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shared services (i.e. audit logging, monitoring, and message deliveries). Improved productivity and reliability. Reduced cost compared to on-premises servers.
with cutting-edge Machine Learning libraries. AWS and Azure Cloud Technologies already have integrations with powerful, open source ML libraries such as TensorFlow.
and reduce deployment and operational complexities. Cloud management services can be adopted across multiple applications to facilitate overarching processes.
to determine system components (i.e. Campaign Management Modules, Interaction / Real-time Modules, Other Migration Components and Considerations)
established for further support in the event of a system failure
to compute elements and reduce latency (dynamic) and simplify processes for the requester using content delivery services with coaching for faster access to popular objects (static)
ensures the protection of data in transit (i.e. with TLS/SSL and Amazon Virtual Private Cloud) and fortifies the application with security groups in place to manage open protocols/ports, while also performing tests to mitigate threats from cross-site scripting, SQL Injection, Command Injection, Path Traversal, and insecure server configurations
of each node to validate input and output within the system network
to establish system limits and failure points, and gain a greater understanding of services reaching resource contention (which can lead to system deadlock)
to verify application’s communication exclusion rules to outgoing data and ensure that messages are delivered to the appropriate customers
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