My view is that these kinds of frameworks should minimize their impact upon application code, and particularly should not do things that slow down the edit-execute cycle. Using plugins to substitute heavyweight components does a lot to help this process, which is vital for practices such as Test Driven Development. So the primary issue is for people who are writing code that expects to be used in applications outside of the control of the writer.
In these cases even a minimal assumption about a Service Locator is a problem. For service combination, you always have to have some convention in order to wire things together.
The advantage of injection is primarily that it requires very simple conventions - at least for the constructor and setter injections. You don't have to do anything odd in your component and it's fairly straightforward for an injector to get everything configured.
Interface injection is more invasive since you have to write a lot of interfaces to get things all sorted out. For a small set of interfaces required by the container, such as in Avalon's approach, this isn't too bad. But it's a lot of work for assembling components and dependencies, which is why the current crop of lightweight containers go with setter and constructor injection. The choice between setter and constructor injection is interesting as it mirrors a more general issue with object-oriented programming - should you fill fields in a constructor or with setters.
My long running default with objects is as much as possible, to create valid objects at construction time. Constructors with parameters give you a clear statement of what it means to create a valid object in an obvious place. If there's more than one way to do it, create multiple constructors that show the different combinations. Another advantage with constructor initialization is that it allows you to clearly hide any fields that are immutable by simply not providing a setter.
I think this is important - if something shouldn't change then the lack of a setter communicates this very well. If you use setters for initialization, then this can become a pain. Indeed in these situations I prefer to avoid the usual setting convention, I'd prefer a method like initFoo , to stress that it's something you should only do at birth.
But with any situation there are exceptions. If you have a lot of constructor parameters things can look messy, particularly in languages without keyword parameters. It's true that a long constructor is often a sign of an over-busy object that should be split, but there are cases when that's what you need.
If you have multiple ways to construct a valid object, it can be hard to show this through constructors, since constructors can only vary on the number and type of parameters. This is when Factory Methods come into play, these can use a combination of private constructors and setters to implement their work. The problem with classic Factory Methods for components assembly is that they are usually seen as static methods, and you can't have those on interfaces.
You can make a factory class, but then that just becomes another service instance. A factory service is often a good tactic, but you still have to instantiate the factory using one of the techniques here. Constructors also suffer if you have simple parameters such as strings.
With setter injection you can give each setter a name to indicate what the string is supposed to do. With constructors you are just relying on the position, which is harder to follow.
If you have multiple constructors and inheritance, then things can get particularly awkward. In order to initialize everything you have to provide constructors to forward to each superclass constructor, while also adding you own arguments. This can lead to an even bigger explosion of constructors. Despite the disadvantages my preference is to start with constructor injection, but be ready to switch to setter injection as soon as the problems I've outlined above start to become a problem.
This issue has led to a lot of debate between the various teams who provide dependency injectors as part of their frameworks. However it seems that most people who build these frameworks have realized that it's important to support both mechanisms, even if there's a preference for one of them.
A separate but often conflated issue is whether to use configuration files or code on an API to wire up services. For most applications that are likely to be deployed in many places, a separate configuration file usually makes most sense.
Almost all the time this will be an XML file, and this makes sense. However there are cases where it's easier to use program code to do the assembly. One case is where you have a simple application that's not got a lot of deployment variation. In this case a bit of code can be clearer than a separate XML file. A contrasting case is where the assembly is quite complex, involving conditional steps. Once you start getting close to programming language then XML starts breaking down and it's better to use a real language that has all the syntax to write a clear program.
You then write a builder class that does the assembly. If you have distinct builder scenarios you can provide several builder classes and use a simple configuration file to select between them. I often think that people are over-eager to define configuration files.
Often a programming language makes a straightforward and powerful configuration mechanism. Modern languages can easily compile small assemblers that can be used to assemble plugins for larger systems. If compilation is a pain, then there are scripting languages that can work well also. It's often said that configuration files shouldn't use a programing language because they need to be edited by non-programmers.
But how often is this the case? Do people really expect non-programmers to alter the transaction isolation levels of a complex server-side application? Non-language configuration files work well only to the extent they are simple.
