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kave on azure deployment

Riccardo Vincenzo Vincelli edited this page Aug 31, 2016 · 5 revisions

Deploying a cluster on Microsoft Azure

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Three different deployment styles

Deployment on Azure can be done in three different ways, deployment is described elsewhere

  • Manual deploy. The user provisions and configures all machines, and installs KAVE as if it were any other cluster, see Installing AmbariKave
  • Marketplace deploy: The user clicks a button on the Azure marketplace and the provisioning of a fixed/static set machines with fixed/static configuration is performed with minimal user intervention see AmbariKave-azure and links to be provided in the future
  • Template deploy: the user chooses from a list of clusters, sizes, and configurations, clicks a deployment link on github and then this set of machines and configurations is deployed with minimal intervention from the user. See AmbariKave-azure-templates

Marketplace deployment

This deployment method is the classic one click install via the Azure Marketplace.

The user goes through a wizard filling a few details in an the deployment is launched: when the status on the portal is green, so successful, then the user will be able to connect to the cluster, using SSH, VNC or RDP.

When the deployment is confirmed successful on Azure the cluster is ready and you can connect using one of the methods above. Consider though that the installation of the Ambari services may still be in progress, therefore make sure no tasks are in progress or pending before you start to use the cluster actively - you can monitor this via the Ambari webapp.

In case the Azure provisioning fails, try to connect to the gate anyway, because this is usually a symptom of Azure having trouble to assess the provisioning state and timing out to early, while the AmbariKave automatic setup was successful instead.

Table of Contents

For users, installers, and other persons interested in the KAVE, or developing solutions on top of a KAVE.

Kave on Azure

For contributors

For someone who modifies the AmbariKave code itself and contributes to this project. Persons working on top of existing KAVEs or developing solutions on top of KAVE don't need to read any of this second part.

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