Monitor and optimize your cloud spend with budget tracking, usage analysis, and right-sizing.
This requirements table for Cloud Cost Management products clearly outlines the key features and functionalities considered when evaluating vendors. We include Compliance, Integration, Security, Pricing, Workflow, Cost Visibility, Cost Optimization, Cost Ingestion, Cost Allocation, User Experience and Budgeting and Forecasting.
Other important considerations may include the level of technical support offered, the availability of detailed documentation and developer resources, and pricing and licensing options. Customize these requirements in Taloflow and get expert ratings for 15 different vendors against all of the features in the table below, including None.
| Requirement | Description | Features |
|---|---|---|
| Must access cloud platform data securely | Provides a safe and secure way to reliably pull cloud cost information and container telemetry. |
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| Must be suitable for financial planning | Must provide the reporting and modeling tools that FP&A needs for forecasting and accounting of cloud spend. |
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| Must connect costs to APM and observability data | Provides ready-made connectors for pulling in various application telemetry data, including logs, metrics, traces, and events, for cloud cost analysis. |
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| Must have affordable pricing | Must be competitively priced for the expected level of adoption of the tool and the projected growth in cloud spend. |
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| Must integrate with DevOps tools | Provides ready-made connectors for pulling and pushing event and cost data from/to the CI/CD pipeline. |
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| Must meet compliance standards | Must meet compliance requirements for the relevant industry or regulatory standards. |
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| Must meet enterprise auth and access control standards | Provides the standard enterprise features for limiting access to the application to specific groups of users and more secure authentication methods. |
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| Must optimize compute costs | Detects waste and leverages machine learning technology to map, predict, and manage cloud compute costs efficiently across instances and discount plans. |
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| Must optimize storage costs | Detects waste and leverages machine learning technology to map, predict, and manage cloud storage costs efficiently across disks, volumes, buckets, etc. |
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| Must post notifications to alerting tools | Provides ready-made connectors for pushing to various general or point solutions for alerting, communication, and incident management. |
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| Must provide comprehensive monitoring of cloud spend | Monitors all cloud platform spend with near-limitless possibilities for slicing and dicing the data to troubleshoot cost issues. |
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| Must provide comprehensive tools for cost allocation | Provides ways to automate chargeback and allocation of costs to business units/groups and monitor compliance with budgets. |
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| Must provide flexible deployment options | Provides a suitable and seamless path to integration and a short time to start getting value out of the tool. |
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| Must provide granular insight into Kubernetes-related spend | Must provide the same level of support for Kubernetes and container spend insights as other native cloud services. |
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| Must support cost data ingestion for the cloud stack | Must monitor and/or optimize cloud spend across the cloud stack. |
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| Must tie cloud costs to business impact | Provides a suite of tools to make business and engineering decisions based on marginal and average costs and ROI of cloud spend. |
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| Must tie cost insights to developer activity and workflow | Must make it intuitive for developers to predict and understand their costs, and troubleshoot issues with minimal disruptions to their habitual workflow. |
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