Zesty vs ZopNight: Autoscaling Commitments and Storage, Compared

What Zesty does

An earlier version of this page called Zesty a purchasing tool that does nothing about utilization. Its current product pages say otherwise. The homepage (zesty.co) leads with AWS and Azure commitment optimization. The platform also covers:

• Multi-dimensional autoscaling, which will “continuously rightsize CPU, memory, and replica counts” for Kubernetes workloads (product page).
• PV autoscaling, which will “automatically scale persistent volumes up or down” (PV autoscaling).
• FastScaler, which keeps “a pool of hibernated nodes” ready for traffic spikes (FastScaler). This is a scale-up aid, not off-hours scheduling.
• Adaptive pod placement for node consolidation (pod placement).

The docs index (docs.zesty.co) covers installing Kompass on EKS and the Insights agent on AKS. The supported-services page says Commitment Manager covers EC2, plus EKS and ECS running on EC2, and that Zesty Disk covers EBS and Azure Managed Disks (supported services, dated July 2024). Pricing is “based on actual usage and realized savings” (zesty.co/pricing). We found no off-hours environment scheduling on the pages we read, so we make no claim either way.

Continuous right-fit versus deliberate off-hours

Zesty’s automation is reactive to load. Commitments rebalance, pods resize, volumes grow and shrink, and pre-warmed nodes absorb spikes, all with little human input. That fits production systems whose demand moves around.

ZopNight’s scheduling is deliberate. A team decides staging runs 8 AM to 7 PM on weekdays in its own timezone, attaches the schedule to a group, and ZopNight enforces it. That covers cluster nodes, VMs, RDS, Cloud SQL, Azure flexible servers and Kubernetes namespaces. It works the same way on GCP. Around the schedule, recommendations cover idle and orphaned resources, rightsizing and discounts, and each can be remediated with an approval gate for destructive steps.

Choose Zesty if…

• Your spend is mostly steady production load on AWS or Azure, and you want commitments, pods and disks to follow demand automatically.
• Disk over-provisioning is a real line item, and you want volumes that shrink as well as grow.
• You prefer pricing that tracks realized savings.

Choose ZopNight if…

• A large share of spend is environments that do not need to run nights and weekends, and you want them off on a timetable with overrides that expire.
• You run on GCP, or on all three clouds, and want one set of schedules and recommendations across them.
• You want cost reporting too: billed cost from each cloud’s billing export, showback by team and tag, budgets, and anomaly root-cause analysis. See Compute Engine scheduling for a GCP example.