We’ve made dashboards we can use to observe the machine’s behavior in real time, and we created logs that we can review retroactively and trace the origin of issues, if they arise. However, both of these tools require us to be proactive in order to know whether the machine needs our attention. Eventually, we don’t want to babysit the project and wait for it to fail – instead, we want the machine itself to let us know that our attention is needed. Alerting is what happens when the machine lets you know it needs your intervention. For big companies, that’s a huge topic, that covers questions such as what infrastructure should be built to decide when to send out alerts, what is the medium through which the alerts are sent, who to alert, what conditions should trigger an alert, and more. We’ll start by talking more about how these companies approach some of these questions and then, as we’ve done so far, try to distill some of these ideas and bring them into the world of maker projects.
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