Reyk AI - Docs
  • About Reyki AI
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  • 🚀Optimization Features
    • Compute Optimization Engine (COE)
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    • Block Storage Optimization (BSO) Engine
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  • Reyki AI - Object Store Optimizer (OSO)
  • Additional Features
  • Snapshot Auto Manager (SAM)
  1. Optimization Features

Object Storage Optimization (OSO) Engine

Autonomous object storage optimizations and recommendations.

PreviousCompute Optimization Engine (COE)NextKubernetes Optimization Engine (KOE)

Last updated 1 year ago

Reyki AI - Object Store Optimizer (OSO)

Intelligent Data Tiering: Automatically monitor and balance your cloud storage needs across frequency of access, performance, and cost of ownership.

  • Automatically move data between different storage tiers based on access frequency patterns.

  • Fluidly move data between archived and non-archive storage tiers depending on changes in data access patterns.

  • Predictive recommendations can be toggled between "Full Autopilot" or "Require Approval" modes for fine-grain user control.

  • Transparently review data lifecycle management policies and augment them to manage tiering, archival, or deletion rules.

Additional Features

Workload Optimized: Additional meta-logic determines whether your data patterns pertain to traditional enterprise workloads or AI workloads, and then implement storage tiering recommendations that optimize performance in terms of latency, throughput, and cost according to use case best practices.

Stale Disk Termination: Identify and notify users of stale disks and analyze their cost of continued ownership over time. Recommend (or automate) their termination based on self-determined rules or AI algorithms to drive long-term storage savings.

Data Janitor Bot: Automatically identify, consolidate, and recommend garbage data for deletion. Common examples include the removal of extraneous "delete" markers of already-deleted data, which take up space; or removal of no-value fragments of failed multi-part uploads that consume extra storage.

Snapshot Auto Manager (SAM)

  • Recommend retention policies to minimize long-term storage costs of snapshots.

  • Optimize snapshot deletion mechanics by deleting entire snapshot chains, rather than just latest unwanted snapshot.

  • Use efficient boot-disk snapshots to create snapshot images, which in turn are used to create multiple VMs. This minimizes network charges for data traveling between the location of snapshots and the locations where you restore it.

  • Optimize creation and storage of snapshots in best-suited cloud regions, availability zones to minimize lowest network costs data.

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Use-case and workload driven storage tier recommendations

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Identify and recommend stale disks for review and termination

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Remove non-vital garbage meta data to enhance performance

Intelligent Storage Tier