Containers all the way through…

In this post I will attempt to cover fundamentals of Bare Metal Systems, Virtual Systems and Container Systems. And the purpose for doing so is to learn about these systems as they stand and also the differences between them, focusing on how they execute programs in their respective environments.

Bare metal systems

Let’s think of our Bare Metal Systems as desktops and laptops we use on a daily basis (or even servers in server rooms and data-centers), and we have the following components:

• the hardware (outer physical layer)
• the OS platform (running inside the hardware)
• the programs running on the OS (as processes)

Programs are stored on the hard drive in the form of executable files (a format understandable by the OS) and loaded into memory via one or more processes. Programs interact with the kernel, which forms a core part of the OS architecture and the hardware. The OS coordinate communication between hardware i.e. CPU, I/O devices, Memory, etc… and the programs.

 

A more detailed explanation of what programs or executables are, how programs execute and where an Operating System come into play, can be found on this Stackoverflow page [2].

Virtual systems

On the other hand Virtual Systems, with the help of Virtual System controllers like, Virtual Box or VMWare or a hypervisor [1] run an operating system on a bare metal system. These systems emulate bare-metal hardware as software abstraction(s) inside which we run the real OS platform. Such systems can be made up of the following layers, and also referred to as a Virtual Machines (VM):

• a software abstraction of the hardware (Virtual Machine)
• the OS platform running inside the software abstraction (guest OS)
• one or more programs running in the guest OS (processes)

It’s like running a computer (abstracted as software) inside another computer. And the rest of the fundamentals from the Bare Metal System applies to this abstraction layer as well. When a process is created inside the Virtual System, then the host OS which runs the Virtual System might also be spawning one or more processes.

Container systems

Now looking at Container Systems we can say the following:

• they run on top of OS platforms running inside Bare Metal Systems or Virtual Systems
• containers which allow isolating processes and sharing the kernel between each other (such isolation from other processes and resources are possible in some OSes like say Linux, due to OS kernel features like cgroups[3] and namespaces)[4]

A container creates an OS like environment, inside which one or more programs can be executed. Each of these executions could result in a one or more processes on the host OS. Container Systems are composed of these layers:

• hardware (accessible via kernel features)
• the OS platform (shared kernel)
• one or more programs running inside the container (as processes)

Summary

Looking at these enclosures or rounded rectangles within each other, we can already see how it is containers all the way through.

There is an increasing number of distinctions between Bare Metal Systems, Virtual Systems and Container Systems. While Virtual Systems encapsulate the Operating System inside a thick hardware virtualisation, Container Systems do something similar but with a much thinner virtualisation layer.

There are a number of pros and cons between these systems when we look at them individually, i.e. portability, performance, resource consumption, time to recreate such systems, maintenance, et al.

Word of thanks and stay in touch

Thank you for your time, feel free to send your queries and comments to @theNeomatrix369. Big thanks to my colleague, and  our DevOps craftsman  Robert Firek from Codurance for proof-reading my post and steering me in the right direction.

Resources

• [1] Wikipedia page for Hypervisor
• [2] Stackoverflow page for “How does a program execute? Where does the operating systems come into play ?”
• [3] Wikipedia page on cgroups
• [4] Linux man page on namespaces

(Part 3 of 3): Synopsis of articles & videos on Performance tuning, JVM, GC in Java, Mechanical Sympathy, et al

This is a continuation of the previous post titled (Part 2 of 3): Synopsis of articles & videos on Performance tuning, JVM, GC in Java, Mechanical Sympathy, et al.

In our first review, The Atlassian guide to GC tuning is an extensive post covering the methodology and things to keep in mind when tuning GC, practical examples are given and references to important resources are also made in the process. The next one How NOT to measure latency by Gil Tene, he discusses some common pitfalls encountered in measuring and characterizing latency, demonstrating and discussing some false assumptions and measurement techniques that lead to dramatically incorrect reporting results, and covers simple ways to sanity check and correct these situations.  Finally Kirk Pepperdine in his post Poorly chosen Java HotSpot Garbage Collection Flags and how to fix them! throws light on some JVM flags – he starts with some 700 flags and boils it down to merely 7 flags. Also cautions you to not just draw conclusions or to take action in a whim but consult and examine – i.e. measure don’t guess!

….read more (reblogged from the Java Advent Calendar)

(Part 2 of 3): Synopsis of articles & videos on Performance tuning, JVM, GC in Java, Mechanical Sympathy, et al

This is a continuation of the previous post titled (Part 1 of 3): Synopsis of articles & videos on Performance tuning, JVM, GC in Java, Mechanical Sympathy, et al.

Without any further ado, lets get started with our next set of blogs and videos, chop…chop…! This time its Martin Thompson’s blog posts and talks. Martin’s first post on Java Garbage collection distilled basically distils the GC process and the underlying components including throwing light on a number of interesting GC flags (-XX:…). In his next talk he does his myth busting shaabang about mechanical sympathy, what people correctly believe in and the misconceptions. In the talk on performance testing, Martin takes its further and fuses Java, OS and the hardware to show how understanding of all these aspects can help write better programs.

Java Garbage Collection Distilled by Martin Thompson

There are too many flags to allow tuning the GC to achieve the throughput and latency your application requires. There’s plenty of documentation on the specifics of the bells and whistles around them but none to guide you through them.

….read more (reblogged from the Java Advent Calendar)

(Part 1 of 3): Synopsis of articles & videos on Performance tuning, JVM, GC in Java, Mechanical Sympathy, et al

I have been contemplating for a number of months about reviewing a cache of articles and videos on topics like Performance tuning, JVM, GC in Java, Mechanical Sympathy, etc… and finally took the time to do it – may be this was the point in my intellectual progress when was I required to do such a thing!

Thanks to Attila-Mihaly for giving me the opportunity to write a post for his yearly newsletter Java Advent Calendar, hence a review on various Java related topics fits the bill! The selection of videos and articles are purely random, and based on the order in which they came to my knowledge. My hidden agenda is to mainly go through them to understand and broaden my own knowledge at the same time share any insight with others along the way….read more (reblogged from the Java Advent Calendar)