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ading1977 Merge pull request #275 from ading1977/OM-46988
Add stitching metadata for kubernetes VM for stitching with XL server
Latest commit f91bd9b Jun 24, 2019
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build kubeturbo 64 version update (#265) May 14, 2019
cmd/kubeturbo Revert the change May 21, 2019
debugging Add support for building debugging images. May 22, 2019
deploy supplied links for sample yamls Jun 20, 2019
docs/design/actions implement Move by set invalid schedulerName Jun 27, 2017
examples Implemented Pod Affinity/Anti-Affinity Constraints Jul 19, 2017
hack Used Pod UID, Namespace and Name to Construct a Global UUID Used in T… May 17, 2017
logging-agent Add date to log file name in logging agent (#175) Apr 10, 2018
pkg Patch VMEM peak Jun 24, 2019
test fix-OM-28151: move failure because of node IP Dec 27, 2017
vendor Update turbo-go-sdk and go mod to include change in sdk Jun 24, 2019
.gitignore Use the latest golang to get dlv to avoid surprises May 22, 2019
.travis.yml Change go version to 1.11 in travis configuration Feb 20, 2019 Updates to documentation, sample yamls and helm chart for 6.3 feature… Apr 9, 2019 adding contributing guide framework doc Oct 8, 2016
Dockerfile.debug Add support for building debugging images. May 22, 2019
Dockerfile.delve Use the latest golang to get dlv to avoid surprises May 22, 2019
Makefile Enforce dockerhub repository and the version for debug images to avoi… ( Jun 15, 2019 readme typos Jun 20, 2019
go.mod Update turbo-go-sdk and go mod to include change in sdk Jun 24, 2019
go.sum Update turbo-go-sdk and go mod to include change in sdk Jun 24, 2019


  1. Overview
  2. Getting Started
  3. Kubeturbo Use Cases
  4. Coming Soon


Kubeturbo leverages Turbonomic's patented analysis engine to provide visibility and control across the entire stack in order to assure the performance of running micro-services in Kubernetes Pods, as well as the efficiency of underlying infrastructure.

Getting Started

Kubeturbo Installation

  • Review the prerequisites and Deploy Kubeturbo.
  • (Optional) To prepare Kubeturbo for debugging, go here.
  • Once deployed, corresponding k8s/OS cluster targets will show up in Turbonomic UI.

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Use Cases

  • Full-Stack Visibility by leveraging 50+ existing Turbonomic controllers, from on-prem DataCenter to major public cloud providers. No more shadow IT
    • From Load Balancer all the way down to your physical Infrastructure
    • Real-Time resource monitoring across entire DataCenter
    • Real-Time Cost visibility for your public cloud deployment

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  • Intelligently, continuously redistribute workload under changing conditions by leveraging The Turbonomic analysis engine
    • Consolidate Pods in real-time to increase node efficiency
    • Reschedule Pod to prevent performance degradation due to resource congestion from the underlying node
    • Reschedule Pod to leverage resources from new node added to the cluster
    • Reschedule Pods that peak together to different nodes, to avoid performance issues due to "noisy neighbors"

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  • Right-Sizing your Pod and your entire IT stack
    • Combining Turbonomic real-time performance monitoring and analysis engine, Turbonomic is able to provide right-sizing information for each service as well as the entire IT stack.
    • Right-sizing up your Pod limit, if necessary, to avoid OOM
    • Right-sizing down your Pod requested resource, if necessary, to avoid resource over-provisioning or overspending in public cloud deployment. screen shot 2017-06-01 at 9 56 55 am

Coming Soon

  • What-If Planner in 6.4
    • A complete What-If sandbox to help you plan your IT changes in advance
    • Plan for workload change: Add/Remove Containers
    • Plan for infrastructure change: Add/Remove/Replace Nodes
  • Also in 6.4:
    • Manage guaranteed resources: insight into requests across the cluster
    • Consistent resizing of containers for the same service
  • Storage control for persistent volumes
  • Added dimensions in SLO based control
    • Manage horizontal scaling of services without thresholds
    • Manage the trade-offs of performance, availability of resources, and compliance
    • Leverage your SLO data to add response time and throughput leveraging telemetry data collected - Istio, Prometheus, etc
  • Support for Cluster Federation Control Plane
    • Complete visibility for your K8s deployments across different underlying infrastructures
    • Create affinity/anti-affinity policies directly from Turbonomic UI
    • Improve cost efficiency by consolidating workload across deployments and identifying the cheapest region and provider to deploy your workload
    • What-if planning for Cluster Consolidation for federated clusters
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