The problem we keep seeing

There's always one person on the team who has quietly become "the cloud bill person." Nobody assigned them the role. They just stopped saying no. They open 3-4 dashboards every week, and hope nothing important slipped through.

The thing is, when we audit a team's setup, the same patterns show up almost every time:

• Dev and staging environments are running 168 hours a week. The team uses about 50.

• 80% of Hot-tier storage that hasn't been accessed in 2+ years.

• Hackathon clusters and debug RDS instances nobody remembered to delete.

• Production is over-provisioned for traffic that hits twice a quarter.

AWS Trusted Advisor, GCP Recommender, and Azure Advisor catch about 14% of this. They check a fixed set of rules and only inside one cloud. The other 86% sits there until someone with a free afternoon goes looking for it.

That's why we built Zopnight.

Zopnight is a multi-cloud FinOps autopilot built on top of ZopDev. It helps engineering teams find waste, schedule non-prod off, right-size production, and prep for traffic spikes all across AWS, GCP, and Azure. Discover, optimize, and govern your multi-cloud spend.

What's inside Zopnight

4 engines, one control plane:

• Recommendations: 400 audit rules with evidence-backed savings (metric, threshold, current cost, optimized cost. No black-box ML)

• Smart Scheduling: Your dev environment runs 168 hours a week. Your team uses ~50. Schedule the other 118 off.

• Auto-scaling: Sizes production for actual traffic, not peak guesses

• Event Readiness: Pre-flight planned events (Black Friday, launches, load tests) with capacity validation

Plus auto-tagging, showback, atlas view, and an MCP server that lets your AI tools query your cloud directly.

How it actually works

1. Connect a cloud account read-only (IAM role, no agents, takes about 2 minutes)

2. Zopnight discovers every resource across your AWS, GCP, and Azure accounts

3. 400 audit rules surface what's idle, oversized, or forgotten. Every finding ships with the evidence: the metric we observed, the threshold, the current cost, and the optimized cost. No black-box ML.

4. You schedule non-prod off, right-size production, or remediate from one console

5. Savings get validated against your actual cloud bill, not estimates

What this looks like in practice

A Global FMCG leader running a SAP HANA-heavy environment on AWS adopted Zopnight to govern non-production cloud spend. Within a short operating period:

• 4 AWS accounts under governance

• 500+ non-production resources actively managed

• 81 automated schedules running daily

• ~24% reduction in non-production cloud costs, measured against actual spend plus savings

Savings came entirely from scheduling. No optimization recommendations were applied, no budget controls enforced. Just turning things off when nobody was using them.

Why teams trust it

• Read-only IAM role by default. Write actions are opt-in and scoped. Cloud metadata stays in your account; we don't replicate it.

• SOC 2 Type II, ISO 27001. Available on AWS, Azure, and GCP Marketplace.

• Built by ZopDev. Team from Meesho, OYO, HashiCorp, Accenture.

Try it

Connect a cloud account, read-only, and get your first findings in under 5 minutes. Free tier supports up to 10 resources, no credit card.

🌐 zop.dev/zopnight

Curious how engineering teams here are tracking cloud waste today. Spreadsheets? Custom dashboards? Just hoping the bill stays the same? Drop your stack in the comments. 🌙