What is Managed AI Ops and what does Plugsky run?

Key facts

Monitoring	24/7 uptime, latency, error rate, model drift and GPU health
Scaling	Auto-scaling capacity including burst events
Patching	Critical CVEs within 24 hours, high severity within 7 days
Optimisation	Continuous eval, model-swap recommendations, right-sizing and caching
Incident response	1h P1, 4h P2, 24h P3 targets
Support	Named CSM and quarterly business reviews
Deployment	Plugsky cloud, your VPC, on-prem or air-gapped
Product status	Live

TL;DR

• Plugsky operates monitoring, scaling, patching and optimisation for you.
• Critical security patches are targeted within 24 hours.
• Incident response is tiered at 1h P1, 4h P2 and 24h P3.
• A named CSM and quarterly reviews replace the 3 a.m. pager.
• Works across cloud, VPC, on-prem and air-gapped deployments.

How it works, step by step

1. Define service levels for uptime, latency and incident response.
2. Agree which environments are in scope — cloud, VPC, on-prem or air-gapped.
3. Hand over observability access and a change-management process.
4. Set alert thresholds, escalation paths and maintenance windows.
5. Review optimisation and model-swap recommendations on a fixed cadence.
6. Use quarterly business reviews to adjust capacity and cost targets.

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What is covered

Managed AI Ops takes the operational load off your team. Monitoring covers uptime, latency, error rates, model drift and GPU health around the clock. Capacity auto-scales with traffic, including burst events that would otherwise require manual intervention. Security patching follows a defined clock: critical CVEs within 24 hours and high-severity issues within 7 days. Model optimisation runs continuous evaluation against your workloads and recommends swaps when a cheaper or better model fits.

Cost optimisation is part of the scope too: right-sizing, spot capacity where appropriate and caching all reduce the bill without changing application code.

Incident response and support

Incidents are handled against explicit targets — 1 hour for P1, 4 hours for P2 and 24 hours for P3 — with a named CSM as your entry point and quarterly business reviews to track trends. For organisations that have been running AI on a best-effort basis, this is often the first time incident handling and post-incident review become routine rather than heroic.

The service spans Plugsky cloud, your VPC, on-prem and air-gapped environments, so the operating model stays consistent even when the deployment topology changes.

Model and cost optimisation in practice

Optimisation is not only downsizing. The team evaluates your actual prompts against current models, watches for drift as upstream providers update their weights, and recommends changes when a new model offers better quality per unit of capacity. Routing and fusion strategies can shift trivial traffic to cheap models while keeping hard requests on strong ones.

• Continuous evals catch regressions before users do.
• Right-sizing removes idle GPU capacity.
• Caching cuts repeated inference for deterministic prompts.

Managed or self-operated?

Self-operation makes sense while an AI workload is small, stable and close to the team that built it. Managed AI Ops pays for itself when the workload becomes production-critical, when several teams depend on it, or when compliance teams need evidence of patch and incident management. The honest trade-off is control versus attention: you give up some hands-on autonomy in exchange for a team whose job is keeping the stack up.

Start with a clear scope — environments, service levels and escalation paths — and a defined review cadence. Managed operations fails when it is bolted on without a written operating agreement, not because the tooling is missing.

Honest comparison

Activity	Managed AI Ops	In-house ops team	No dedicated ops
Monitoring	24/7 across uptime, latency, drift and GPU	Business hours unless on-call	Reactive
Scaling	Automated including bursts	Manual or custom automation	Manual
Security patching	24h critical, 7d high targets	Depends on bandwidth	Ad hoc
Incident response	Tiered P1/P2/P3 targets	Internal on-call	Best effort
Optimisation	Continuous evals and recommendations	When time allows	None
Coverage	Cloud, VPC, on-prem, air-gapped	Your deployment	Your deployment