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Load balancing, high availability and automated back up on cloud

Here’s how we enabled load balancing and high availability clustering on cloud with automated data replication for a Manufacturing firm on SUSE and SAP HANA

Customer Challenges

The customer, a manufacturing firm had a cloud hosted application.

  • During heavy data traffic, the application was unable to scale dynamically to support the traffic
  • Since automated backup was not available, daily manual back up was getting very time consuming as the application data was growing in volume.
  • Any network or hardware failure, resulted in unexpected interruption was unavailable. The downtime in the application incurred huge monitory losses.

Key Technologies

  • Ubuntu Server
  • Azure Load balancer
  • NSG
  • Azure Active Directory
  • Clustering and Resource Monitoring
  • Continuous Data Replication for Failover
  • Open SUSE

Software Used

  • Server application ( Node JS / DotNET/ Php )
  • Corosync, Pacemaker ( Clustering )
  • Hawk Console ( Resource Monitoring )
  • Hana Database

Solution Highlights

  • Using Azure Load balancer, VMs were configured for high availability
  • Clustering for both the VMs at OS level using pacemaker and corosync
  • Automated Data replication from the primary server to secondary server to ensure data consistency
  • Monitoring cluster nodes using Hawk
  • Configuring health probes and backend pools for scaling up the application

Implementation Steps

  • Firstly, a resource group on Azure was created. Then, a VM was added to that specific resource group to add all the created resources
  • Two Opensuse VMs were created in availability set. A load balancer was configured on the backend to Opensuse.
  • Opensuse VM packages were updated, and then the required packages were installed for clustering. By configuring both the VMS, clustering was enabled between two the VMs at OS level.
  • HAWK Console was used to monitor the created resources.
  • HANA database was installed in both VMs and SAP Hana studio was used for clustering and replication was performed from primary to secondary database.
  • The resources to be monitored were then configured from Azure and across the OS level.
  • After this, topology of master and slave was configured.
  • An Active Directory application was created and configured to the created VMs which allowed us to monitor the application from azure.
  • After this level of configuring clustering replication,
  • Successful failover and failback tests were performed
  • The data that was replicated was verified


  • Biased routing of traffic – effective routing of the traffic during peak load by distributing the load among the 2 servers
  • Automated data backup – with the data being backed up automatically, disaster recovery management is in place
  • High availability – for seamless back up and failover
  • Cluster Monitoring/ Management – view and analyze the logs to assess the performance of the clusters
  • Automatic reconfiguration & Dynamically Scalable
  • Reliable protection for mission critical data since high availability even during down time
  • Robust management across all platforms.

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