Infracost included in The Forrester Cloud Cost Management And Optimization Solutions Landscape, Q3 2026

We're excited to share that Infracost is included in The Forrester Cloud Cost Management And Optimization Solutions Landscape, Q3 2026.

The report gives technology leaders an overview of vendors in cloud cost management and optimization.

Cost is an engineering decision

Engineers make most of the decisions that drive cloud spend: which instance type, how many replicas, which storage tier, whether to turn on that managed service. Yet they rarely see the cost of those choices until the bill arrives weeks later. By then, the change is in production and fixing it means rework.

We built Infracost to close that gap. Infracost shows engineers the cost impact of their infrastructure changes directly in the pull request, before anything is deployed. FinOps and platform teams get a way to set cost and tagging policies once and have them checked automatically on every change.

The result is fewer surprises on the bill, and far less back-and-forth between finance and engineering. The cheapest time to fix a cost problem is before it ships.

AI is reshaping FinOps from both sides

AI is changing cloud cost in two ways at once, and FinOps teams are feeling both.

First, AI is a fast-growing cost in its own right. Model choice, token usage, and inference patterns introduce pricing that is harder to predict and harder to attribute than a traditional VM or database. A single decision, like which model a feature calls, can swing monthly spend dramatically.

Second, AI is changing who writes infrastructure code. Coding agents now generate Terraform and Kubernetes configs in seconds, and the volume of infrastructure changes is growing faster than any team can review for cost. If cost awareness depends on a human noticing a problem in review, it won't keep up.

Both trends point to the same answer: cost context has to live inside the workflow where changes are made, whether a person or an agent is making them.

Where we're focused

Beyond core cost visibility, we're investing in three areas where we think engineering-led FinOps matters most:

• AI cost management. AI workloads bring new pricing models and far less predictable spend. Teams need cost context for these choices at design time, not after the invoice.

• Container cost management and optimization. Kubernetes makes it easy to over-provision and hard to see who owns what. We want container costs to be as visible to engineers as any other infrastructure change.

• Policy and governance automation. Cost policies work best as code: versioned, reviewed, and enforced automatically in the same workflow engineers already use.

Where we're headed

Putting cost in the pull request was step one. The next phase is making cost context available everywhere infrastructure decisions happen, including to AI.

• Cost context for AI coding agents. When an agent writes or modifies infrastructure code, it should know what that change will cost before it proposes it, and follow the same cost and tagging policies an engineer would.

• Agents that fix cost issues already in production. Shifting left prevents new waste, but most organizations also carry years of it. We're building toward agents that find cost issues that have already shipped and open the fix as a pull request, ready for an engineer to review and merge.

• AI spend in the same workflow. Model and GPU choices should get the same cost visibility and policy checks as any other infrastructure change.

Our customers and open source community are how we get there. Thousands of engineers and FinOps practitioners use Infracost every day, and their feedback, issues, and contributions decide what we build next. Many of the ideas above started as requests from them.

Want to see what cost-aware engineering looks like for your team? Book a demo or try Infracost for free.

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