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Documentation Index

Fetch the complete documentation index at: https://docs.kubex.ai/llms.txt

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Policies are used with the analysis models to analyze your collected data to populate the tables and charts in the your Kubex interface. When data is collected an environment is created and the policy is selected based on your specific use case. Kubex policies allow you to tailor the Kubex analytics engine to accurately maximize efficiency and minimize risk. Policies represent the unique requirements, constraints and operational goals of your virtual environments. Once captured, policies can be customized and re-used for each of your various environments. You can work with your account manager to customize the policy to better suit your requirements, if necessary. You need an understanding of not only your current infrastructure, but also of business and operational guidelines that are unique to your company or line of business before making any policy changes. Once selected and customized, your policy is used to provide details of your infrastructure efficiency. Policies cover both quantitative criteria such as maximum and minimum utilization levels, etc. and qualitative criteria such as business rules, technical affinities/anti-affinities, security requirements, process requirements, etc. Kubex provides a number of policies that can be used immediately to generate results for review. After reviewing the initial results you can then decide if you need to use another policy or customize the policy settings.
  • Initial Assessment—This policy produces end-state recommendations rather than gradual changes. It is intended for short term assessments when the recommendations are validated and confirmed before being applied. This policy is not recommended for on-going, automated implementation of the recommendations.
  • Ongoing Management—This policy reflects best practices for generating actionable recommendations. The resource utilization of each system is modeled using a minimum of 7 days and up to 60 days of historical workload. When downsizing systems, the predicted CPU and memory usage levels must not exceed 70% and 90%, respectively. When the memory usage metrics are not available, the analysis effectively assumes the existing memory allocation of the instance is required.

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    Policy Categories Overview

    Each policy is organized into categories. Each category groups policy settings based on how the settings define your environment.
    Policy CategoryDescription
    Representative Workload and Operational WindowingPolicy settings related to representative day selection, and the settings that affect the selection and scope of historical utilization data to model system workloads.
    Container Sizing - CPU UpsizePolicy settings used to determine whether container/instance CPU allocation is under-provisioned, and used to recommend resource allocation increases.
    Container Sizing - CPU DownsizePolicy settings used to determine whether container/instance CPU allocation is over-provisioned, and used to recommend resource allocation decreases.
    Container Sizing - CPU Allocation RangesCriteria that are used to determine recommended CPU allocation changes.
    Container Sizing - Memory UpsizePolicy settings used to determine whether container/instance memory allocation is under-provisioned, and used to recommend resource allocation increases.
    Container Sizing - Memory DownsizePolicy settings used to determine whether container/instancememory allocation is over-provisioned, and used to recommend resource allocation decreases.
    Container Sizing - Memory Allocation RangesCriteria that are used to determine recommended memory allocation changes.
    Container Technology and Output MappingPolicy settings that affect .

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    Commonly Tuned Policy Settings

    Before onboarding your environments you can optionally meet with an account manager to review the your requirements and then select tune the policy settings to align with your requirements. The following settings are commonly tuned for container environments:
    • Workload history—The number of days of data needed for different types recommendations.
    • CPU and Memory Utilization Limits—These policy settings define the up/down sizing and idle detection limits.

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    Video Resources