Imagine that we have a simple structure of a client machine and a sever which are connected through the Internet. It is well-known how to show such structure with a deployment diagram.
Now I want to show that it is possible to have unlimited number of such clients and servers where each client has a possibility to be connected to each server. Moreover I want to show that each client machine has the same software client on it and each server has the same database scheme, but with one of different implementations (MySQL, Oracle, ...).
What the best and detailed way of model this with UML?
You can draw deployment diagram as depicted on picture below.
Communication path between nodes defines that many clients and many servers communicate with each other. (top part of diagram)
There are instances of nodes from top part of diagram to define that there are concrete instances of database server on your server machines. Internet is not node of deployment from this point of view. Internet is form of communication realization between nodes.
If it is needed to define deployed code on nodes, use artifacts.
See, the database server is node as well, but of execution environment type !
here is my diagram. I hope it will help you
Use instances of Components and Nodes:
The fact that each client can connect to any server could be shown as a simple note (pragmatic approach) or in some other diagram - collaboration for example (formal approach). If there is a dispatching algorithm in between, I sugest tha latter. If not, the note will be enough, as this is somehow expected.
I suggest to use a plain deployment diagram to show the dependencies
Related
I am in the process of analizing how to set up an OPCUA server in the cloud, and one of the challenges is data visibility. As data visibility, I mean that a user/customer can see certain data/devices that only belongs to him, and the same will apply to other users.
So the node creation process will depend on who the connected user is.
How can this be implemented in the best way according to OPCUA and specifically eclipse milo? Is it different namespaces for each customer? Any suggestion will be appreciated.
Different namespaces per customer would be an okay approach, but whether you do that or not you ultimately need to be examining the Session during the execution of Browse, Read, Write, and other services to determine which User is connected and what rights they have.
Here is the background:
We have a cluster (of 3) different services deployed on various containers (like Tomcat, TomEE, JBoss) etc. Each of the services does one thing. Like one service manages a common DB and provides REST services to CRUD the db. One service puts some data into a JMS Queue, Another service reads from the Queue and updates the DB. There is a client app that makes a REST service call to one of the service that sets off creating a row in the db, pushing that row into a queue etc.
Question: We need to implement the client app so that we know at any given point in time where the processing is. How do I implement this in RcJava 2/Java 9?
First, you need to determine what functionality in RxJava 2 will benefit you.
Coordination between asynchronous sources. Since you have a) event-driven requests from one side, and b) network queries on the other sides, this is a good fit so far.
Managing a stream of data, transforming and combining from one or more sources. You have given no indication that this is required.
Second, you need to determine what RxJava 2 does not provide:
Network connections. This is provided by your existing libraries.
Database management. Again, this is provided in your existing solutions.
Now, you have to decide whether the firstlies add up to something you can benefit from, given the up-front costs of learning a new library.
I m studying Microservices architecture and I m actually wondering something.
I m quite okay with the fact of using (back) service discovery to make request able on REST based microservices. I need to know where's the service (or at least the front of the server cluster) to make requests. So it make sense to be able to discover an ip:port in that case.
But I was wondering what could be the aim of using service registry / discovery when dealing with AMQP (based only, without HTTP possible calls) ?
I mean, using AMQP is just like "I need that, and I expect somebody to answer me", I dont have to know who's the server that sent me back the response.
So what is the aim of using service registry / discovery with AMQP based microservice ?
Thanks for your help
AMQP (any MOM, actually) provides a way for processes to communicate without having to mind about actual IP addresses, communication security, routing, among other concerns. That does not necessarily means that any process can trust or even has any information about the processes it communicates with.
Message queues do solve half of the process: how to reach the remote service. But they do not solve the other half: which service is the right one for me. In other words, which service:
has the resources I need
can be trusted (is hosted on a reliable server, has a satisfactory service implementation, is located in a country where the local laws are compatible with your requirements, etc)
charges what you want to pay (although people rarely discuss cost when it comes to microservices)
will be there during the whole time window needed to process your service -- keep in mind that servers are becoming more and more volatile. Some servers are actually containers that can last for a couple minutes.
Those two problems are almost linearly independent. To solve the second kind of problems, you have resource brokers in Grid computing. There is also resource allocation in order to make sure that the last item above is correctly managed.
There are some alternative strategies such as multicasting the intention to use a service and waiting for replies with offers. You may have reverse auction in such a case, for instance.
In short, the rule of thumb is that if you do not have an a priori knowledge about which service you are going to use (hardcoded or in some configuration file), your agent will have to negotiate, which includes dynamic service discovery.
