Introducing Nova AI Ops: The AI-Native Operating System for SRE Teams
Introducing Nova AI Ops: The AI-Native Operating System for SRE Teams
隆重推出 Nova AI Ops：专为 SRE 团队打造的 AI 原生操作系统
Hey, I’m Samson — and I built Nova AI Ops because I was tired of being paged at 3 AM. For years, I watched SRE teams (including my own) drown in the same problems: 12+ monitoring tools that don’t talk to each other, $50,000/month bills from Datadog + PagerDuty + Splunk + New Relic + OpsGenie + half a dozen more, 300+ alerts per day (most of which were noise), 47-minute MTTRs because engineers had to check 6 dashboards during every incident, and on-call burnout so bad that 40% of the team left in a year. I kept thinking: this has to be a tooling problem, not a people problem. So I built Nova AI Ops.
大家好，我是 Samson。我开发 Nova AI Ops 是因为我受够了凌晨 3 点被传呼机吵醒。多年来，我目睹了包括我自己在内的 SRE 团队深陷同样的困境：十几种互不兼容的监控工具；每月支付给 Datadog、PagerDuty、Splunk、New Relic、OpsGenie 等服务的账单高达 5 万美元；每天收到 300 多条警报，其中大部分是无效噪音；平均故障修复时间（MTTR）长达 47 分钟，因为工程师在处理每次事故时都要查看 6 个仪表盘；值班人员精疲力竭，导致一年内 40% 的团队成员离职。我一直在想：这一定是工具的问题，而不是人的问题。于是，我开发了 Nova AI Ops。
What Nova AI Ops Is
什么是 Nova AI Ops
Nova AI Ops is one AI-native platform that replaces your entire monitoring and incident response stack. One install command, zero config files, 500+ integrations. But the real difference isn’t the consolidation — it’s the AI. We built a fleet of 100 specialized AI agents that work in parallel:
- Detection agents: watch metrics, logs, traces, and events 24/7.
- Correlation agents: group related alerts (94% noise reduction in production).
- Diagnosis agents: match incoming incidents against 10,000+ historical patterns.
- Remediation agents: execute 954 pre-built runbooks with automatic rollback.
- Approval Queue: for high-risk actions that need a human in the loop.
Nova AI Ops 是一个 AI 原生平台，旨在取代你现有的整个监控和事故响应技术栈。只需一条安装命令，无需配置文件，支持 500 多种集成。但它真正的不同之处不在于整合，而在于 AI。我们构建了一支由 100 个专业 AI 智能体组成的集群，它们并行工作：
- 检测智能体： 24/7 全天候监控指标、日志、追踪和事件。
- 关联智能体： 对相关警报进行分组（生产环境噪音减少 94%）。
- 诊断智能体： 将传入的事故与 10,000 多种历史模式进行匹配。
- 修复智能体： 执行 954 个预置的运行手册（Runbooks），并支持自动回滚。
- 审批队列： 针对需要人工介入的高风险操作进行把关。
The result? 78% of incidents auto-resolve without anyone getting paged. The 22% that do reach humans arrive with root cause analysis, blast radius preview, suggested fix, and one-click approval.
结果如何？78% 的事故无需人工介入即可自动解决，无需任何人被传呼。剩下的 22% 需要人工处理的事故，在推送时会附带根本原因分析、影响范围预览、修复建议以及一键审批功能。
The Numbers That Matter
关键数据
Here’s what we see in production environments: 以下是我们在生产环境中观察到的数据：
| Metric | Before Nova | After Nova |
|---|---|---|
| Alerts per day | 300+ | ~18 |
| MTTR | 47 min | 3 min |
| Auto-resolution rate | 0% | 78% |
| Monitoring bill | $50K/mo | $29/user |
| Dashboards during incidents | 6+ | 1 |
| Tools replaced | - | 12+ |
What Makes It “AI-Native”
为什么它是“AI 原生”的？
Most “AIOps” tools bolt ML onto existing monitoring. They make alerts smarter but still wake you up. Nova was built AI-first from day one:
- Agents think, not just alert: When an incident fires, the diagnosis agent walks your dependency graph, pulls relevant logs, queries historical patterns, and produces a ranked list of likely causes — before any human opens the dashboard.
- What-If simulation: Before enabling auto-remediation on a runbook, you can replay any past incident through it to see exactly what would have happened. No surprises in production.
- Baseline learning: Nova observes your services for 14 days and learns what “normal” looks like. A traffic spike that would trigger a static threshold gets ignored if it matches Tuesday morning patterns.
- Safety rails: Every remediation runs in a sandboxed context with automatic rollback if validation fails. High-risk actions (database changes, prod deploys) always require human approval via the Approval Queue.
