Configure Your Notification Preferences

Read this first. OpenFrame doesn't yet have a single "notification preferences" screen where you set severity floors and pick channels (email / Slack / webhook) in one place — a unified notification & alert center is on the roadmap. Until it ships, the controls that decide what reaches you and where live in a few different spots. This guide shows you the levers that exist today so you're not waiting on clients to call you. We'll update it to a straight click-through once the dedicated center lands.

The goal of this step is simple: make sure the right alerts reach the right people, and the noise doesn't. Here's how to get there with what's in the product now.

Before you start

You need an Admin role.
If you want alerts in Slack (recommended), have a Slack workspace where you can add an app. Full steps are in Connect Slack for Alerts and Two-Way Commands (Phase 8).

The three levers that control your notifications today

1. Slack — your primary alert channel

Right now, Slack is the cleanest way to get OpenFrame alerts in front of your team in real time. Once connected, alerts post to the channel you choose, and you can even run /openframe commands back. If you only set up one notification path during onboarding, make it this one.

Set it up via Connect Slack for Alerts and Two-Way Commands (Phase 8), then point alerts at a dedicated channel — something like #openframe-alerts — so they don't get lost in general chatter.

Tip: one channel for everything gets noisy fast. Many shops split a high-signal #alerts-critical from a catch-all #alerts-all so the stuff that matters at 2am is easy to spot.

2. AI approval prompts — Mingo and Fae asking permission

A big share of what you'll "get notified" about isn't a failure — it's your AI agents asking before they act. Anything you've set to Ask User or Ask Technician in AI Settings & Guardrails surfaces as an approval request rather than running silently.

So your guardrail settings are a notification setting: tighten them and you'll be pinged more often (more control, more interruptions); loosen them and agents handle more on their own (fewer pings, more trust). Tune this deliberately — see Configure Your Tenant Settings for the walkthrough, and Approval Workflows — When Mingo Asks Permission (Phase 6) for the day-to-day.

3. Monitoring severity — deciding what's even worth an alert

What counts as "worth telling you about" starts at the Monitoring layer. Each monitoring policy carries a severity (e.g. Low), which is your basis for deciding what should escalate versus what's just logged. Getting severity right on your policies is how you set a de facto "floor" today — only the things you care about get flagged loudly.

You'll build these out properly in Phase 4 — Monitoring & Policies. For onboarding, just know that severity is set on the policy, not in a global preferences page.

A sensible day-one setup

You don't need to perfect this now. A good starting point:

Connect Slack and route alerts to a dedicated channel.
Leave the default AI guardrails in place (destructive actions ask first), and adjust only where your comfort level differs.
Come back in Phase 4 to set severities on your monitoring policies so the important stuff stands out.

That gets you real-time alerts and AI approvals from day one, without drowning anyone.

What's missing today (and coming)

So you know where the edges are: there's currently no single screen to set per-user severity floors, toggle email digests, or wire arbitrary webhooks for notifications. Those are part of the planned notification/alert center. If a unified preferences page is important to your workflow, it's worth a vote/feature request in the OpenMSP Slack community.

Quick checklist

Connected Slack and chose a dedicated alerts channel (Phase 8)
Reviewed AI guardrails so you're pinged for the right approvals (Tenant Settings guide)
Noted that monitoring severity (Phase 4) is where you'll tune what escalates
Flagged any need for a unified preferences center to your OpenFrame contact

What's next

That wraps Phase 1. Next up is Phase 2 — Device Deployment: getting the OpenFrame agent onto your first machines so there's something to actually monitor and alert on.

Based on OpenFrame v0.9.19. This area is actively evolving — re-check the console and roadmap before treating any of it as fixed.

Frequently Asked Questions

MSP AI Agents

Can AI Agents Really Close Tickets Without a Technician?

Yes. In production MSP shops today, 10% to 25% of tickets close before a human opens them. Thread alone has processed 173 million tickets across 750-plus MSP partners at 96% triage accuracy, handing back 490,000-plus technician hours. Agents own the low-risk, high-volume work (password resets, MFA enrollment, known installs, onboarding and offboarding) and flag anything that touches production data or needs judgment for a human to take.

How Much Can AI Agents Save an MSP?

On a five-person desk, reported deployments show $78,000 to $130,000 in annual direct labor savings, roughly 30% fewer escalations, and 15% to 20% better SLA compliance. Broader MSP adoption data adds ticket handling time cut by 45% and five to 12 points of margin, all from reclaimed capacity rather than headcount cuts.

AI MSP

Where Should an MSP Start With AI?

Start with a readiness assessment, not a tool purchase. Confirm your ticket history is clean and your RMM, PSA, and monitoring systems connect. Then pick one high-volume, low-risk workflow, usually ticket triage, and pilot it on internal tickets before any client sees it.

Which Tasks Should an MSP Automate First?

Automate high-volume, low-risk tasks first. Ticket triage and alert noise reduction top the list because they run constantly and a human still resolves the underlying issue. Save security approvals, billing changes, and client-facing actions for later, always with a human in the loop.

AI Safety

Is AI Safe for MSP Client Data?

It can be, with governance. Keep a human in the loop on high-risk actions, log every automated step for audit, and choose platforms that keep your data yours with no vendor lock-in. Pilot on internal data first so you catch issues before client systems are involved.

AI for MSPs

How Do You Measure AI ROI in an MSP?

Set a baseline before rollout, then track tickets closed per technician, mean time to resolution, percentage of tickets resolved with no human touch, technician hours reclaimed, and cost per ticket. AI-driven automation commonly cuts operational cost per ticket by 25 to 40%.

About OpenFrame

What's included in OpenFrame? Does it integrate with my existing tools?

OpenFrame isn't built to plug into your stack. It replaces it. Instead of duct-taping a dozen tools together (RMM, MDM, SIEM, patching, remote access, each its own login and bill), we bundle it into one unified platform: RMM, MDM, monitoring, automation, remote access, patch management, security monitoring, and ticketing, plus built-in AI copilots. So "does it integrate with X?" usually means: you won't need X anymore.

Zabbix for MSPs

Is Zabbix Free for MSPs?

Yes. Zabbix is open source under GPLv2 with no license fee, no per-device pricing, and no paywalled features. You can monitor unlimited hosts at zero software cost. The real expense is the infrastructure to host it and the engineering time to configure and maintain it.

Log Aggregation

Is Grafana Loki Free?

Yes. Self-hosted Loki is free and open source under the AGPLv3 license, so you pay only for the infrastructure you run it on. Grafana Cloud is the paid, managed option, starting at $0.45 per GB of logs ingested with 50 GB free each month.

MSP Password Manager

What Is the Best Password Manager for MSPs?

There is no single best. For most MSPs, Bitwarden balances low cost and no lock-in, 1Password offers the most polished multi-tenant console, and Keeper adds built-in privileged access. The right pick depends on your budget, client base, and need for PAM.