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Practical Site Reliability Engineering

You're reading from   Practical Site Reliability Engineering Automate the process of designing, developing, and delivering highly reliable apps and services with SRE

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788839563
Length 390 pages
Edition 1st Edition
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Authors (3):
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Pethuru Raj Chelliah Pethuru Raj Chelliah
Author Profile Icon Pethuru Raj Chelliah
Pethuru Raj Chelliah
Shailender Singh Shailender Singh
Author Profile Icon Shailender Singh
Shailender Singh
Shreyash Naithani Shreyash Naithani
Author Profile Icon Shreyash Naithani
Shreyash Naithani
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Table of Contents (14) Chapters Close

Preface 1. Demystifying the Site Reliability Engineering Paradigm 2. Microservices Architecture and Containers FREE CHAPTER 3. Microservice Resiliency Patterns 4. DevOps as a Service 5. Container Cluster and Orchestration Platforms 6. Architectural and Design Patterns 7. Reliability Implementation Techniques 8. Realizing Reliable Systems - the Best Practices 9. Service Resiliency 10. Containers, Kubernetes, and Istio Monitoring 11. Post-Production Activities for Ensuring and Enhancing IT Reliability 12. Service Meshes and Container Orchestration Platforms 13. Other Books You May Enjoy

Summary


There are several activities being strategically planned and executed to enhance the resiliency, robustness, and versatility of enterprise, edge, and embedded IT. It is overwhelmingly accepted that the domains of data analytics and machine learning are going to be the key differentiators for corporations in fulfilling the varying expectations of their customers, clients, and consumers. This chapter has described the various post-production data analytics to allow you to gain a deeper understanding of applications, middleware solutions, databases, and IT infrastructures to manage them effectively and efficiently. Machine-learning algorithms enable the formation of self-learning models to predict problems and prescribe the viable solutions to surmount them. Thus, data analytics methods and ML algorithms come in handy in realizing resilient IT. The other important facets include static and dynamic code analyzes to proactively identify bugs in software code to enhance application reliability...

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