Manually tracking cloud usage is both time-consuming and prone to errors, increasing the risk of cost overruns. A unified approach to governing multi-cloud costs is essential, involving the consolidation and analysis of data from all providers to ensure comprehensive visibility. This empowers organizations to detect underutilized resources, optimize pricing, and enforce effective cost management policies across their infrastructure.
By Mohammad Wahba, Director, Systems Engineering – Middle East, Nutanix
As organizations are driven towards digital transformation strategies and as they modernize legacy applications to achieve business agility, it is clear that hybrid cloud environments is the way forward. However, with a mix of private and public clouds, expanding across multiple cloud service providers, they face the daunting task of maintaining visibility and control over cloud costs. Manually tracking and analyzing cloud usage across different accounts and services is a time-consuming and error-prone process that can lead to cost overruns and hidden inefficiencies.
Effective multi-cloud cost governance requires a unified approach that aggregates and analyzes data from all cloud providers, providing a comprehensive view of cloud spending. This visibility enables organizations to identify underutilized resources, optimize pricing strategies, and enforce cost policies across their entire multi-cloud environment.
The Power of Automation in Multi-Cloud Cost Management
Automation is a game-changer for multi-cloud cost management. By automating routine tasks, such as resource provisioning, scaling, and cost analysis, organizations can free up their IT teams to focus on strategic initiatives and innovation. Automation also helps to ensure consistency and compliance with cloud policies, reducing the risk of errors and non-compliance issues.
We define key pillars of automation that serves the multi-cloud cost management and governance as following:
· Resource provisioning automation: Automate the creation and provisioning of apps/data, ensuring cost-effectiveness and consistency across environments.
· Resource scaling automation: Leverage automated scaling policies to dynamically adjust resource capacity based on real-time usage patterns, preventing overprovisioning and unnecessary costs.
· Cost monitoring and alerting: Employ automated monitoring tools to track cloud spending, identify anomalies, and generate alerts for potential cost overruns or non-compliant usage.
· Cost optimization recommendations: Implement AI-powered tools to analyze cloud usage patterns and recommend cost-saving strategies, such as switching to more cost-effective instance types or optimizing storage allocation.
Nutanix, an established leader in hybrid multi cloud computing assists organizations with its unique offering for ‘FinOps-as-a-Service’. The company provides enterprises with a unique offering for multi-cloud cost management & governance assuring:
– One-click visibility
– Control Cloud Sprawl
– Automated insights
Nutanix’s leadership in the field of cloud cost management comes with new innovations emerging to address the challenges of multi-cloud environments.
· AI-powered cost forecasting: AI algorithms can be used to predict future cloud spending based on historical usage patterns and market trends, enabling proactive cost management and budgeting.
· Cloud cost anomaly detection: Machine learning techniques can identify anomalies in cloud usage patterns, such as spikes in resource consumption or unexpected account activity, helping to uncover potential issues before they lead to significant costs.
· Granular cost allocation: Tools are emerging that enable organizations to allocate cloud costs to specific business units or projects, providing greater visibility into cost drivers and enabling more granular cost optimization.
In summary, Nutanix FinOps-as-a-Service helps organizations achieve optimum hybrid multi cloud cost control with a complete offering that combines best-in-class cloud consumption analytics with award-winning Professional Services.