大多数“AIOps”工具只是在现有监控上叠加机器学习。它们让警报变得更智能，但依然会把你从睡梦中吵醒。Nova 从第一天起就是以 AI 为核心构建的：
- 智能体不仅是报警，还会思考： 当事故发生时，诊断智能体会遍历你的依赖关系图，提取相关日志，查询历史模式，并生成一份按可能性排序的潜在原因列表——这一切都在人类打开仪表盘之前完成。
- “假设”模拟： 在启用运行手册的自动修复功能之前，你可以回放任何过去的事故，查看具体会发生什么。确保生产环境万无一失。
- 基准学习： Nova 会观察你的服务 14 天，学习什么是“正常”状态。如果流量激增符合周二早晨的模式，它会忽略该警报，而不会触发静态阈值。
- 安全护栏： 每次修复都在沙盒环境中运行，如果验证失败，会自动回滚。高风险操作（如数据库变更、生产环境部署）始终需要通过审批队列进行人工确认。
Who It’s For
适用人群
Nova AI Ops is for you if:
- You’re an SRE, DevOps engineer, or platform engineer.
- You run production workloads on AWS, GCP, Azure, or Kubernetes.
- You’re tired of tool sprawl, alert fatigue, or on-call burnout.
- You want AI that actually does work, not AI that just summarizes dashboards.
如果你符合以下情况，Nova AI Ops 非常适合你：
- 你是 SRE、DevOps 工程师或平台工程师。
- 你在 AWS、GCP、Azure 或 Kubernetes 上运行生产工作负载。
- 你厌倦了工具繁杂、警报疲劳或值班带来的精疲力竭。
- 你想要的是真正能干活的 AI，而不是只会总结仪表盘数据的 AI。
What We Replace
我们取代了什么
One Nova subscription replaces:
- Datadog (metrics + APM + infra monitoring)
- PagerDuty / OpsGenie / VictorOps (on-call + alerting)
- Splunk / Elastic (log management)
- New Relic / Dynatrace (APM)
- Grafana (dashboards, but you can keep yours if you want)
- Custom runbook tools and incident management platforms
一个 Nova 订阅即可取代：
- Datadog（指标 + APM + 基础设施监控）
- PagerDuty / OpsGenie / VictorOps（值班 + 警报）
- Splunk / Elastic（日志管理）
- New Relic / Dynatrace（APM）
- Grafana（仪表盘，如果你愿意也可以保留）
- 自定义运行手册工具和事故管理平台
Everything in one dashboard, one bill, one AI platform. 所有功能集成在一个仪表盘、一份账单、一个 AI 平台中。
Pricing
定价
-
Basic: Free forever, 1 user, core monitoring.
-
Standard: $29/user/mo, up to 10 users, AI Copilot, on-call scheduling.
-
Pro: $50/user/mo, unlimited users, full AI auto-remediation, 90-day retention.
-
基础版： 永久免费，1 个用户，核心监控。
-
标准版： 每用户每月 29 美元，最多 10 个用户，包含 AI Copilot 和值班排班。
-
专业版： 每用户每月 50 美元，不限用户数，包含完整的 AI 自动修复功能，90 天数据保留。
No enterprise sales call. Self-serve upgrade. Free trial at novaaiops.com — no credit card required. 无需企业销售电话，自助升级。访问 novaaiops.com 即可免费试用，无需信用卡。
What’s Coming Next
未来规划
Over the next few weeks, I’ll be posting deep-dives on dev.to about:
- How we built the AI agent fleet architecture.
- The correlation engine that cuts alert noise by 94%.
- Runbook automation patterns that actually work in production.
- Post-mortem best practices from 200+ real incidents.
- Monitoring costs and why your bill is too high.
- On-call wellness and fair rotation design.
在接下来的几周里，我将在 dev.to 上发布深度文章，探讨：
- 我们如何构建 AI 智能体集群架构。
- 如何通过关联引擎将警报噪音降低 94%。
- 在生产环境中真正有效的运行手册自动化模式。
- 从 200 多起真实事故中总结的事后复盘最佳实践。
- 监控成本分析以及为什么你的账单总是居高不下。
- 值班人员的身心健康与公平的轮班设计。
If any of this resonates, follow along. I write honestly about what works and what doesn’t — no marketing fluff. 如果你对此有共鸣，请关注我。我会诚实地分享哪些方法有效，哪些无效——绝无营销套话。
Try It
立即试用
If you want to see it in action, novaaiops.com has a free trial with no credit card required. Install takes under a minute:
curl -fsSL https://get.novaaiops.com/install.sh | sudo bash
如果你想亲眼见证它的效果，请访问 novaaiops.com 进行免费试用，无需信用卡。安装过程不到一分钟：
curl -fsSL https://get.novaaiops.com/install.sh | sudo bash
And if you just want to talk shop about SRE, monitoring, or AI agents, drop a comment. I read every reply. Happy to answer any questions about the platform, the tech, or the decision to build it in the first place.
如果你只是想聊聊 SRE、监控或 AI 智能体，欢迎留言。我会阅读每一条回复。我很乐意回答关于该平台、技术细节或我最初决定开发它的任何问题。
— Samson Written by Dr. Samson Tanimawo, Founder & CEO, Nova AI Ops.