I'm starting to learn about google's firebase, seems really cool for real time applications. The auto-synced database seems very easy to use and I feel like diving into it.. I plan to start learning by building a simple checkers multiplayer game, but I still have an important question about it..
Firebase auto-syncs between users and devices using their 'magic' Database, which stores data and sends out to 'subscribers' of that db. Now what if I want to have some server processing of this data in between? For example, when a player makes a move, I want something that is not on client-side to make sure that is a valid move.. what would be the architecture to accomplish that?
Having a trusted process that sits between the users is a common scenario when using Firebase. Have a look at our classic blog post Where does Firebase fit in your app?, it would fit closest to pattern 2 there.
Typically you'll want to use the firebase-queue for this. Your users write their "requests" (probably moves in your case) into the queue, the server processes those and updates the actual board.
Another great thing about this is that it's easy to secure. The users can only write to the queue, while the server is the only one that can read the queue and update the board. A lot simpler to capture in security rules than many other approaches.
What is the standard pattern of orchestrating microservices?
If a microservice only knows about its own domain, but there is a flow of data that requires that multiple services interact in some manner, what's the way to go about it?
Let's say we have something like this:
Invoicing
Shipment
And for the sake of the argument, let's say that once an order has been shipped, the invoice should be created.
Somewhere, someone presses a button in a GUI, "I'm done, let's do this!"
In a classic monolith service architecture, I'd say that there is either an ESB handling this, or the Shipment service has knowledge of the invoice service and just calls that.
But what is the way people deal with this in this brave new world of microservices?
I do get that this could be considered highly opinion-based. but there is a concrete side to it, as microservices are not supposed to do the above.
So there has to be a "what should it by definition do instead", which is not opinion-based.
Shoot.
The Book Building Microservices describes in detail the styles mentioned by #RogerAlsing in his answer.
On page 43 under Orchestration vs Choreography the book says:
As we start to model more and more complex logic, we have to deal with
the problem of managing business processes that stretch across the
boundary of individual services. And with microservices, we’ll hit
this limit sooner than usual. [...] When it comes to actually
implementing this flow, there are two styles of architecture we could
follow. With orchestration, we rely on a central brain to guide and
drive the process, much like the conductor in an orchestra. With
choreography, we inform each part of the system of its job and let it
work out the details, like dancers all find‐ ing their way and
reacting to others around them in a ballet.
The book then proceeds to explain the two styles. The orchestration style corresponds more to the SOA idea of orchestration/task services, whereas the choreography style corresponds to the dumb pipes and smart endpoints mentioned in Martin Fowler's article.
Orchestration Style
Under this style, the book above mentions:
Let’s think about what an orchestration solution would look like for
this flow. Here, probably the simplest thing to do would be to have
our customer service act as the central brain. On creation, it talks
to the loyalty points bank, email service, and postal service [...],
through a series of request/response calls. The
customer service itself can then track where a customer is in this
process. It can check to see if the customer’s account has been set
up, or the email sent, or the post delivered. We get to take the
flowchart [...] and model it directly into code. We could even use
tooling that implements this for us, perhaps using an appropriate
rules engine. Commercial tools exist for this very purpose in the form
of business process modeling software. Assuming we use synchronous
request/response, we could even know if each stage has worked [...]
The downside to this orchestration approach is that the customer
service can become too much of a central governing authority. It can
become the hub in the middle of a web and a central point where logic
starts to live. I have seen this approach result in a small number of
smart “god” services telling anemic CRUD-based services what to do.
Note: I suppose that when the author mentions tooling he's referring to something like BPM (e.g. Activity, Apache ODE, Camunda). As a matter of fact, the Workflow Patterns Website has an awesome set of patterns to do this kind of orchestration and it also offers evaluation details of different vendor tools that help to implement it this way. I don't think the author implies one is required to use one of these tools to implement this style of integration though, other lightweight orchestration frameworks could be used e.g. Spring Integration, Apache Camel or Mule ESB
However, other books I've read on the topic of Microservices and in general the majority of articles I've found in the web seem to disfavor this approach of orchestration and instead suggest using the next one.
