Become a master Solutions Architect with this comprehensive guide, featuring cloud design patterns and real-world solutions for building scalable, secure, and highly available systems
Purchase of the print or Kindle book includes a free eBook in PDF format.
The second edition of AWS for Solutions Architects provides a practical guide to designing cloud solutions that align with industry best practices. This updated edition covers the AWS Well-Architected Framework, core design principles, and cloud-native patterns to help you build secure, high-performance, and cost-effective architectures.
Gain a deep understanding of AWS networking, hybrid cloud connectivity, and edge deployments. Explore big data processing with EMR, Glue, Kinesis, and MSK, enabling you to extract valuable insights from data efficiently. New chapters introduce CloudOps, machine learning, IoT, and blockchain, equipping you with the knowledge to develop modern cloud solutions.
Learn how to optimize AWS storage, implement containerization strategies, and design scalable data lakes. Whether working on simple configurations or complex enterprise architectures, this guide provides the expertise needed to solve real-world cloud challenges and build reliable, high-performing AWS solutions.
This book is for application and enterprise architects, developers, and operations engineers who want to become well versed with AWS architectural patterns, best practices, and advanced techniques to build scalable, secure, highly available, highly tolerant, and cost-effective solutions in the cloud. Existing AWS users are bound to learn the most, but it will also help those curious about how leveraging AWS can benefit their organization. Prior knowledge of any computing language is not needed, and there’s little to no code. Prior experience in software architecture design will prove helpful.
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Saurabh Shrivastava is a technology leader, author, inventor, and public speaker with over 18 years of experience in the IT industry. He currently works at Amazon Web Services (AWS) as a Global Solutions Architect Leader and enables global consulting partners and enterprise customers on their journey to the cloud. Saurabh led the AWS global technical partnerships, set his team's vision and execution model, and nurtured multiple new strategic initiatives. Saurabh has authored various blogs and whitepapers across a diverse range of technologies, such as big data, IoT, machine learning, and cloud computing. He is passionate about the latest innovations and their impact on our society and daily life. He holds a patent in cloud platform automation. Before AWS, Saurabh worked as an enterprise solution architect, software architect, and software engineering manager in Fortune 50 enterprises, start-ups, and global product and consulting organizations
Neelanjali Srivastav is a technology leader, product manager, agile coach, and cloud practitioner with over 16 years of experience in the software industry. She currently works at Amazon Web Services (AWS) as a Senior Product Manager and enables global customers on their data journey to the cloud. Neelanjali evangelizes and enables AWS customer and partners in AWS database, analytics, and machine learning services. She sets the product vision and cultivates new products in incubation. Before AWS, Neelanjali led teams of software engineers, solutions architects, and systems analysts to modernize IT systems and develop innovative software solutions for large enterprises. Neelanjali has held multiple roles in the IT services industry and R&D, focusing on enterprise application management, cloud service management, and orchestration.
Alberto Artasanchez is a solutions architect with expertise in the cloud, data solutions, and machine learning, with a career spanning over 28 years in various industries. He is an AWS Ambassador and publishes frequently in a variety of cloud and data science publications. He is often tapped as a speaker on topics including data science, big data, and analytics. He has a strong and extensive track record of designing and building end-to-end machine learning platforms at scale. He also has a long track record of leading data engineering teams and mentoring, coaching, and motivating them. He has a great understanding of how technology drives business value and has a passion for creating elegant solutions to complicated problems.
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