Find the Right GCP Cost Optimization Tool

There are dozens of cloud cost tools. Most are built for AWS. Here is an honest comparison of the tools that actually work well with Google Cloud Platform in 2026 — what they do, where they fall short, and which one fits your team.

Feature Comparison

FeatureCloud GuardianInfracostVantageCloudZeroTernaryCAST AI
GCP Support Deep (9 resource types) Yes (IaC cost estimates) Yes (cost visibility) Basic (AWS-first) GCP-native GKE only
Cloud Run Optimization Deep (CPU, memory, idle, instances)Cost estimates onlyBasic cost trackingCost attribution
Automated Remediation Yes (direct + Terraform PRs) K8s autoscaling
GitHub PR Integration Yes (Terraform fix PRs) Yes (cost estimate comments)
Scale-to-Zero Detection
Artifact Registry Cleanup Yes (auto cleanup policies)
Secret Manager Optimization
Cost Verification (re-scan after fix) Yes (automatic)
Multi-Cloud SupportGCP only AWS, Azure, GCP AWS, Azure, GCP + AWS, Azure, GCPGCP only AWS, Azure, GCP
Free Tier Free during beta Free (open source) Free for small usageNo Free tier available Free for monitoring
MCP / AI Integration 70+ MCP tools for Claude CodeLimited API
Open Source NoNoNoNo

Last updated March 2026. Feature availability based on public documentation. Reach out if anything is inaccurate.

Tool-by-Tool Breakdown

Cloud Guardian: Automated GCP Cost Remediation

Cloud Guardian is purpose-built for Google Cloud Platform. Unlike dashboards that show you what's wrong and leave you to fix it, Cloud Guardian scans 9 resource types — Cloud Run, Compute Engine, Cloud SQL, Cloud Storage, Cloud Functions, GKE, BigQuery, Secret Manager, and Artifact Registry — then generates and applies Terraform fixes automatically via GitHub PRs.

Its standout feature is the closed-loop remediation cycle: detect a violation, plan a fix, open a PR (or apply directly for critical cost issues like cpu_idle disabled or unnecessary min_instances), then re-scan to verify the savings actually materialized. This eliminates the most common FinOps failure mode — recommendations that never get implemented.

Cloud Guardian also ships an MCP server with 50+ tools for Claude Code integration, making it the first cost optimization platform designed for AI-assisted infrastructure management. It is free during beta and open source.

Infracost: Pre-Deploy Cost Estimation

Infracost is an open-source tool that estimates cloud costs from Terraform code before you deploy. It integrates into CI/CD pipelines and posts cost-diff comments on pull requests, helping teams catch cost increases before they hit production.

Infracost excels at shift-left cost awareness — you see the dollar impact of every infrastructure change at code review time. However, it does not monitor running infrastructure, detect waste in existing resources, or automatically remediate issues. Think of it as a preventive tool rather than a detective or corrective one.

For GCP teams, Infracost covers the major resource types but lacks the depth of Cloud Run-specific optimization (CPU idle settings, min instances, scale-to-zero detection) that a GCP-focused tool provides.

Vantage: Multi-Cloud Cost Visibility

Vantage provides cost dashboards, reports, and budgeting across AWS, Azure, GCP, Kubernetes, Datadog, Snowflake, and more. It is the strongest option for teams that need a single pane of glass across multiple providers and SaaS tools.

On the GCP side, Vantage connects to billing exports and provides cost allocation, anomaly detection, and savings recommendations. It does not, however, offer automated remediation — you receive recommendations and act on them manually.

Vantage is a good fit for large organizations that need executive reporting and cost allocation across many cloud accounts. For teams focused specifically on GCP serverless optimization, a dedicated tool will go deeper.

CloudZero: Unit Economics for Cloud Spend

CloudZero focuses on unit economics — mapping cloud costs to business dimensions like customers, features, or teams. It answers questions like 'how much does it cost to serve customer X?' rather than 'which Cloud Run service is over-provisioned?'

CloudZero is AWS-first. While it supports GCP billing data ingestion, the deepest integrations, recommendations, and automation are built around AWS services. GCP-heavy teams will find the experience less polished.

For organizations where cost allocation and chargeback across business units is the primary concern, CloudZero is strong. For teams that need hands-on resource optimization and auto-remediation on GCP, it is less relevant.

Ternary: GCP-Native FinOps

Ternary (now part of the Virtana portfolio) is one of the few cost management tools built specifically for Google Cloud. It connects to BigQuery billing exports and provides cost allocation, CUD/SUD analysis, and budget management tailored to GCP's billing model.

Ternary's GCP-native approach means it understands committed use discounts, sustained use discounts, and GCP-specific pricing nuances that multi-cloud tools sometimes handle incorrectly. It is the closest direct competitor to Cloud Guardian in the GCP space.

Where Cloud Guardian and Ternary diverge is in approach: Ternary is a visibility and planning tool (dashboards, reports, CUD recommendations), while Cloud Guardian is an action-oriented tool (scan, fix, verify). If you need reporting for FinOps stakeholders, Ternary is solid. If you need your infrastructure to actually change, Cloud Guardian goes further.

CAST AI: Kubernetes Cost Optimization

CAST AI specializes in Kubernetes cost optimization across AWS EKS, Azure AKS, and GCP GKE. It automatically right-sizes pods, rebalances nodes, and leverages spot/preemptible instances to reduce cluster costs — often by 50% or more.

If your GCP workloads run on GKE, CAST AI is the best-in-class option for cluster optimization. It actively manages your infrastructure (not just recommends) and can demonstrate significant savings quickly.

However, CAST AI only covers Kubernetes. If you run Cloud Run services, Cloud Functions, standalone Compute Engine VMs, or need to manage Artifact Registry and Secret Manager waste, you need a complementary tool. Cloud Guardian and CAST AI pair well together — CAST AI for GKE, Cloud Guardian for everything else.

When to Choose Cloud Guardian

Cloud Guardian is not the right tool for every team. Here is where it shines — and where you might be better served by one of the alternatives above.

GCP-only or GCP-primary teams

If Google Cloud is your primary (or only) cloud provider, you benefit from the deep GCP-specific resource scanning that multi-cloud tools cannot match.

Serverless-heavy architectures

Cloud Run, Cloud Functions, Secret Manager, Artifact Registry — if these are your core infrastructure, Cloud Guardian covers them at a depth no other tool does.

Teams that want auto-remediation, not dashboards

If your problem is not 'we don't know what's wasteful' but 'we know but nobody has time to fix it,' Cloud Guardian's automated fix-and-verify loop solves that.

Small to medium engineering orgs

Startups and mid-size teams without a dedicated FinOps team benefit most from automation. Enterprise teams with established FinOps practices may prefer the reporting depth of Vantage or Ternary.

AI-assisted infrastructure management

If your team uses Claude Code or similar AI tools, Cloud Guardian's 70+ MCP tools let you query costs, trigger remediations, and manage infrastructure conversationally.

Open-source preference

Cloud Guardian is open source. You can audit the code, self-host, and contribute. If vendor lock-in or transparency matters to your team, this is a differentiator.

Try Cloud Guardian Free

Free during beta. No credit card required. Connect your GCP projects in under 5 minutes and see your first cost savings within an hour.