With over 14,000 active employees and nearly 15,000 user accounts at any given time, Identity and Access Management was a major challenge. Add in the fact that over 200 applications are used on a daily basis, from point of sales, to financials and human resource information systems, you’ve got yourself a seemingly impossible task to manage identities securely and efficiently.
Self-healing automation is quietly transforming how engineering teams operate. Here's what it actually looks like — and why the ROI case is becoming impossible to ignore.
A few years ago, "self-healing infrastructure" was the kind of phrase that lived in conference keynotes and vendor decks. The gap between the pitch and production reality was wide enough to be a running joke in Slack channels.
That gap has closed considerably. The combination of full-stack observability, mature automation frameworks, and better runbook tooling means that a meaningful percentage of production incidents — the kind that have been waking your team for years — can now be resolved before anyone's phone buzzes.
The term gets overloaded, so let's be precise. Self-healing automation refers to systems that can detect a known failure condition and execute a predefined remediation without human intervention.
This isn't AI magic. It's the systematic conversion of your runbooks — the ones your senior engineers have mentally catalogued over years of incidents — into automated actions that execute at machine speed.
Most on-call teams could rattle off a list immediately: the disk fill that clears with a log rotation, the connection pool exhaustion that resolves with a service restart, the query that runs away every time a specific job fires.
These aren't unknown problems. They're known problems that haven't been automated yet — usually because the team is too busy responding to incidents to invest in preventing the next one. It's one of the more vicious cycles in engineering operations.
"The incidents that page you most often are usually the ones you understand best. Which means they're also the ones most ready to be automated."
A useful exercise: pull your last 90 days of incident data and tag each one as novel (required human judgment) or known (had a defined playbook). For most teams, the known category is larger than expected — and it's where self-healing automation earns its keep.
Conservative projections based on 50% MTTR reduction and a 30% reduction in page volume show material returns quickly:
The savings compound across downtime cost reduction, engineer labor recovered, and — most significantly — attrition prevented. Losing one engineer to on-call burnout costs upwards of $310,000 in fully-loaded replacement costs. Automation that keeps two engineers from burning out pays for itself before the fiscal year closes.
The teams seeing the fastest results aren't boiling the ocean. They pick a single, high-frequency incident type — the one that fires most often, has a clear remediation, and requires zero human judgment to resolve — and automate that first.
One automated incident type builds confidence. Confidence builds momentum. Within a quarter, teams that started with one automated playbook typically have a dozen. The on-call rotation starts to look different: fewer pages, shorter response windows when human judgment is needed, and engineers who show up to work on Monday without residual 3am fatigue.
That's not a moonshot. It's just what happens when the tooling finally catches up with what the problems actually require.
The first step toward a healthier on-call culture is a single conversation. Reach out to our team today and let's talk about what's possible for your organization. Contact the Arisant experts at 303-330-4065 or email us at polaris_monitoring@arisant.com
Polaris is a monitoring tool with self-healing capabilities that can augment or replace your current monitoring solution. Please reach out if you'd like additional information.
This analysis draws on industry research from Gartner, PagerDuty, and first-party incident data. Cost estimates reflect conservative projections for a mid-size technology organization operating with 10 on-call engineers.