Choreography Style
Under choreography style the author says:
With a choreographed approach, we could instead just have the customer
service emit an event in an asynchronous manner, saying Customer
created. The email service, postal service, and loyalty points bank
then just subscribe to these events and react accordingly [...]
This approach is significantly more decoupled. If some
other service needed to reach to the creation of a customer, it just
needs to subscribe to the events and do its job when needed. The
downside is that the explicit view of the business process we see in
[the workflow] is now only implicitly reflected in our system [...]
This means additional work is needed to ensure that you can monitor
and track that the right things have happened. For example, would you
know if the loyalty points bank had a bug and for some reason didn’t
set up the correct account? One approach I like for dealing with this
is to build a monitoring system that explicitly matches the view of
the business process in [the workflow], but then tracks what each of
the services do as independent entities, letting you see odd
exceptions mapped onto the more explicit process flow. The [flowchart]
[...] isn’t the driving force, but just one lens through
which we can see how the system is behaving. In general, I have found
that systems that tend more toward the choreographed approach are more
loosely coupled, and are more flexible and amenable to change. You do
need to do extra work to monitor and track the processes across system
boundaries, however. I have found most heavily orchestrated
implementations to be extremely brittle, with a higher cost of change.
With that in mind, I strongly prefer aiming for a choreographed
system, where each service is smart enough to understand its role in
the whole dance.
Note: To this day I'm still not sure if choreography is just another name for event-driven architecture (EDA), but if EDA is just one way to do it, what are the other ways? (Also see What do you mean by "Event-Driven"? and The Meanings of Event-Driven Architecture). Also, it seems that things like CQRS and EventSourcing resonate a lot with this architectural style, right?
Now, after this comes the fun. The Microservices book does not assume microservices are going to be implemented with REST. As a matter of fact in the next section in the book, they proceed to consider RPC and SOA-based solutions and finally REST. An important point here is that Microservices does not imply REST.
So, What About HATEOAS? (Hypermedia as the Engine of Application State)
Now, if we want to follow the RESTful approach we cannot ignore HATEOAS or Roy Fielding will be very much pleased to say in his blog that our solution is not truly REST. See his blog post on REST API Must be Hypertext Driven:
I am getting frustrated by the number of people calling any HTTP-based
interface a REST API. What needs to be done to make the REST
architectural style clear on the notion that hypertext is a
constraint? In other words, if the engine of application state (and
hence the API) is not being driven by hypertext, then it cannot be
RESTful and cannot be a REST API. Period. Is there some broken manual
somewhere that needs to be fixed?
So, as you can see, Fielding thinks that without HATEOAS you are not truly building RESTful applications. For Fielding, HATEOAS is the way to go when it comes to orchestrating services. I am just learning all this, but to me, HATEOAS does not clearly define who or what is the driving force behind actually following the links. In a UI that could be the user, but in computer-to-computer interactions, I suppose that needs to be done by a higher level service.
According to HATEOAS, the only link the API consumer truly needs to know is the one that initiates the communication with the server (e.g. POST /order). From this point on, REST is going to conduct the flow, because, in the response of this endpoint, the resource returned will contain the links to the next possible states. The API consumer then decides what link to follow and move the application to the next state.
Despite how cool that sounds, the client still needs to know if the link must be POSTed, PUTed, GETed, PATCHed, etc. And the client still needs to decide what payload to pass. The client still needs to be aware of what to do if that fails (retry, compensate, cancel, etc.).
I am fairly new to all this, but for me, from HATEOAs perspective, this client, or API consumer is a high order service. If we think it from the perspective of a human, you can imagine an end-user on a web page, deciding what links to follow, but still, the programmer of the web page had to decide what method to use to invoke the links, and what payload to pass. So, to my point, in a computer-to-computer interaction, the computer takes the role of the end-user. Once more this is what we call an orchestrations service.
