7 Steps to Deploy the MapR Sandbox on Microsoft Azure
by James Sun
If you’ve been keeping tabs on all of the great product enhancements that have been coming out of MapR, you will know that the 5.2 version of the MapR Converged Data Platform went GA this summer. It takes a few cycles to make the platform available on the Azure Marketplace, largely due to the testing efforts required. We’re pleased to announce that version 5.2 can now be deployed on the Azure marketplace as a sandbox offering.
MapR has worked closely with Azure to develop sandboxes that enable users to do a proof of concept with the MapR Converged Data Platform. These sandboxes, which are pre-loaded and preconfigured with the MapR software and the required supporting operating system, can be launched on the Azure Marketplace portal. They require no additional license charges from MapR; you only have to pay Azure based on hourly usage of the VMs. This blog post will cover the details of how you can get a MapR Sandbox up and running in less than 10 minutes on the Azure platform.
Working with the Azure MapR marketplace sandbox
Since a lot of MapR partners and customers already have Azure accounts, and MapR has partnered with the Azure marketplace to provide sandboxes which bypass the installation phase, we believe this will be very beneficial to speed up Proof of Concepts (POCs).
Point your browser to https://portal.azure.com and login to your Azure account. In the search area, click on the “+New” option on the left pane, type in MapR, and you will find a few MapR Azure marketplace offerings as illustrated below.
Select the desired offering. e.g., MapR Converged Data Platform 5.2 in Sandbox
After you selected a desired offering, you will see an introduction screen as illustrated below. Go ahead and click on “Create.
In this screen, you need to provide information such as cluster name, disk type for the VM, username to login to the VM, password, your subscription name and resource group. Note that you can either select new or existing resource group. After you have filled in the information, select “OK” to proceed to the next step.
In this step, you will need to select the VM size. You can expand the “View all” on the top right corner of the screen to see more options. In this case, we selected “D3 Standard.” Click “Select” to move forward.
In this step, you are going to configure storage and the corresponding network for the VM. You can either create a new or existing storage account—let’s create a new one. Similarly, we choose to create a new network for our VM in this demo. Fill in the name of network as well as the address space and subnet address range, and then hit “OK.”
In this step, you can review your VM settings. Click “OK” if everything looks good.
In this step, you need to review the purchase agreement. Click “Purchase” to proceed.
If everything goes well, you should see a successful deployment in about 10 minutes. Click on the “Virtual Machines” option on the portal, then click on the VM name to find out its IP address.
Once you have the IP address of the VM, point your browser at: https://<VM IP>:8443 to go to the MapR Control System (MCS) portal. Login with the credentials that you provided when creating the VM.
In MapR 5.2, we have also added new monitoring capabilities based on open source tools like Kibana and Grafana. For Kibana, you can point your browser at http://<VM IP>:5601 and for Grafana, point your browser at http://<VM IP>:3000. For more information regarding MapR Monitoring, refer to this URL: https://www.mapr.com/resources/mapr-monitoring
We have walked you through how to spin up a MapR Sandbox on the Azure cloud. In order to take full advantage of the MapR cluster for your big data analytics, try out Apache Drill (http://drill.apache.org), the SQL-on-Hadoop engine that is gaining a lot of momentum in the community. You can quickly start exploring big datasets without having to model schemas upfront. Just simply point your browser at: http://<VM IP>:8047.
There’s an extensive set of Drill tutorials, which walk you through the steps required to query data stored in a MapR cluster, and extract insights and visualize the findings using Tableau, a leading visualization tool that is part of the broader ecosystem. Finally, I encourage you to check out the MapR Converge Community (http://community.mapr.com), where you can find lots of resources and FAQs about various topics. You can also ask questions and get quick responses to those.
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Content Originally posted in MapR Converge Blog post, visit here
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