“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
Automatic language detection
Observability
Recommendations come from CPU and memory percentiles, not from the runtime or language inside the container.
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.
Network tracing (eBPF)
Observability
Investigation agents read metrics, logs and traces from connected observability tools instead of capturing network traffic.
Collects pod-to-pod network flows with netfilter by default. An eBPF collector mode is available as an opt-in setting.
Node group profiling for shapes and sizes
Observability
Allocation groups cost by cluster, namespace or service, with unallocated node capacity shown, but not by node group.
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
Kubernetes Cost splits node cost across CPU and memory only. The separate AWS Cost Analyzer agent reports cross-AZ network cost per account, not per workload.
Prices network traffic by type, including cross-AZ, cross-region, internet egress and NAT paths, estimated at cloud list rates.
Workload storage cost
Cost attribution
Not in the public docs for Kubernetes Cost. Persistent volume cost is not attributed to workloads; S3 storage is handled in the separate Cloud Cost module.
Calculates persistent volume claim storage cost for each workload.
Flexible instance shapes in node groups
Cluster autoscaling
Komodor does not provision nodes or choose instance types; it leaves node scaling to your autoscaler.
Node policies select instances by category, family, size and capacity type, so one policy spans many shapes.
Spot-to-spot consolidation
Cluster autoscaling
Spot price history is read for cost attribution only, with no spot instance replacement.
Installs Karpenter with spot-to-spot consolidation turned on for AWS, Azure, GCP and OCI, with a per-cluster toggle in Karpenter settings.
Manage existing Karpenter
Cluster autoscaling
Not in the public docs as a managed integration. Pod placement respects the karpenter.sh/do-not-evict annotation when grouping pods.
Mirrors existing Karpenter NodePools as read-only cluster-managed policies, and a migration wizard moves them under DevZero management.
Static capacity
Cluster autoscaling
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 profiling
Observability
The Right Sizing tab expands each workload into per-container CPU and memory usage against its recommendation. No runtime or code-level profiling is documented.
Builds a usage profile per workload from collected CPU, memory and runtime data and uses it to drive rightsizing recommendations.
Application health profiling
Observability
Triages error-budget burn from your own indicators and correlates alerts into incidents. Health signals come from connected observability tools, not a built-in agent.
Tracks OOM kills, crash loops, CPU throttling and container startup lifecycle events for each workload.
API latency, throughput and error detection
Observability
Request rates and latency are read only through connected observability integrations during investigations.
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 consolidation opportunities
Observability
Pod placement groups unevictable pods onto labelled nodes with a soft affinity so the autoscaler can remove the rest, and reports potential savings per cluster.
Previews underused nodes whose pods fit elsewhere in their node group and drains them on demand or by policy. Also flags duplicate and overlapping node policies.
Savings Plan, RI and CUD awareness
Cost attribution
Applies one enterprise discount rate you enter to public list prices. The AWS Cost Analyzer reports reserved-instance coverage gaps but does not price nodes by commitment.
Reads AWS, GCP and Azure billing exports to show commitment coverage and utilization and to price nodes at commitment-adjusted cost. It does not buy or manage commitments.
Horizontal pod autoscaling
Workload autoscaling
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
Skips HPA-managed workloads by default. With HPA right-sizing on, it converts the HPA metric to AverageValue so resizing does not trigger scaling.
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.
Language-aware autoscaling
Workload autoscaling
Policies tune percentile, buffers and caps per preset, with no runtime-specific handling such as JVM heap.
Raises the CPU request of detected Java containers to a startup floor, 75m by default, and can tune JVM heap flags when the heap rule is on. No other runtime has its own rule.
Workload profile-based autoscaling
Workload autoscaling
Policies select workloads by cluster, namespace, type and name patterns rather than by observed behavior profiles.
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
Not in the public docs as a dedicated reaction. The Overview counts under-provisioned containers fixed, and policies can allow right-sizing up.
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
No node provisioning is offered, so nodes are not chosen to fill Savings Plans or reservations.
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.
Workload profile-based node scaling
Cluster autoscaling
Pod placement is turned on per cluster, with no node policies tied to workload profiles.
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.
Live migration of running pods
Reliability
PodMotion checkpoints one container per pod with CRIU and restores it on another node. It needs containerd 1.6+, a podmotion RuntimeClass and labelled nodes; GKE needs special setup and GPUs are excluded.
Checkpoints a running container with CRIU and restores it on the replacement pod with its in-memory state. Opt-in per policy, on labelled nodes in the same cluster.
Checks before a change is applied
Reliability
Policy guardrails cap how far one change may move a value, and pods that cannot resize in place fall back to on-creation changes.
Live migration checks workload kind, image coherence and node readiness first, and skips the workload without changes if a check fails. Live migration is opt-in per policy and part of Pro.
Alerts on restarts, OOM kills and throttling
Reliability
Groups alerts from your monitoring into incidents, runs root-cause agents and proposes a fix for approval. Alerts must come from a connected source.
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.
Free tier
Pricing
Offers a 14-day free trial from the free-trial page. No permanent free tier or free plan is listed.
The free plan costs $0 and covers unlimited clusters with monitoring, cost attribution and 30-day data retention.
Last updated
Komodor prices by quote; DevZero publishes a flat per-CPU rate.
Customby quote
Komodor does not publish prices; request a quote.
$5per CPU per month
Billed on consumption, so compute savings lower your bill too.
Start freePublished results from customers who run DevZero in production.
Keep Komodor for incidents; move cost work one namespace at a time.
Start in non-production; it reads usage and cost without changing workloads.
Expect cost to differ: Komodor uses list prices less a discount rate, DevZero uses your bill.
Turn off Komodor rightsizing per namespace, then create DevZero workload rules.
Keep Komodor for troubleshooting; DevZero does not replace its AI SRE.
Komodor is an operations platform with AI SRE and cost modules. DevZero is built around cost, with node costs from your cloud bill and egress cost by destination domain.
Not for incident response. DevZero alerts cover restarts, out-of-memory kills, and CPU throttling, but it is built for cost and utilization.
Yes. It rightsizes with guardrails, resizes in place on Kubernetes 1.33 or later, and groups unevictable pods so autoscalers can remove nodes.
Yes. Komodor offers PodMotion. DevZero's live migration is opt-in per workload rule and works within one cluster.
DevZero Free is $0 and Pro is $5 per CPU per month. Komodor lists custom pricing and a 14-day trial.
“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
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.