“We were essentially able to reduce the cost of that cluster by about 75%. On AWS, DevZero demonstrated they could achieve significantly higher savings than we initially thought possible.”
Mihir Nair
Head of Architecture, Databahn
Feature Comparison
Automatic language detection
Observability
Cast AIJVM only
Detects Java containers and injects a JMX metrics agent at pod admission. No automatic detection is documented for other runtimes.
DevZeroTen runtimes
The node agent detects JVM, Node.js, .NET, Go, Rust, GraalVM native image, Python, Ruby, Deno and Bun in every container with no workload changes. Low-privilege installs turn it off.
Application health profiling
Observability
Cast AIReliability metrics
Reliability metrics reports request rate, error rate, and latency per service, stored in an in-cluster ClickHouse database. It covers service traffic, not full application profiling.
DevZeroIncluded
Tracks OOM kills, crash loops, CPU throttling and container startup lifecycle events for each workload.
API latency, throughput and error detection
Observability
Cast AIHTTP, gRPC
A per-node collector observes HTTP/1.x, HTTP/2, and gRPC traffic without intercepting it and reports rate, errors, and duration per service.
DevZeroOpt-in
Records inbound request rate, errors and latency per container from socket probes in the network monitor. Off by default; enable it with the containerRedMetrics Helm value.
Node group profiling for shapes and sizes
Observability
Cast AINode templates
Node templates set instance family, architecture, GPU, and zone constraints for the autoscaler. The docs describe no profiling report on node group shapes.
DevZeroIncluded
Analyzes each node group and the workloads on it, then suggests node policy changes to requirements, capacity type, zones, limits and disruption settings.
Network cost
Cost attribution
Cast AIZone, no internet
Kvisor prices inter-zone and intra-zone traffic per workload and namespace. The docs state that internet traffic costs are not tracked.
DevZeroIncluded
Prices network traffic by type, including cross-AZ, cross-region, internet egress and NAT paths, estimated at cloud list rates.
Node storage cost
Cost attribution
Cast AIGKE ephemeral
Includes ephemeral storage in GKE cost totals, but detailed cost and capacity analysis is available only for persistent volumes.
DevZeroNot offered
Horizontal pod autoscaling
Workload autoscaling
Cast AIIncluded
Manages native Kubernetes HPA objects and simulates replica behavior when setting CPU targets. The older Cast AI horizontal scaler is deprecated.
DevZeroVia KEDA
Horizontal scaling runs through KEDA ScaledObjects rendered from the workload rule. KEDA is an opt-in install, off by default, and DevZero creates no native HPA.
Coexists with HPA, VPA and KEDA
Workload autoscaling
Cast AIHPA, KEDA
Works with Kubernetes HPA and KEDA ScaledObjects, adjusting its strategy by the metric types each one uses. KEDA ScaledJobs are not supported.
DevZeroDefers to them
Detects existing autoscalers automatically. An actuating VPA stands DevZero down. With an HPA it skips replica scaling, keeps vertical sizing, and offers an optional clamp against triggering scale-out.
Predictive workload scaling
Workload autoscaling
Cast AICPU, no HPA
Forecasts CPU up to 3 days ahead after 5 days of history. Memory stays reactive, and workloads with active HPA are not eligible.
DevZeroNot offered
Workload forecasts estimate cost only, and no rule scales from a forecast.
Workload profile-based autoscaling
Workload autoscaling
Cast AINot offered
Recommendations come from usage percentiles over a look-back period rather than a workload profile.
DevZeroBehavior-based sizing
The sizing engine adapts percentile targets and headroom to each workload's observed CPU and memory behavior. No rule triggers scaling from a stored profile.
OOM and CPU throttling handling
Workload autoscaling
Cast AIOOM, CPU stall
Raises memory after OOM kills, even for workloads without metrics, and raises CPU when PSI stall exceeds a configurable threshold.
DevZeroOOM by default
Raises memory right after an OOM kill, on by default, with configurable multipliers and cooldowns. A CPU throttling response exists in the operator but ships off.
