Data infrastructure optimization in a multi-cloud architecture


Infrastructure is not realy a topic on which Masterdata focusses much attention

However, I found the recent post by our partner, Syncsort to be really interesting as they explored strategies for optimizing data infrastructure in a multi-cloud architecture

Many of our customers are exploring cloud options for managing data. yet, infrastructure, bandwidth and cost concerns can impact your ability to benefit from cloud.

Syncsort are data integration and optimization experts and deliver some really simple strategies for optimizing your multi-cloud investment that I think are very relevant in Africa.

 

 

These include:

  • Avoiding using equivalent services on multiple clouds – for example, only run Hadoop on one cloud rather than trying to move Hadoop data across cloud instances.
  • Store data where it is collected. This may sound obvious but many of us move data unnecessarily – for example, for analytics when we could run our analytics jobs in the same cloud as our storage.
  • Optimize data before you move it – data shroud be cleaned, deduplicated, compressed etc before it is moved to reduce time and costs and make it more useful once it arrives in the new cloud
  • And of course, using third party tools rather than each cloud providers in house tools can reduce the learning curve and make your IT team more productive.

Read the Syncsort blog past at http://blog.syncsort.com/2018/10/big-data/data-infrastructure-optimization-multi-cloud-architecture/ or download their free eBook, The New Rules for your Data landscape to learn more.

 

 

 

 

 

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