I suppose we can use HATEOAS with either orchestration or choreography.
The API Gateway Pattern
Another interesting pattern is suggested by Chris Richardson who also proposed what he called an API Gateway Pattern.
In a monolithic architecture, clients of the application, such as web
browsers and native applications, make HTTP requests via a load
balancer to one of N identical instances of the application. But in a
microservice architecture, the monolith has been replaced by a
collection of services. Consequently, a key question we need to answer
is what do the clients interact with?
An application client, such as a native mobile application, could make
RESTful HTTP requests to the individual services [...] On the surface
this might seem attractive. However, there is likely to be a
significant mismatch in granularity between the APIs of the individual
services and data required by the clients. For example, displaying one
web page could potentially require calls to large numbers of services.
Amazon.com, for example,
describes how some
pages require calls to 100+ services. Making that many requests, even
over a high-speed internet connection, let alone a lower-bandwidth,
higher-latency mobile network, would be very inefficient and result in
a poor user experience.
A much better approach is for clients to make a small number of
requests per-page, perhaps as few as one, over the Internet to a
front-end server known as an API gateway.
The API gateway sits between the application’s clients and the
microservices. It provides APIs that are tailored to the client. The
API gateway provides a coarse-grained API to mobile clients and a
finer-grained API to desktop clients that use a high-performance
network. In this example, the desktop clients make multiple requests
to retrieve information about a product, whereas a mobile client
makes a single request.
The API gateway handles incoming requests by making requests to some
number of microservices over the high-performance LAN. Netflix, for
example,
describes
how each request fans out to on average six backend services. In this
example, fine-grained requests from a desktop client are simply
proxied to the corresponding service, whereas each coarse-grained
request from a mobile client is handled by aggregating the results of
calling multiple services.
Not only does the API gateway optimize communication between clients
and the application, but it also encapsulates the details of the
microservices. This enables the microservices to evolve without
impacting the clients. For example, two microservices might be
merged. Another microservice might be partitioned into two or more
services. Only the API gateway needs to be updated to reflect these
changes. The clients are unaffected.
Now that we have looked at how the API gateway mediates between the
application and its clients, let’s now look at how to implement
communication between microservices.
This sounds pretty similar to the orchestration style mentioned above, just with a slightly different intent, in this case, it seems to be all about performance and simplification of interactions.
Trying to aggregate the different approaches here.
Domain Events
The dominant approach for this seems to be using domain events, where each service publish events regarding what have happened and other services can subscribe to those events.
This seems to go hand in hand with the concept of smart endpoints, dumb pipes that is described by Martin Fowler here: http://martinfowler.com/articles/microservices.html#SmartEndpointsAndDumbPipes
Proxy
Another apporach that seems common is to wrap the business flow in its own service.
Where the proxy orchestrates the interaction between the microservices like shown in the below picture:
.
Other patterns of the composition
This page contains various composition patterns.
So, how is orchestration of microservices different from orchestration of old SOA services that are not “micro”? Not much at all.
Microservices usually communicate using http (REST) or messaging/events. Orchestration is often associated with orchestration platforms that allow you to create a scripted interaction among services to automate workflows. In the old SOA days, these platforms used WS-BPEL. Today's tools don't use BPEL. Examples of modern orchestration products: Netflix Conductor, Camunda, Zeebe, Azure Logic Apps, Baker.
Keep in mind that orchestration is a compound pattern that offers several capabilities to create complex compositions of services. Microservices are more often seen as services that should not participate in complex compositions and rather be more autonomous.
I can see a microservice being invoked in an orchestrated workflow to do some simple processing, but I don’t see a microservice being the orchestrator service, which often uses mechanisms such as compensating transactions and state repository (dehydration).
