Insider's Guide to Cloud Computing, An [Paperback] Linthicum, David

Many cloud computing initiatives flat-out fail; others limp along, functioning tolerably without ever delivering what they promised. An Insider's Guide to Cloud Computing reveals why and shows how to do better. Cloud pioneer and long-time CTO David Linthicum explodes the industry's secrets and presents practical ways to optimize cloud for value and performance.

Linthicum takes a hard look at aggressively marketed technologies such as cloud-based AI, containers, no-code, serverless computing, and multicloud. He illuminates what works, what absolutely does not work, and how to manage the difficult cost-complexity tradeoffs presented by many offerings. You'll learn why some workloads and datasets still don't belong on the cloud, and even discover "game changer" technology that has actually been undersold.

Linthicum's seen it all: the tricks providers play to make their numbers at customers' expense…realities whispered about in conference rooms and spilled over drinks at conferences…facts and techniques you simply must know to deliver value-optimized solutions.

An Insider's Guide to Cloud Computing is for every technical and business decision-maker responsible for evaluating, planning, implementing, operating, or optimizing cloud systems. It offers exceptional value to professionals ranging from solution architects to cloud engineers, CTOs to enterprise consultants, or those just getting started on their cloud computing journey.

• What cloud providers don't tell you about their storage and compute services
• Cloud-based artificial intelligence and machine learning: What are you actually paying for?
• Containers, Kubernetes, and cloud-native development: truth versus hype
• Multicloud: Which approaches actually save you money?
• Real-world cloud security: beyond silos, black boxes, and out-of-control complexity
• Cloud computing, carbon footprints, and sustainability: reality versus fiction
• The crucial role of talent: how to identify, find, and keep the skills you need
• How cloud computing is changing―and how to prepare for what's coming

David Linthicum is on most top-10 lists of technology innovators and influencers, including cloud computing, edge computing, AI, and security technology. David is a best-selling author of more than 15 books and more than 7,000 published articles. He is also the originator of many business-related technology concepts, including enterprise application integration (EAI). He's an innovator within service-oriented architecture (SOA), and now cloud computing and the use of cloud computing for digital transformations.

With his remarkable ability to design, explain, and implement technology solutions to solve existing business problems and create new opportunities, David rose rapidly through the corporate ranks from programmer to CEO, with stops in between that helped inform his holistic view of enterprises. Based in Washington, DC, David currently serves Global 2,000 clients as Deloitte's Chief Cloud Strategy Officer, where he drives new innovations and market offerings, and leads people and projects, as well as thought leadership outreach. This includes on the "Deloitte On Cloud Podcast," as well as several Forbes and WSJ articles.

David's 60+ courses on LinkedIn Learning consistently appear on the "Popular Courses" list and provide course content on cloud computing, cloud architecture, cloud security, cloud governance, cloud operations, AI, DevOps, and many other concepts related to cloud computing and enterprise technology in general. He's also an adjunct professor for Louisiana State University (LSU), where he's created courses on DevOps, Cloud Computing, Cloud Architecture, and other courses that are in demand by the LSU student body. David has done over 1,000 conference presentations in the U.S. and abroad, often as a keynote speaker at conferences related to enterprise technology. He has hosted over 2,000 Webinars on the correct use of enterprise technology, including cloud computing, edge computing, AI, DevOps, and data science.