Lucidity AutoScaler Tackles Kubernetes Storage Waste with Automated Persistent Volume Management
Lucidity has expanded its cloud storage management platform to address a persistent problem in Kubernetes environments: underutilized Persistent Volumes that quietly drain cloud budgets.
The company announced that AutoScaler now supports Amazon EKS, automatically rightsizing Persistent Volumes based on real-time data demands. This addresses what Lucidity calls "a sneaky source of invisible waste" where Kubernetes scales compute instances dynamically but leaves storage untouched and often severely underutilized.
The Kubernetes Storage Problem
While Kubernetes excels at scaling application instances up and down based on demand, the underlying storage remains static. Persistent Volumes provisioned for workloads often sit at low utilization rates, sometimes for months, creating unnecessary cloud costs that can easily go unnoticed.
"Most companies provision Persistent Volumes conservatively to avoid performance issues, but then never optimize them afterward," explains the challenge that many platform engineering teams face when managing containerized workloads at scale.
Technical Implementation
AutoScaler's Kubernetes integration works by:
- Monitoring real-time data usage across EKS Persistent Volumes
- Automatically expanding and shrinking storage without downtime or manual intervention
- Maintaining optimal capacity based on actual application demands rather than initial estimates
- Operating alongside existing Kubernetes infrastructure without requiring changes to application code
The system transforms what Lucidity describes as "static Persistent Volumes that are difficult to manage" into "truly dynamic Persistent Volumes that respond to real-time data needs."
Developer and DevOps Benefits
The update brings several practical advantages for engineering teams:
Reduced Manual Overhead
- Eliminates the need for manual Persistent Volume monitoring and resizing
- Removes storage capacity planning guesswork for containerized applications
- Frees up engineering time from routine storage maintenance tasks
Better Visibility
- New CSV reporting module provides on-demand insights into savings, coverage, and policy compliance
- Helps teams track and communicate storage optimization value to leadership
- Offers transparency into storage utilization patterns across Kubernetes clusters
Faster Implementation
- Bulk onboarding capabilities for Linux environments speed up enterprise deployments
- Enables rapid setup across petabyte-scale storage environments
- Reduces time-to-value for organizations migrating from on-premises to cloud
Cost Impact
According to Lucidity's data, customers typically see up to 70% savings on cloud block storage spending. For Kubernetes environments specifically, this could be significant given how easy it is for Persistent Volume waste to accumulate unnoticed across multiple clusters and namespaces.
The automation aspect is particularly relevant for teams managing large Kubernetes deployments where manually optimizing hundreds or thousands of Persistent Volumes would be impractical.
Integration Considerations
AutoScaler supports AWS EKS initially, with other Kubernetes platforms likely to follow. The system works across AWS, Azure, and Google Cloud for traditional VM-based workloads, suggesting multi-cloud Kubernetes support may expand over time.
For teams evaluating the technology, key considerations include:
- Current Persistent Volume utilization rates across clusters
- Manual effort spent on storage capacity management
- Integration requirements with existing monitoring and automation tools
- Compliance and security requirements for automated storage operations
The Kubernetes storage management space has relatively few automated solutions, making this a notable development for platform engineering teams dealing with cloud cost optimization and infrastructure automation challenges.
