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What IT should understand before implementing an in-memory computing solution


As I explained in ”Scale out and conquer architectural decisions behind distributed in memory systems,” choosing the right open source solution (such as a combination of Apache Ignite, Apache Kafka, Apache Spark, and Kubernetes) for an in-memory computing (IMC) infrastructure ensures a simpler and more cost-effective architecture for applications to support digital transformation and omnichannel customer engagement initiatives.

It is also critical when deciding on a solution to ensure the flexibility to deploy and manage the architecture to meet your organization’s requirements related to simplicity, security, availability, and cost. As you evaluate various IMC architecture alternatives, here are some key considerations to keep in mind.

Architecture deployment flexibility

The solution should offer the flexibility to be deployed on-premises; on an internal cloud, private virtual cloud, or public cloud; or on a hybrid environment. This flexibility is essential for balancing infrastructure costs and management requirements.

Server configuration

Be sure the in-memory computing cluster can be built using commodity servers. This is essential for controlling costs and increasing redundancy as the IMC infrastructure scales to dozens or even hundreds or thousands of servers.



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