Who actually uses these products,
and what made them stay.

The Datadog SRE

A site reliability engineer or DevOps engineer responsible for the uptime and performance of production systems. They chose Datadog because it combines metrics, traces, logs, and alerts in one place — but now they're paying for all of it and the bill is terrifying. They've built dashboards that are beautiful, alerts that are precise, and runbooks that nobody reads. They are the person who gets paged at 3 AM and needs to determine in 90 seconds whether this is a real incident or a flapping alert.

“The shift was quiet.”

The PagerDuty On-Call Engineer

A software engineer or site reliability engineer who is on a rotating on-call schedule and whose relationship with PagerDuty is defined by the moments it wakes them up. They've been paged at 3am. They've resolved incidents from their phone in bed. They've also been paged for something that wasn't an incident — a flaky alert, a threshold set too low, a monitoring rule that was never updated after the system changed. Every false positive erodes their trust in the alert and their willingness to respond with full urgency next time. They manage this tension carefully.

“The shift was quiet.”

The Sentry Error Wrangler

A developer — usually mid-level to senior — who has become the de facto owner of error tracking on their team. They set up Sentry, configured the alerts, and now they're the person who triages the error feed every morning. They know the difference between a real bug and a noisy exception. They've learned to read stack traces the way a doctor reads X-rays — quickly, looking for the thing that's actually wrong. They carry the mental burden of knowing exactly how many errors are happening in production at any given moment.

“Not a single dramatic moment — more like a Tuesday at 3pm when they realized they hadn't thought about grouping algorithms that split one bug into multiple issues or merge different bugs into one in two weeks.”

The Sentry Error Monitor

A backend, frontend, or full-stack developer at a product company for whom Sentry is the first place they look when something goes wrong in production. They didn't set Sentry up — it was already there when they joined — but they've learned to read its output. They've been paged because of a Sentry alert. They've traced a production incident back to a specific line using Sentry's stack traces. They've also spent 40 minutes investigating a Sentry error that turned out to be a bot making malformed requests. They've learned to filter.

“It happened mid-workflow — it's Wednesday afternoon.”

The Datadog SRE

A site reliability engineer or platform engineer at a company with a production system that people depend on. Datadog is their window into that system. They've built dashboards that tell the story of what's happening in production. They've written monitors that page them when something goes wrong. They've been paged at 2am by monitors they wrote themselves and have opinions about that experience. They are better at Datadog than most people at their company and still feel like they're using 30% of what it can do.

“Not a single dramatic moment — more like a Tuesday at 3pm when they realized they hadn't thought about alert fatigue from monitors that fire on normal variance — the cry-wolf problem in two weeks.”

The Make Power Automator

An operations lead, automation specialist, or technical non-developer who moved to Make (formerly Integromat) after hitting the ceiling on Zapier. They know what they wanted to build and Zapier's linear trigger-action model couldn't do it: conditional branches, iterators, error handlers, multi-route flows. Make could. They learned Make. They have built things in Make that non-technical people would describe as software and technical people would describe as creative. They exist in the middle of the developer-to-non-developer spectrum and they've built a practice there.

“A client needs a system: when a new deal is created in HubSpot above a certain value, create a proje.”

The Make Integration Architect

An automation specialist, operations engineer, or technical ops manager who builds complex workflows in Make because Zapier wasn't enough. They connect 10–30 tools with branching logic, iterators, aggregators, error handlers, and data transformations. They build automations that look like flowcharts, not if-then rules. They've learned Make's visual interface deeply — routers, filters, webhooks, custom HTTP modules. They are the person who automates what everyone else does manually, and they take quiet pride in systems that run for months without intervention.

“A teammate asked how they managed build multi-step automations with branching logic that handles different cases (approval/rejection, success/failure).”