If they become complex then it's time to think about using a proper programming language. One thing we're seeing in the Java world at the moment is a cacophony of configuration files, where every component has its own configuration files which are different to everyone else's. If you use a dozen of these components, you can easily end up with a dozen configuration files to keep in sync. My advice here is to always provide a way to do all configuration easily with a programmatic interface, and then treat a separate configuration file as an optional feature.
You can easily build configuration file handling to use the programmatic interface. If you are writing a component you then leave it up to your user whether to use the programmatic interface, your configuration file format, or to write their own custom configuration file format and tie it into the programmatic interface.
The important issue in all of this is to ensure that the configuration of services is separated from their use. Indeed this is a fundamental design principle that sits with the separation of interfaces from implementation. It's something we see within an object-oriented program when conditional logic decides which class to instantiate, and then future evaluations of that conditional are done through polymorphism rather than through duplicated conditional code. If this separation is useful within a single code base, it's especially vital when you're using foreign elements such as components and services.
The first question is whether you wish to defer the choice of implementation class to particular deployments. If so you need to use some implementation of plugin. Once you are using plugins then it's essential that the assembly of the plugins is done separately from the rest of the application so that you can substitute different configurations easily for different deployments.
How you achieve this is secondary. This configuration mechanism can either configure a service locator, or use injection to configure objects directly. In this article, I've concentrated on the basic issues of service configuration using Dependency Injection and Service Locator. There are some more topics that play into this which also deserve attention, but I haven't had time yet to dig into.
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As mentioned above, a guest machine can run on either a hosted hypervisor or a bare-metal hypervisor. There are some important differences between them. First off, a hosted virtualization hypervisor runs on the operating system of the host machine. The benefit of a hosted hypervisor is that the underlying hardware is less important. This results in better performance, scalability, and stability. The tradeoff here is that hardware compatibility is limited because the hypervisor can only have so many device drivers built into it.
Well, since the VM has a virtual operating system of its own, the hypervisor plays an essential role in providing the VMs with a platform to manage and execute this guest operating system. It allows for host computers to share their resources amongst the virtual machines that are running as guests on top of them. As you can see in the diagram, VMs package up the virtual hardware, a kernel i. OS and user space for each new VM. For all intent and purposes, containers look like a VM. For example, they have private space for processing, can execute commands as root, have a private network interface and IP address, allow custom routes and iptable rules, can mount file systems, and etc.
This diagram shows you that containers package up just the user space, and not the kernel or virtual hardware like a VM does. Each container gets its own isolated user space to allow multiple containers to run on a single host machine.
We can see that all the operating system level architecture is being shared across containers. The only parts that are created from scratch are the bins and libs.
This is what makes containers so lightweight. Docker is an open-source project based on Linux containers. It uses Linux Kernel features like namespaces and control groups to create containers on top of an operating system. Containers are far from new; Google has been using their own container technology for years. Ease of use: Docker has made it much easier for anyone — developers, systems admins, architects and others — to take advantage of containers in order to quickly build and test portable applications.
It allows anyone to package an application on their laptop, which in turn can run unmodified on any public cloud, private cloud, or even bare metal. Speed: Docker containers are very lightweight and fast. Since containers are just sandboxed environments running on the kernel, they take up fewer resources. You can create and run a Docker container in seconds, compared to VMs which might take longer because they have to boot up a full virtual operating system every time.
Docker Enterprise Edition is perhaps the best known commercial container management solution. It provides an integrated, tested and certified platform for apps running on enterprise Linux or Windows operating systems and cloud providers.
But there are many others, and several notable ones have a layer of proprietary software built around Kubernetes at the core. Examples of this type of management software product include:. But in the last couple of years a great deal of effort has been devoted to developing software to enhance the security of containers. For example, Docker and other container systems now include a signing infrastructure allowing administrators to sign container images to prevent untrusted containers from being deployed.
However, it is not necessarily the case that a trusted, signed container is secure to run, because vulnerabilities may be discovered in some of the software in the container after it has been signed. For that reason, Docker and others offer container security scanning solutions that can notify administrators if any container images have vulnerabilities that could be exploited. More specialized container security software has also been developed.
Another specialist container security company called Polyverse takes a different approach. It takes advantage of the fact that containers can be started in a fraction of a second to relaunch containerized applications in a known good state every few seconds to minimize the time that a hacker has to exploit an application running in a container.
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