A bot that manages PagerDuty on-call schedules directly from internal chat channels like Slack and IRC.
PagerBot is a chat bot that integrates with PagerDuty to manage on-call schedules and incidents directly from internal chat channels like Slack and IRC. It allows teams to query who is on call, create schedule overrides, trigger incidents, and switch shifts using natural language commands without leaving their chat environment.
DevOps teams, SREs, and engineering organizations using PagerDuty for on-call management who want to streamline operations within their existing chat workflows.
It reduces context switching by bringing on-call management into chat, supports natural language for ease of use, and is self-hostable with simple deployment options like Heroku and Docker.
Manage Pagerduty on-call schedules from within your internal chat channels.
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Uses the Chronic library to parse human-like date and time expressions, enabling intuitive commands like 'put me on triage for 30 minutes' for schedule overrides without memorizing syntax.
Supports both Slack and IRC, allowing teams to manage on-call schedules directly in their existing chat environments, as highlighted in the README's platform support.
Offers one-click Heroku deployment and Docker-based local development, with the admin interface configurable in under 8 minutes, reducing initial setup time.
Includes a web-based admin panel for managing API keys and enabling commands, providing a centralized way to customize the bot without code changes.
Only integrates with Slack and IRC, with no mention of support for other popular platforms like Microsoft Teams, potentially excluding modern team setups.
Relaunching the admin interface requires manual steps like rescaling Heroku dynos or changing config variables, as noted in the FAQ, adding operational overhead.
Heavily relies on Heroku for easy deployment, which may not suit teams using other cloud providers or requiring on-premises hosting, limiting flexibility.
Depends on the Chronic library for date parsing, which can be error-prone with ambiguous inputs, risking incorrect schedule overrides in critical on-call scenarios.