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portada Programming Microsoft Azure Service Fabric (Developer Reference)
Type
Physical Book
Year
2018
Language
English
Pages
528
Format
Paperback
ISBN13
9781509307098
Edition No.
2

Programming Microsoft Azure Service Fabric (Developer Reference)

Haishi Bai (Author) · Microsoft Press · Paperback

Programming Microsoft Azure Service Fabric (Developer Reference) - Haishi Bai

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Synopsis "Programming Microsoft Azure Service Fabric (Developer Reference)"

Build, operate, and orchestrate scalable microservices applications in the cloud    This book combines a comprehensive guide to success with Microsoft Azure Service Fabric and a practical catalog of design patterns and best practices for microservices design, implementation, and operation. Haishi Bai brings together all the information you’ll need to deliver scalable and reliable distributed microservices applications on Service Fabric. He thoroughly covers the crucial DevOps aspects of utilizing Service Fabric, reviews its interactions with key cloud-based services, and introduces essential service integration mechanisms such as messaging systems and reactive systems.    Leading Microsoft Azure expert Haishi Bai shows how to:  Set up your Service Fabric development environment  Program and deploy Service Fabric applications to a local or a cloud-based cluster  Compare and use stateful services, stateless services, and the actor model  Design Service Fabric applications to maximize availability, reliability, and scalability  Improve management efficiency via scripting  Configure network security and other advanced cluster settings  Collect diagnostic data, and use Azure Operational Management Suite to interpret it  Integrate microservices components developed in parallel  Use containers to mobilize applications for failover, replication, scaling, and load balancing  Streamline containerization with Docker in Linux and Windows environments  Orchestrate containers to schedule workloads and maintain services at desired states  Implement proven design patterns for common cloud application workloads  Balance throughput, latency, scalability, and cost 

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