So you're having two services:
Invoice micro service
Shipment micro service
In real life, you would have something where you hold the order state. Let's call it order service. Next you have order processing use cases, which know what to do when the order transitions from one state to another. All these services contain a certain set of data, and now you need something else, that does all the coordination. This might be:
A simple GUI knowing all your services and implementing the use cases ("I'm done" calls the shipment service)
A business process engine, which waits for an "I'm done" event. This engine implements the use cases and the flow.
An orchestration micro service, let's say the order processing service itself that knows the flow/use cases of your domain
Anything else I did not think about yet
The main point with this is that the control is external. This is because all your application components are individual building blocks, loosely coupled. If your use cases change, you have to alter one component in one place, which is the orchestration component. If you add a different order flow, you can easily add another orchestrator that does not interfere with the first one. The micro service thinking is not only about scalability and doing fancy REST API's but also about a clear structure, reduced dependencies between components and reuse of common data and functionality that are shared throughout your business.
HTH, Mark
If the State needs to be managed then the Event Sourcing with CQRS is the ideal way of communication. Else, an Asynchronous messaging system (AMQP) can be used for inter microservice communication.
From your question, it is clear that the ES with CQRS should be the right mix. If using java, take a look at Axon framework. Or build a custom solution using Kafka or RabbitMQ.
You can implement orchestration by using spring State machine model.
Steps
Add below dependency to your project ( if you are using Maven)
<dependency>
<groupId>org.springframework.statemachine</groupId>
<artifactId>spring-statemachine-core</artifactId>
<version>2.2.0.RELEASE</version>
</dependency>
Define states and events e.g. State 1, State 2 and Event 1 and Event 2
Provide state machine implementation in buildMachine() method.
configureStates
configureTransitions
Send events to state machine
Refer to documentation page for complete code
i have written few posts on this topic:
Maybe these posts can also help:
API Gateway pattern - Course-grained api vs fine-grained apis
https://www.linkedin.com/pulse/api-gateway-pattern-ronen-hamias/
https://www.linkedin.com/pulse/successfulapi-ronen-hamias/
Coarse-grained vs Fine-grained service API
By definition a coarse-grained service operation has broader scope than a fine-grained service, although the terms are relative. coarse-grained increased design complexity but can reduce the number of calls required to complete a task. at micro-services architecture coarse-grained may reside at the API Gateway layer and orchestrate several micro-services to complete specific business operation. coarse-grained APIs needs to be carefully designed as involving several micro-services that managing different domain of expertise has a risk to mix-concerns in single API and breaking the rules described above. coarse-grained APIs may suggest new level of granularity for business functions that where not exist otherwise. for example hire employee may involve two microservices calls to HR system to create employee ID and another call to LDAP system to create a user account. alternatively client may have performed two fine-grained API calls to achieve the same task. while coarse-grained represents business use-case create user account, fine-grained API represent the capabilities involved in such task. further more fine-grained API may involve different technologies and communication protocols while coarse-grained abstract them into unified flow. when designing a system consider both as again there is no golden approach that solve everything and there is trad-off for each. Coarse-grained are particularly suited as services to be consumed in other Business contexts, such as other applications, line of business or even by other organizations across the own Enterprise boundaries (typical B2B scenarios).
the answer to the original question is SAGA pattern.
I'm designing a database monitoring application. Basically, the database will be hosted in the cloud and record-level access to it will be provided via custom written clients for Windows, iOS, Android etc. The basic scenario can be implemented via web services (ASP.NET WebAPI). For example, the client will make a GET request to the web service to fetch an entry. However, one of the requirements is that the client should automatically refresh UI, in case another user (using a different instance of the client) updates the same record AND the auto-refresh needs to happen under a second of record being updated - so that info is always up-to-date.
