Optimize what is really driving your GCP spend
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30%
36 hrs
$2M+
12+
Connect GCP without changing how you run it
Bring your GCP data into view without adding another layer to manage. The connection is lightweight, requires no infrastructure deployment, and keeps access secured and limited to what OneLens needs.
Understand GCP costs to the level of your infrastructure
Use historical utilization to surface rightsizing and capacity opportunities
Go beyond workloads to understand node pools, instance types and cluster capacity behind that spend. Bring compute, storage and network costs together across workloads, teams, namespaces and environments.
Understand the usage and workloads contributing to spend
Identify the storage usage and configurations driving GCS cost
Surface logging cost back to where ingestion is growing
Trace GCP commitment opportunities using usage context
Connect spend to the services, resources and usage behind it
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Give every workload a cost
Allocate GCP spend across projects, teams and environments, including shared infrastructure where costs don't naturally belong to one owner.
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Give every workload a cost
Bring cost together with utilization, configuration and historical behavior to assess rightsizing, capacity and commitment opportunities.
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Turn spend into a business metric
Measure cloud cost per customer, feature, workload or usage unit to connect infrastructure spend with the economics of your business.
Turn cost signals into work that gets done
Move from identifying a cost issue to assigning ownership, routing the right action, and keeping spend against plan.
Tickets
Create policy-driven tickets with the affected resource, recommended action and potential savings, so the owner has the context needed to act.
Workflows
Route cost anomalies, policy violations and ticket events into Slack, Jira, ServiceNow and the workflows your teams already use.
Budgets
Track actual and projected spend against configured budget thresholds, and alert owners when spend is approaching or expected to exceed them.
Manage GCP at infrastructure depth
Other integrations
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OneLens brings GCP billing, usage and resource context together across services such as GKE, BigQuery, Storage, Logging, Networking, Databases and other managed services. This lets teams connect spend to the infrastructure and usage behind it, then work on rightsizing, capacity, commitments and other optimization opportunities.
OneLens connects GKE cost with CPU and memory utilization, resource requests and limits, node capacity, persistent storage and shared cluster costs. This gives teams the context to evaluate rightsizing and capacity decisions at the Kubernetes level rather than relying only on cluster-level spend.
OneLens provides allocation across organizational dimensions such as projects, teams, environments and cost centers, with Kubernetes allocation extending into namespaces and workloads. The approach can use business mapping, account and namespace structure, virtual tags and usage-based apportionment rather than depending entirely on perfect tagging.
OneLens combines cost with the technical context behind that spend, allowing teams to investigate utilization, capacity, rightsizing, commitments and resource behavior rather than optimizing billing data alone. Recommendations can then move into workflows with owners and approval paths instead of remaining as dashboard findings.
OneLens connects GCP cost with the infrastructure and usage driving it, including GKE utilization, resource capacity, BigQuery usage, storage, logging and commitments. It goes beyond reporting spend to connect allocation, optimization and action in the same workflow.
Yes. OneLens can track spend against budgets and use forecasting to give teams visibility into potential overruns. The underlying model is intended to make the drivers behind a forecast visible, rather than presenting an unexplained projected number.
OneLens is designed for multi-cloud cost management across AWS, Azure, GCP and OCI, with Kubernetes, GPU and AI spend brought into the same cost model.
Beyond public-cloud infrastructure, OneLens extends into Kubernetes, GPU infrastructure, LLM and AI spend, data platforms and observability costs. The broader technology scope includes data platforms such as BigQuery, Snowflake, and Databricks, alongside cloud and AI infrastructure.
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