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Kief is a software delivery consultant with ThoughtWorks in London, specializing in tools, practices, and processes for the continuous delivery of software. Kief is a DZone MVB and is not an employee of DZone and has posted 19 posts at DZone. You can read more from them at their website. View Full User Profile

The Automated Server Management Lifecycle

02.13.2012
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One of the cornerstones of a well-automated infrastructure is a system for provisioning individual servers. A system that lets us reliably, quickly, and repeatably create new server instances that are consistent across our infrastructure means we spend less time fiddling with individual servers. Instead, servers become disposable components that are easily swapped, replaced, and expanded as we focus our attention on the bigger picture of the services we’re providing.

The first step in achieving this is making sure server instances are built using an automated process. This ensures every server is built the same way, that improvements can be easily folded into the server build process, and that it is a simple matter to spin up new instances and to scrap and replace broken ones. Automating this process also means your team of highly skilled, well-paid professionals don’t need to spend large amounts of their time on the brainless rote-work of menu-clicking through OS installation work.

I first used automated installation by PXE-booting physical rack servers in 2002, following the advice I found on the then-current infrastructures.org site, and in later years applied the same concepts with virtualized servers and then IaaS cloud instances.

The machine lifecycle

I think of this as the machine lifecycle (which I tend to call the ‘server lifecycle’ because that’s what I normally work with, although it’s just as applicable to desktops). This involves a number of activities required to set up and manage a single machine instance, such as partitioning storage, installing software, and applying configuration.

Basic Server Lifecycle phases

These activities are applied during one or more phases of the machine lifecyle. There are three phases: “Package Image”, “Provision Instance”, and “Update Instance”. There are a number of different strategies for deciding which activities to do in each phase.

The various activities may be applied during one or more phases, depending on the strategy used to manage the machine’s lifecycle. Some strategies carry out more activities during the packaging phase, for instance, while other approaches might have a simpler packaging phase but do more in the provisioning and/or updating phase.

Machine lifecycle phases

Image packaging phase

In the image packaging phase, some or all elements of a machine instance are pre-packaged into a machine image in a way that can be reused to create multiple running instances.

This could be as simple as using a bare OS installation CD or ISO from the vendor. Alternately, it could be a snapshot of a fully installed, fully configured runnable system, such as a Symantec Ghost image, VMWare template, or EC2 AMI. Either way, these images are maintained in a Machine Image Library for use in the instance provisioning phase.

With the ManualInstanceBuilding pattern, everything happens during provisioning

Different machine lifecycle strategies use different approaches to image packaging. ManualInstanceBuilding and ScriptedInstanceBuilding both tend to use stock OS images, which involves less up-front work and maintenance of the Machine Image Library, since the instances are take straight from the vendor. However, work is still needed to create, test, and maintain the checklists or scripts used to configure instances when provisioning.

On the other hand, CloningExistingMachineInstances and TemplatedMachineInstances both create pre-configured server images, which need only minor changes (e.g. hostnames and IP addresses) to provision new instances. This is appealing because less work is done to provision a new instance, but the drawback is that creating and updating images takes more work. Admins tend to make updates and fixes to running instances which may not make it into the templates, which contributes to ConfigurationDrift, especially if changes are made ad-hoc.

What happens in each phase with the TemplateMachineInstances pattern

CloningExistingMachineInstances, which usually takes the shape of copying an existing server to create new ones as needed, tends to make ConfigurationDrift worse, as new servers inherit the runtime cruft and debris (log files, temporary files, etc.) of their parents, and it is difficult to bring various servers into line with a single, consistent configuration. TemplatedMachineInstances are a better way to keep an infrastructure consistent and easily managed.

The tradeoffs between scripted installs vs. packaged images depends partly on the tools used for scripting and / or packaging, which in turn often depends on the hosting platform. Amazon AWS requires the use of templates (AMIs), for example. In either case, exploiting automation more fully in the provisioning phase favours the case for keeping the packaging phase as lightweight as possible.

Instance Provisioning Phase

In the provisioning phase, a machine instance is created from an image and prepared for operational use.

Examples of activities in this phase include instantiating a VM or cloud instance, preparing storage (partitioning disks, etc.), installing the OS, installing relevant software packages and system updates, and configuring the system and applications for use.

There are two main strategies for deciding which activities belong in the packaging versus the provisioning phases. One is RoleSpecificTemplates, and the other is GenericTemplate.

With RoleSpecificTemplates, the machine image library includes images that have been pre-packaged for specific roles, such as web server, application server, mail server, etc. These have the necessary software and configuration created in the packaging phase, so that provisioning is a simple matter of booting a new instance and tweaking a few configuration options. There are two drawbacks of this approach. Firstly, you will have more images to maintain, which creates more work. When the OS used for multiple roles is updated, for example, the images for all of those roles must be repackaged. Secondly, this pattern gives you less flexibility, since you can’t easily provision an instance that combines multiple roles, unless you create - and then maintain - images for every combination of roles that you might need.

What happens in each phase with the GenericTemplate pattern

With the GenericTemplate pattern, each image is kept generic, including only the software and configuration that is common to all roles. The role for each machine instance is assigned during the provisioning phase, and software and configuration are applied accordingly then. The goal is to minimise the number of images in the machine image library, to reduce the work needed to maintain them. Typically, a separate template is needed for each hardware and OS combination that can’t be supported from a single OS install. The JeOS (Just Enough Operation System) concept takes this to the extreme, making the base template as small as possible.

The GenericTemplate pattern does require a more robust automated configuration during provisioning, and may mean provisioning an instance takes longer than using more fully-built images, since more packages will need to be installed during install.

Instance Updating Phase

Once a machine instance is running and in use, it is continuously updated. This includes activities such as applying system and software updates, new configuration settings, user accounts, etc.

Many teams carry out these updates manually, however it requires a high level of discipline and organization to maintain systems this way, especially as the number of systems grows. The number of machines that a team can be managed is closely dependent on the size of the team, so the ration of servers to sysadmins is low. In practice, teams using manual updates tend to be reactive, updating machines opportunistically when carrying out other tasks, or in order to fix problems that crop up. This leads to ConfigurationDrift, with machines becoming increasingly inconsistent with one another, creating various problems including unreliable operation (software that works on one machine but not another), and extra work to troubleshoot and maintain.


Source:  http://kief.com/automated-server-management-lifecycle.html
Published at DZone with permission of Kief Morris, author and DZone MVB.

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