Tuesday, September 24, 2019

Learning Docker (Free PDF)

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We have been fiddling with virtualization techniques and tools for quite a long time now in order to establish the much-demanded software portability. The inhibiting dependency factor between software and hardware needs to be decimated by leveraging virtualization, a kind of beneficial abstraction, through an additional layer of indirection. The idea is to run any software on any hardware. This is achieved by creating multiple virtual machines (VMs) out of a single physical server, with each VM having its own operating system (OS). Through this isolation, which is enacted through automated tools and controlled resource sharing, heterogeneous applications are accommodated in a physical machine.

With virtualization, IT infrastructures become open, programmable, remotely monitorable, manageable, and maintainable. Business workloads can be hosted in appropriately-sized virtual machines and delivered to the outside world, ensuring broader and more frequent utilization. On the other hand, for high-performance applications, virtual machines across multiple physical machines can be readily identified and rapidly combined to guarantee any kind of high-performance requirement.

The virtualization paradigm has its own drawbacks. Because of the verbosity and bloatedness (every VM carries its own operating system), VM provisioning typically takes a while, the performance goes down due to excessive usage of computational resources, and so on. Furthermore, the growing need for portability is not fully met by virtualization. Hypervisor software from different vendors comes in the way of ensuring application portability. Differences in the OS and application distributions, versions, editions, and patches hinder smooth portability. Computer virtualization has flourished, whereas the other, closely associated concepts of network and storage virtualization are just taking off. Building distributed applications through VM interactions invites and involves some practical difficulties.

Chapter 1: Getting Started with Docker
Chapter 2: Handling Docker Containers
Chapter 3: Building Images
Chapter 4: Publishing Images
Chapter 5: Running Your Private Docker Infrastructure
Chapter 6: Running Services in a Container
Chapter 7: Sharing Data with Containers
Chapter 8: Orchestrating Containers
Chapter 9: Testing with Docker
Chapter 10: Debugging Containers
Chapter 11: Securing Docker Containers

Author Details
"Pethuru Raj", PhD, works as a cloud architect at the IBM Global Cloud Center of Excellence (CoE) in Bangalore, India. He completed his CSIR-sponsored PhD degree at Anna University, Chennai, and continued his UGC-sponsored postdoctoral research at the Department of Computer Science and Automation of IISc, Bangalore.

"Jeeva S. Chelladhurai" has been working as a technical project manager at the IBM Global Cloud Center of Excellence (CoE) in India for the last 8 years. He has more than 18 years of experience in the IT industry.

"Vinod Singh" is a lead architect for IBM's cloud computing offerings. He has more than 18 years of experience in the cloud computing, networking, and data communication domains. Currently, he works for IBM's cloud application services and partner marketplace offerings.

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