I am trying to learn deployment topology and data centre topology for complex application. I know that answer to this question may vary depending on different scenarios. But I am talking about most probable and general case.
I browsed over the internet and came to know that complex large scale e-commerce J2EE applications are deployed on multiple application servers (e.g. weblogic cluster) and these weblogic application servers are connected to multiple data centres (where customer/application specific data is stored). I would like to know how these servers talk to multiple data centres (in terms of JDBC Connection and data source).
Also if there are multiple data centres then there is possibility of inconsistent data.
My knowledge about data centre is zero and would like to know more about how communication between application server and data centres takes place. In short I want to know typical production deployment topology along with data centers.
Thanks in advance.
This is a very complex and broad question that is open to interpretation. You might want to start with something like this to get enough information to ask more specific questions that are a better fit for Stack Overflow: http://www.javaworld.com/article/2077094/soa/construct-java-applications-through-distributed-object-technology.html
We're developing a server system in Scala + Akka for a game that will serve clients in Android, iPhone, and Second Life. There are parts of this server that need to be highly available, running on multiple machines. If one of those servers dies (of, say, hardware failure), the system needs to keep running. I think I want the clients to have a list of machines they will try to connect with, similar to how Cassandra works.
The multi-node examples I've seen so far with Akka seem to me to be centered around the idea of scalability, rather than high availability (at least with regard to hardware). The multi-node examples seem to always have a single point of failure. For example there are load balancers, but if I need to reboot one of the machines that have load balancers, my system will suffer some downtime.
Are there any examples that show this type of hardware fault tolerance for Akka? Or, do you have any thoughts on good ways to make this happen?
So far, the best answer I've been able to come up with is to study the Erlang OTP docs, meditate on them, and try to figure out how to put my system together using the building blocks available in Akka.
But if there are resources, examples, or ideas on how to share state between multiple machines in a way that if one of them goes down things keep running, I'd sure appreciate them, because I'm concerned I might be re-inventing the wheel here. Maybe there is a multi-node STM container that automatically keeps the shared state in sync across multiple nodes? Or maybe this is so easy to make that the documentation doesn't bother showing examples of how to do it, or perhaps I haven't been thorough enough in my research and experimentation yet. Any thoughts or ideas will be appreciated.
HA and load management is a very important aspect of scalability and is available as a part of the AkkaSource commercial offering.
If you're listing multiple potential hosts in your clients already, then those can effectively become load balancers.
You could offer a host suggestion service and recommends to the client which machine they should connect to (based on current load, or whatever), then the client can pin to that until the connection fails.
If the host suggestion service is not there, then the client can simply pick a random host from it internal list, trying them until it connects.
Ideally on first time start up, the client will connect to the host suggestion service and not only get directed to an appropriate host, but a list of other potential hosts as well. This list can routinely be updated every time the client connects.
If the host suggestion service is down on the clients first attempt (unlikely, but...) then you can pre-deploy a list of hosts in the client install so it can start immediately randomly selecting hosts from the very beginning if it has too.
Make sure that your list of hosts is actual host names, and not IPs, that give you more flexibility long term (i.e. you'll "always have" host1.example.com, host2.example.com... etc. even if you move infrastructure and change IPs).
You could take a look how RedDwarf and it's fork DimDwarf are built. They are both horizontally scalable crash-only game app servers and DimDwarf is partly written in Scala (new messaging functionality). Their approach and architecture should match your needs quite well :)
2 cents..
"how to share state between multiple machines in a way that if one of them goes down things keep running"
Don't share state between machines, instead partition state across machines. I don't know your domain so I don't know if this will work. But essentially if you assign certain aggregates ( in DDD terms ) to certain nodes, you can keep those aggregates in memory ( actor, agent, etc ) when they are being used. In order to do this you will need to use something like zookeeper to coordinate which nodes handle which aggregates. In the event of failure you can bring the aggregate up on a different node.
Further more, if you use an event sourcing model to build your aggregates, it becomes almost trivial to have real-time copies ( slaves ) of your aggregate on other nodes by those nodes listening for events and maintaining their own copies.
By using Akka, we get remoting between nodes almost for free. This means that which ever node handles a request that might need to interact with an Aggregate/Entity on another nodes can do so with RemoteActors.
What I have outlined here is very general but gives an approach to distributed fault-tolerance with Akka and ZooKeeper. It may or may not help. I hope it does.
All the best,
Andy