Where the savings hide

Stop over-paying for Kubernetes. Lizrd finds over-provisioned EKS node groups and hands your team the exact instance-type change to make.

“Our node groups were sized for a launch spike we never hit again. Lizrd handed us the exact instance change per group — we shipped it in an afternoon and nothing paged.” — Platform engineer, B2B SaaS

Find compute that's running far below what it's paying for, and get the exact instance or task-size change to make — safely.

“It found a dozen instances running at 8% CPU that everyone was scared to touch. The diff and the one-click rollback made it a no-brainer.” — Staff engineer, fintech

Idle RDS and cache instances quietly bill around the clock. Lizrd spots them and tells you what's safe to stop or schedule.

“Two 'temporary' RDS instances had been idling for months. Lizrd flagged them with the usage history, so stopping them wasn't a debate.” — DevOps lead, marketplace

Find managed inference endpoints running 24/7 with little or no traffic, and get the exact fix — delete or scale to zero — without losing the model.

“We had three SageMaker endpoints from experiments that nobody had torn down. They were quietly burning GPU hours every hour of every day.” — ML platform lead, SaaS

Unattached volumes, unused IPs, and stale snapshots keep billing with nothing using them. Lizrd finds them and confirms they're safe to remove.

“Years of unattached volumes and stale snapshots. Lizrd proved each one was safe to delete, so cleanup took an hour, not a quarter.” — SRE, healthtech

Find training and inference boxes running on far more GPU than they use, and get the exact smaller instance or accelerator to switch to — safely.

“A four-GPU training box was sitting at 14% utilization for weeks. Lizrd showed the evidence and the one-line diff to drop it to a single GPU.” — Staff ML engineer, fintech

Move steady, Arm-compatible workloads to Graviton for ~20–40% better price-performance — with the exact resources to switch and how to verify.

“We knew Graviton was cheaper but never had time to figure out what was safe to move. Lizrd handed us the list, ranked, with the Terraform change for each one.” — Infrastructure lead, developer tools

Find interruptible GPU workloads paying the full on-demand rate, and get the exact change to run them on managed Spot capacity — with automatic resume.

“Our nightly fine-tuning already checkpointed — it just never occurred to anyone it could run on Spot for a fraction of the price.” — Engineering lead, AI startup

Move rarely-touched data to cheaper tiers, upgrade EBS and RDS volumes from gp2 to gp3 in place, and clear stale snapshots — with the exact targets.

“The gp2-to-gp3 upgrades alone paid for the quarter. Same performance, applied in place, no downtime — Lizrd just listed every volume that qualified.” — Cloud engineer, media

Idle NAT gateways, unattached elastic IPs, and load balancers with no traffic bill around the clock. Lizrd finds them and confirms what's safe to remove.

“A NAT gateway left over from a decommissioned VPC had been billing for a year. It's the kind of thing you only find when something actually looks for it.” — Platform engineer, logistics

Warehouses are among the biggest, least-watched cloud lines. Lizrd finds over-provisioned Redshift clusters and BigQuery reservations — and the fix.

“Our warehouse was the single biggest line on the bill and nobody owned it. Lizrd showed the utilization and a defensible smaller configuration — finally a place to start.” — Data platform lead, analytics

Savings Plans and committed-use discounts are free money on steady baselines — if you size them right. Lizrd finds your safe, always-on floor to commit against.

“We under-committed for years because nobody could confidently say what our steady baseline was. Lizrd drew the line, so we committed to it without holding our breath.” — FinOps lead, SaaS

Serverless still over-bills — provisioned DynamoDB that should be on-demand, idle provisioned concurrency. Lizrd spots the mismatch and the switch to make.

“A DynamoDB table on provisioned capacity for a spiky workload was quietly wasteful. One switch to on-demand and the bill matched reality.” — Backend engineer, consumer app