Polling could be an option but the active clients could number in hundreds of thousands, so I'm looking for a more robust and lightweight (on server) solution. I'm versed in .NET and C++/Windows and I could roll-out a complete solution in C++/Windows using IO Completion Ports but feel like that would be an overkill and require too much development time. Looked into ASP.NET WebAPI but not being able to send out notifications is its limitation. Are there any frameworks/technologies in Windows ecosystem that can address this scenario and scale easily as well? Any good options outside windows ecosystem e.g. node.js?
You did not specify a database that can be used so if you are able to use MSSQL Server, you may want to lookup SQL Dependency feature. IF configured and used correctly, you will be notified if there are any changes in the database.
Pair this with SignalR or any real-time front-end framework of your choice and you'll have real-time updates as you described.
One catch though is that SQL Dependency only tells you that something changed. Whatever it was, you are responsible to track which record it is. That adds an extra layer of difficulty but is much better than polling.
You may want to search through the sqldependency tag here at SO to go from here to where you want your app to be.
My first thought was to have webservice call that "stays alive" or the html5 protocol called WebSockets. You can maintain lots of connections but hundreds of thousands seems too large. Therefore the webservice needs to have a way to contact the clients with stateless connections. So build a webservice in the client that the webservices server can communicate with. This may be an issue due to firewall issues.
If firewalls are not an issue then you may not need a webservice in the client. You can instead implement a server socket on the client.
For mobile clients, if implementing a server socket is not a possibility then use push notifications. Perhaps look at https://stackoverflow.com/a/6676586/4350148 for a similar issue.
Finally you may want to consider a content delivery network.
One last point is that hopefully you don't need to contact all 100000 users within 1 second. I am assuming that with so many users you have quite a few servers.
Take a look at Maximum concurrent Socket.IO connections regarding the max number of open websocket connections;
Also consider whether your estimate of on the order of 100000 of simultaneous users is accurate.
I want to use Azure table to store data which is posted by users. And whenever a user post something to some other user it should give out a notification to this user. I have looked into Comet solution with PokeIn to see if there are a way for it. As I'm new to this technique I would like to know the approach before writing the code.
My though to tackle this problem so far is that you can make reverse ajax call to the server. And then at the server it will continuously check the database, with a while-loop, if something has changed. A sleep will be put so it won't overload the server. However this would introduce a lot of unnecessary checks to the database. I have asked a question here earlier, about how to do long polling. And one of the answer suggested to use SqlDependency. However this is MS SQL specific. I want to know how to do it in Azure tables, if it is possible.
Any comments or answer to the general approach would be much appreciated.
I am answering this question based on your question essentially posted first paragraph in which how to use Windows Azure Tables (Without any Database) to write such solution (fellow SO professionals may have different approach). Windows Azure table essentially are key value pair database so there are no such functionality as SQLDependency.
As first approach, with Windows Azure Tables and Windows Azure Queues you can create such solution. When you write something to Azure Tables, you post a message to Azure Queue. In a separate thread you can keep checking for queue state and once there is a message you can take necessary action. The drawback to this approach is that you would need to constantly peeking the queue and depend on how aggressive you are in your polling, it will add transaction cost (about 10,000 for $0.001) but aggressive checking will adds up a lot quickly.
Another solution is to use Windows Azure Table and Service Bus. With Service bus you don't need to use poll instead you can develop a solution in which you will be notified when there is an update to your tables and then rest you can take care.
I have seen both the solution implemented by users and depend on application usability the cost varies so does coding complexity. Before choosing Windows Azure Queue or Service Bus, i would suggest reading the article below to understand the differences in between two to make better decision:
Windows Azure Queues and Windows Azure Service Bus Queues - Compared and Contrasted
Most if not all of the NSB examples for ASP.NET (or MVC) have the web application sending a message using Bus.Send and possibly registering for a simple callback, which is essentially how I'm using it in my application.
What I'm wondering is if it's possible and/or makes any sense to handle messages in the same ASP.NET application.
The main reason I'm asking is caching. The process might go something like this:
User initiates a request from the web app.