Savings plan aware node choice
Cluster autoscaling
Cast AIRI, SP, CUD
The autoscaler consumes imported Reserved Instances, Savings Plans, and CUDs when it provisions matching instances, with flex sizing, and node templates can target AWS capacity reservations.
DevZeroEstimates only
Savings estimates flag the share of billed node hours under a reservation or savings plan. It does not buy commitments or steer nodes onto them.
Spot-to-spot consolidation
Cluster autoscaling
Cast AIRebalancer
Rebalancing plans replace nodes, Spot included, with the cheapest fitting set, and the ML interruption model moves at-risk Spot nodes. Both run as plans, not continuous consolidation.
DevZeroIncluded
Installs Karpenter with spot-to-spot consolidation turned on for AWS, Azure, GCP and OCI, with a per-cluster toggle in Karpenter settings.
Static capacity
Cluster autoscaling
Cast AIVia workaround
Node templates have no minimum node count setting. The docs describe a helper deployment that keeps a fixed number of nodes running per template.
DevZeroIncluded
Supports fixed-size NodePools through spec.replicas on AWS, Azure and GCP once you turn on the Static capacity setting. OCI is not supported.
Workload profile-based node scaling
Cluster autoscaling
Cast AINot offered
The autoscaler picks nodes from pod requests and node template constraints.
DevZeroSuggestions only
Node policy suggestions read workload profiles, such as spot suitability and startup time, to propose spot capacity and grace periods. You apply them; no rule scales nodes on profiles.
Alerts on restarts, OOM kills and throttling
Reliability
Cast AIOOM alerts
Sends a notification when continuous OOMKilled events hit a workload and pauses its automation. No restart or throttling alert is documented.
DevZeroIncluded
Alerts on application restarts, out-of-memory kills and CPU throttling, delivered by email or by webhook to Slack, Microsoft Teams, Discord or your own endpoint.
Last updated
Pricing Compared
Cast AI sells by quote; DevZero publishes $5 per CPU per month.
Customquote only
- Website. No rate card; pricing is by quote.
- AWS Marketplace. Free tier and monthly tiers from $200 to $5,000.
- Marketplace usage. Per-CPU charge on top of the tier.
Tier details come from the AWS Marketplace listing.
$5per CPU per month
- Free. $0 for monitoring, unlimited clusters, 30-day retention.
- Pro. $5 per CPU per month, billed monthly, 180-day retention.
- Enterprise. Custom, adds security scanning and SSO.
Pro has no annual commitment.
Start freeTeams Already Running DevZero
Published results from customers who run DevZero in production.
How To Switch From Cast AI To DevZero
Both can run in one cluster, so move one namespace at a time.
- 1Install
Install the operator in one cluster
Connect your billing export; the Free tier changes no workload.
- 2Compare
Check recommendations against Cast AI
Compare costs per namespace; note workloads using Cast AI GPU sharing.
- 3Roll out
Enable rules one namespace at a time
Start with a low-risk namespace; enable live migration only where wanted.
- 4Retire
Remove Cast AI from migrated namespaces
Disable Cast AI automation per namespace; plan Karpenter if you used its autoscaler.
DevZero vs Cast AI: FAQ
Both offer live migration and in-place resize. Cast AI adds GPU sharing and its own node autoscaler. DevZero adds node costs from your cloud bill and egress by domain.
Yes. Cast AI needs Kubernetes 1.30 or later and excludes GPU pods. DevZero's is opt-in per rule, works within one cluster, and skips sidecars.
Yes. Cast AI offers MIG, time-slicing, MPS, fractional GPUs, and DRA. DevZero recommends GPU requests but does not share GPUs.
Cast AI prices nodes from list prices plus the commitments you enter. DevZero reads your billing export, so negotiated rates are included.
DevZero Free is $0 and Pro is $5 per CPU per month. Cast AI is by quote; its AWS Marketplace tiers run $200 to $5,000 monthly.
What our Customers say
See your own numbers first
In a demo you can
Use your own data
See your cluster costs and recommendations in the dashboard.
Compare side by side
Check DevZero's results against your current tool.
Plan the switch
Move one namespace at a time, and keep the rest where it is.