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Harness Cloud Cost Management

San Francisco, California, United States

What it is

Harness Cloud Cost Management is a web service for tracking and managing cloud costs across AWS, Azure, and Google Cloud Platform. It supports cost allocation, budget alerts, spend forecasting, rightsizing guidance, and commitment management. These tools let teams assign spending, monitor budgets, estimate costs, and manage cloud commitments. The service uses per-spend billing. Its Free Plan costs nothing and includes community support. The Cloud Cost Management plan has fees based on tracked cloud spend: Cloud Cost Insights is charged at 1% of total tracked cloud spend, Commitment Orchestrator and Autostopping at 1.25% for specified spend, and Cluster Orchestrator at 2% of tracked Kubernetes cloud spend. Paid pricing is available on request. The service is offered by Harness, founded in 2017 and headquartered in San Francisco, California.

For and against

For

  • Supports AWS, Azure, and Google Cloud Platform
  • Includes cost allocation and budget alerts
  • Offers spend forecasting and rightsizing guidance
  • Free Plan includes community support

Against

  • Paid plan fees are based on tracked cloud spend
  • Paid pricing is available on request

The verdict

Harness Cloud Cost Management brings several cloud cost management tools together in a web service. A free tier is listed, while paid fees are tied to tracked spend.

Who it suits

It suits teams that need to monitor cloud costs across AWS, Azure, or Google Cloud Platform. Teams can use its allocation, alerts, forecasting, rightsizing, and commitment tools to manage spend.

Plans and prices

Free Plan

Free

Free tier · Community support

Cloud Cost Management

Priced on request

Fees are charged as a percentage of tracked cloud spend · Cloud Cost Insights is charged at 1% of total tracked cloud spend · Commitment Orchestrator and Autostopping are charged at 1.25% for specified spen · Cluster Orchestrator is charged at 2% of tracked Kubernetes cloud spend

Every plan, in full

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