AWS for Industries

Category: AWS CodeDeploy

Modernizing IMS networks on AWS

IP Multimedia Subsystem (IMS) is a platform for delivering IP-based multimedia services such as voice, video, text, and supplementary services (for example, call barring, message waiting, ad hoc conferences, and more) to fixed and mobile users. With 5G, which is a framework to connect these users to networks such as IMS, the core network (5GC) […]

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Fully automated CI/CD pipelines for deploying and managing Magma on AWS

Introduction Magma is an open-source, flexible, and extendable mobile core network solution. It is designed to be 3GPP generation and access network agnostic. Magma supports many radio technologies, such as LTE, 5G, and WiFi, and it enables use cases like mobile private networks, fixed wireless access, or mobile edge computing. It is governed by the […]

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Preparing for travel and hospitality’s recovery

This post is authored by Roger El Khoury – Founder and Managing Director of Neorcha. — How contactless services in hotels can help the industry bounce back Whilst we’re in the midst of the COVID-19 crisis, hoteliers around the world – as one of the hardest hit sectors globally- are preparing for a new normal. […]

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Enable agile mainframe development, test, and CI/CD with AWS and Micro Focus

Mainframes are still used by numerous organizations in sectors such as financial services or manufacturing. To thrive in today’s fast-moving economy, customers tell us they must accelerate the software development lifecycle (SDLC) for applications hosted on their mainframes. Micro Focus development and test solutions combined with AWS DevOps services provide the speed, the elasticity, and […]

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Enabling mainframe automated code build and deployment for financial institutions using AWS and Micro Focus solutions

Mainframes are used by financial institutions for critical applications, batch data processing, online transaction processing, and mixed concurrent workloads. They have non-functional requirements such as performance, security, and resource availability to process all workloads, even in development environments. However, potential resource and parallelism reduction may occur during the development of new programs and subsequent testing. […]

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