惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

人人都是产品经理
人人都是产品经理
博客园_首页
IT之家
IT之家
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Vercel News
Vercel News
美团技术团队
D
Docker
WordPress大学
WordPress大学
T
Tailwind CSS Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
The Cloudflare Blog
Y
Y Combinator Blog
F
Fortinet All Blogs
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
G
Google Developers Blog
爱范儿
爱范儿
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
月光博客
月光博客
MongoDB | Blog
MongoDB | Blog
S
SegmentFault 最新的问题
GbyAI
GbyAI
Hugging Face - Blog
Hugging Face - Blog
Microsoft Azure Blog
Microsoft Azure Blog
A
About on SuperTechFans

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
3 on-call rotation mistakes that burn out your best engin...
Sonia · 2026-04-29 · via DEV Community
Cover image for 3 on-call rotation mistakes that burn out your best engineers first

Sonia

The engineers who leave over on-call are rarely the ones who complain about it. They're the ones who quietly absorb everything, resolve incidents fast, never escalate, and one day accept an offer somewhere else. By the time you notice the pattern, you've already lost the person the rotation was grinding down.
Three mistakes that create that outcome.

  1. Measuring shifts per engineer instead of load per engineer. Equal shifts are not equal load. A week with two P1 incidents resolved in 20 minutes each is not the same as a week with twelve alerts that each require 45 minutes of investigation at 2am. If you track only who was on-call and not what that shift actually cost, you will consistently underestimate the burden on your senior engineers, who resolve things faster but get paged more often because they're trusted to handle anything. Track actionable pages per shift per engineer. If one person consistently receives 3x the load of others, the rotation is broken regardless of how the calendar looks. The fix is alert hygiene first (delete alerts nobody acts on for 30 consecutive days), then rebalance the schedule based on load data, not headcount fairness.
  2. Putting engineers on independent on-call before shadow shifts. The correct progression before anyone carries the pager alone: observer phase (receive all the same pages, take no action, watch how the primary responds), then reverse shadow (lead the response with an experienced engineer watching), then independent. Skipping this costs you higher MTTR on every incident that engineer handles alone, plus an experience that makes on-call feel dangerous rather than manageable. Four to six weeks of partial senior engineer time upfront costs significantly less than the first major incident where an unprepared engineer makes it worse.
  3. Treating on-call as part of the job with no additional recognition. An engineer paged three times outside business hours in a single week and expected to deliver full sprint capacity the following week is being asked to absorb a cost that isn't being acknowledged. This doesn't require complex compensation structures. Time in lieu for overnight pages, reduced sprint commitment after heavy on-call weeks, or explicit acknowledgment in performance reviews are all sufficient. The failure mode is pretending the cost doesn't exist. If Opsgenie is still in your stack: end-of-support is April 5, 2027. If your runbooks and escalation policies live inside it, export everything now. The format doesn't migrate cleanly into alternatives.