{"id":3010,"date":"2026-06-22T06:54:51","date_gmt":"2026-06-22T06:54:51","guid":{"rendered":"https:\/\/oka.how\/?p=3010"},"modified":"2026-06-22T07:06:34","modified_gmt":"2026-06-22T07:06:34","slug":"from-alert-to-action-connecting-oka-to-your-ops-toolchain-with-open-source-webhook-bridges","status":"publish","type":"post","link":"https:\/\/oka.how\/index.php\/2026\/06\/22\/from-alert-to-action-connecting-oka-to-your-ops-toolchain-with-open-source-webhook-bridges\/","title":{"rendered":"From alert to action: connecting OKA to your ops toolchain with open-source webhook bridges"},"content":{"rendered":"\r\n
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From alert to action: connecting OKA to your ops toolchain with open-source webhook bridges<\/h1>\r\n\r\n\r\n\r\n

An alert that fires but reaches no one is indistinguishable from no alert at all. A smoke detector that only blinks a red light in the server room is useless if the operations team is on a different floor, working in a different tool, at a different hour. Detection is not the end of the story, delivery is.<\/p>\r\n\r\n\r\n\r\n

OKA<\/a>, developed by UCit, is an all-in-one HPC analytics platform that ships with over 20 native dashboards covering resource utilization, user behavior, job efficiency, sustainability reporting, and cost tracking: all without requiring custom development from your team. It ingests data from your job scheduler (Slurm, PBS, LSF, \u2026) and immediately surfaces actionable insights through its built-in modules: statistical analysis, anomaly detection, forecasting, and automated reporting.<\/p>\r\n\r\n\r\n\r\n

In this series, we have been building up the layers of observability that turn raw scheduler data into operational intelligence. In a first article<\/a>, we showed how Data Enhancers<\/strong> enrich that raw data with custom columns: energy readings from EAR, carbon footprint from the electricity grid, and cost figures from your internal pricing model\u2026 In a second article<\/a>, we covered Healthcheck Rules<\/strong>: Python scripts that run on a schedule inside OKA, monitor enriched metrics for anomalies, and fire structured alerts when a threshold is exceeded.<\/p>\r\n\r\n\r\n\r\n

This article covers the third and final layer: Webhook Bridges<\/strong>. When a Healthcheck fires (a GPU partition sitting idle above its threshold, a user’s job running past its expected wall time, a burst of failed jobs…) OKA can call any HTTP endpoint you configure in its notification profile. A webhook bridge is a small, self-contained Python microservice that sits at that endpoint, translates the OKA notification into the native format of a target tool, and forwards it. Slack, email, Jira, or a full PDF report: the bridge decides what happens next.<\/p>\r\n\r\n\r\n\r\n

This article walks through four open-source examples from the oka_webhooks<\/code> repository<\/a> (coming soon!)<\/mark><\/strong>. Each addresses a concrete integration need. Whether you adopt one as-is or use it as a starting point, these examples cover some of the most common destinations we encounter at HPC operations teams.<\/p>\r\n\r\n\r\n\r\n

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COMING SOON!<\/strong><\/mark> The source code for all bridges discussed here is available in the oka_webhooks<\/code> repository<\/a>.<\/p>\r\n<\/blockquote>\r\n\r\n\r\n\r\n

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How OKA triggers a webhook<\/h2>\r\n\r\n\r\n\r\n

Before looking at the individual bridges, it helps to understand the mechanism that activates them.<\/p>\r\n\r\n\r\n\r\n

OKA’s Notification Profiles<\/strong> (configured in the admin panel under Management \u2192 Notifications<\/strong>) connect a set of healthchecks to one or more delivery channels. A single profile can combine several channel types simultaneously: email<\/strong> (delivered directly by OKA via SMTP), file<\/strong> (appended to a log file on the server), and webhook<\/strong> (an HTTP POST to any URL you configure). When a healthcheck breaches its threshold, OKA evaluates the profile and fires every channel in it, so you can send an internal email and trigger a Slack bridge at the same time with a single profile. For webhook channels, the payload is always the same minimal JSON structure:<\/p>\r\n\r\n\r\n\r\n

JSON<\/span>