Datasette plugin "datasette-ports" has been released.
The author frequently runs many different Datasette instances across dozens of terminal windows and sometimes loses track of them.

After installing datasette-ports, running the command "datasette ports" produces a list of every running Datasette instance.
The output of "datasette ports" includes each Datasette instance URL along with its Datasette version and its associated databases and plugins.
Version 0.1 of the Datasette plugin "datasette-ports" has been released.
The author frequently runs many different Datasette instances across dozens of terminal windows and sometimes loses track of them.

The author describes datasette-ports as an example of README-driven development aimed at solving a problem that may be unique to them.

How does datasette-ports detect and enumerate "every running Datasette instance" (process inspection, port scanning, registry, etc.)?
What operating systems and launch patterns are supported (e.g., terminal-launched processes only versus background services)?
What are the failure modes when multiple instances share similar configurations (same databases/plugins) or when instances are rapidly started/stopped?
Is there any evidence of adoption, feedback, or iteration plans beyond the initial 0.1 release?
Does the command output include any sensitive information (e.g., local URLs with tokens) and are there safeguards around what is displayed?

Growing developer need for local observability and instance management as Datasette usage expands across many concurrent workflows, implying demand for lightweight tooling around multi-instance coordination.
Ecosystem momentum for Datasette plugins that surface runtime metadata such as versions, databases, plugins, suggesting a broader trend toward operational tooling beyond core features.

Evidence of adoption beyond the author such as stars, issues, PRs, or community mentions indicating the pain point is shared and the tool is being used.
Rapid iteration after 0.1 with releases addressing unknowns like detection method, OS support, and safety of displayed data, signaling an active maintenance trajectory.
Integration requests or links from Datasette docs or plugin registries that position the command as a common workflow tool for developers running multiple instances.

Tool remains a one-off with no feedback or updates after 0.1, reinforcing that the problem is niche and limiting broader ecosystem impact.
Detection is fragile or OS-specific, causing frequent failures when instances start and stop, undermining reliability as an observability aid.
Command output exposes sensitive local URLs or tokens without safeguards, discouraging usage and limiting distribution in teams or shared environments.