Web app sends a message to a standalone app server, and logs the change in a local database.
On future page requests from the same user, the web app is aware of the change and lists it in a "pending" status.
A bunch of stuff happens on the back-end and eventually the requests gets approved or rejected. An event is published referencing the original request.
At this point, the web app should start displaying the most recent information.
Now, in a real web app, it's almost a sure thing that this pending request is going to be cached, quite possibly for a long period of time, because otherwise the app has to query the database for pending changes every time the user asks for the current info.
So when the request finally completes on the back-end - which might take a minute or a day - the web app needs, at a minimum, to invalidate this cache entry and do another DB lookup.
Now I realize that this can be managed with SqlDependency objects and so on, but let's assume that they aren't available - perhaps it's not a SQL Server back-end or perhaps the current-info query goes to a web service, whatever. The question is, how does the web app become aware of the change in status?
If it is possible to handle NServiceBus messages in an ASP.NET application, what is the context of the handler? In other words, the IoC container is going to have to inject a bunch of dependencies, but what is their scope? Does this all execute in the context of an HTTP request? Or does everything need to be static/singleton for the message handler?
Is there a better/recommended approach to this type of problem?
I've wondered the same thing myself - what's an appropriate level of coupling for a web app with the NServiceBus infrastructure? In my domain, I have a similar problem to solve involving the use of SignalR in place of a cache. Like you, I've not found a lot of documentation about this particular pattern. However, I think it's possible to reason through some of the implications of following it, then decide if it makes sense in your environment.
In short, I would say that I believe it is entirely possible to have a web application subscribe to NServiceBus events. I don't think there would be any technical roadblocks, though I have to confess I have not actually tried it - if you have the time, by all means give it a shot. I just get the strong feeling that if one starts needing to do this, then there is probably a better overall design waiting to be discovered. Here's why I think this is so:
A relevant question to ask relates to your cache implementation. If it's a distributed or centralized model (think SQL, MongoDB, Memcached, etc), then the approach that #Adam Fyles suggests sounds like a good idea. You wouldn't need to notify every web application - updating your cache can be done by a single NServiceBus endpoint that's not part of your web application. In other words, every instance of your web application and the "cache-update" endpoint would access the same shared cache. If your cache is in-process however, like Microsoft's Web Cache, then of course you are left with a much trickier problem to solve unless you can lean on Eventual Consistency as was suggested.
If your web app subscribes to a particular NServiceBus event, then it becomes necessary for you to have a unique input queue for each instance of your web app. Since it's best practice to consider scale-out of your web app using a load balancer, that means that you could end up with N queues and at least N subscriptions, which is more to worry about than a constant number of subscriptions. Again, not a technical roadblock, just something that would make me raise an eyebrow.
The David Boike article that was linked raises an interesting point about app pools and how their lifetimes might be uncertain. Also, if you have multiple app pools running simultaneously for the same application on a server (a common scenario), they will all be trying to read from the same message queue, and there's no good way to determine which one will actually handle the message. More of then than not, that will matter. Sending commands, in contrast, does not require an input queue according to this post by Udi Dahan. This is why I think one-way commands sent by web apps are much more commonly seen in practice.
There's a lot to be said for the Single Responsibility Principle here. In general, I would say that if you can delegate the "expertise" of sending and receiving messages to an NServiceBus Host as much as possible, your overall architecture will be cleaner and more manageable. Through experience, I've found that if I treat my web farm as a single entity, i.e. strip away all acknowledgement of individual web server identity, that I tend to have less to worry about. Having each web server be an endpoint on the bus kind of breaks that notion, because now "which server" comes up again in the form of message queues.
Does this help clarify things?
An endpoint(NSB) can be created to subscribe to the published event and update the cache. The event shouldn't be published until the actual update is made so you don't get out of sync. The web app would continue to pull data from the cache on the next request, or you can build in some kind of delay.