I'm developing n-layer architecture, and for the data access layer I am using Entity Framework 4.1.
The database oonly expose stored procedures. I also have an additional layer, service layer, developed in WCF.
For each service call, use a new data context in a using statement.
Considering that service calls will reach 1000 per second, this approach is right?
Best Regards.
1000 per second - if your service really has to do something you will need either very good server or load balanced environment.
If your database exposes only stored procedures and you cannot execute direct SQL (= you cannot use LINQ) there is no reason to use EF. Actually there are many reason why you should not because it will not give you any additional value except much worse performance. Also if your stored procedures use for example multiple result sets, table value parameters and some other advanced techniques you will not be able to use them from EF 4.1 at all.
Using direct ADO.NET will allow you executing queries asynchronously which can lead to asynchronous WCF service operations = better utilization of your computing power and better throughput.
You should worry more about server load balancing , sclability , WCF performance issues including but not limited to concurrency , thorottling . You should chose binding that can scale easily as per your need with minium breakdown time in future.
Additionally,You should make sure that you are doing a good multithreaded design on your backend to support your benchmark of 1000 calls/sec ( I am still wondering what it is though) and to increase throughput of your service.
EF doesnt play any part in your case . You need raw performance here . Dont kill by adding another layer of unnecessary stuff.
For load balancing you can start here Loadbalancing
Related
A simple question about scalability. I have been studying about scalability and I think I understand the basic concept behind it. You use an orchestrator like Kubernetes to manage the automatic scalability of a system. So in that way, as a particular microservice gets an increase demand of calls, the orchestrator will create new instances of it, to deal with the requirement of the demand. Now, in our case, we are building a microservice structure similar to the example one at Microsoft's "eShop On Containers":
Now, here each microservice has its own database to manage just like in our application. My question is: When upscaling this system, by creating new instances of a certain microservice, let's say "Ordering microservice" in the example above, wouldn't that create a new set of databases? In the case of our application, we are using SQLite, so each microservice has its own copy of the database. I would asume that in order to be able to upscale such a system would require that each microservice connects to an external SQL Server. But if that was the case, wouldn't that be a bottle neck? I mean, having multiple instances of a microservice to attend more demand of a particular service BUT with all those instances still accessing a single database server?
In the case of our application, we are using SQLite, so each microservice has its own copy of the database.
One of the most important aspects of services that scale-out is that they are stateless - services on Kubernetes should be designed according to the 12-factor principles. This means that service-instances cannot have its own copy of the database, unless it is a cache.
I would asume that in order to be able to upscale such a system would require that each microservice connects to an external SQL Server.
yes, if you want to be able to scale-out, you need to use a database that are outside the instances and shared between the instances.
But if that was the case, wouldn't that be a bottle neck?
This depend very much on how you design your system. Comparing microservices to monoliths; when using a monolith, the whole thing typically used one big database, but with microservices it is easier to use multiple different databases, so it should be much easier to scale-out the database this way.
I mean, having multiple instances of a microservice to attend more demand of a particular service BUT with all those instances still accessing a single database server?
There are many ways to scale a database system as well, e.g. caching read-operations (but be careful). But this is a large topic in itself and depends very much on what and how you do things.
I'm creating a microservice architecture with Core, rabbitMQ, strangler pattern ... but I have to use an existing SQL database (Transaction requeriment).
Doing a research I don't found a lot of information about how implement SQL database, but I think it's impossible to do a transactional operation on different services at the same time.
1- Every service must have access to entirely database?
2- Is a good idea do a service exclusive to do transactionals operations?
3- SQL with microservices it's maybe too much slow?
I don't know if exist a standard for this.
Thanks.
The whole point of microservices is about having small, independent services that are decoupled as much as possible.
Sharing a common database introduces very strong coupling, and is not recommended.
If two services need the same data, you could either (a) have a different database for each, and replicate the data, or (b) introduce a third service that is responsible for access to the database.
If you're looking for a bigger-scale distributed transaction across microservices, then you should look into things like sagas. Typically you'll have a coordinator ("process manager" in some literature) that tracks the various operations, and can compensate or cancel actions that have been performed if the transaction as a whole is bound to fail.
3- SQL with microservices it's maybe too much slow?
What makes you think so?
There is nothing about SQL that makes it inadequate for microservices. Microservices may vary wildly in terms of what they do and what they require. SQL will be perfectly suitable for some microservices, and possibly not so suitable for others. It depends on the service.
It look like you need a distributed transactions in your system
https://msdn.microsoft.com/en-us/library/windows/desktop/ms681205(v=vs.85).aspx
Also there is a nice book devoted to microservices. It includes distributed transactions and other patters used in microservice bases apps.
http://shop.oreilly.com/product/0636920033158.do
1- Every service must have access to entirely database?
No. A microservice has its own schema related to the Aggregate Root / Service that it offers. If a service needs data of another entity, it invokes the APIs provided by another micro service.
2- Is a good idea do a service exclusive to do transactionals
operations?
No. Each microservice is a transaction boundary in its own right. Distributed transactions, particularly using 2PC, do not perform particularly well.
3- SQL with microservices it's maybe too much slow?
I am not totally clear as to why you make such a statement.
I'm currently working in a Silverlight / MS SQL project where the Entity Framework has not been implemented and I would like to know what's the best practice to deal with calculated fields in this particular situation.
Considering that some external system might also consume my data directly in the DB or thru a web service, here's the 3 options I can see right now.
1) Force any external system to consume data thru a web service and create all the calculated fields in the objects only.
2) Create the calculated fields in a DB view and resync your object with the server each time a value needs to be calculated.
3) Replicate the calculation rules in the object and the database view.
Any other suggestions would also be welcomed.
I would recommend to follow two principles: data decoupling and minimum functionality duplication. Both would suggest to put your calculations in one place only, and serve them already calculated. So I would implement the calculations in the DB, and serve them via a web service.
However, you have to consider your particular case. For example, if the calculations are VERY heavy, you could delegate them to the client to spare server resources. This could even be the reason you are using Silverlight. I am in a similar situation on a project, and I found that the best compromise is to push raw data to the client and have it do the heavy computations.
Having a best practice or approach for this kind of problem is difficult as circumstances change what was formerly a good approach might start to seem less useful. That said where possible I would do anything data related at the DB level including calculated fields. This way you know no matter where you are looking at the data from you will see the same results. So your web service, SQL reporting and anything else that needs to look at or receive data will see the same result.
We've got a smart client that talks to a SQL Server database via WCF, displaying the entities in the database, and allowing the user to edit those entities.
Some of the WCF calls return a large data set. Since this data set doesn't change very often, I'm considering some sort of write-through cache on the client, and only getting the deltas from the WCF service.
That is: the client both reads from the service and writes to the service.
I'm not looking for disconnected/offline operation, but since the majority of the data doesn't change very often, I'd probably implement this with a local data store.
I don't want the local store to get too stale, and I don't think I'm too concerned about conflict resolution, because updates will always go straight to the WCF service -- think of it as a write-through cache.
Would Microsoft's Sync Framework be good for this? Could I use a local SQL-CE cache and perform the updates over WCF? The service end has a SQL Server 2005/2008 backend, but I don't want to talk to it directly. Does Sync Framework integrate well with WCF?
Are there other solutions out there? Should I roll something myself?
I don't think you have to couple it to WCF at all. FeedSync allows you to publish directly to an RSS feed.
The only that I'm not too sure about is if it would be suitable for a "large dataset" though. Since you don't need two way replication, if your dataset is extremely large, you might want to write your own WCF implementation to optimize it; especially for the initial population.
Ok, I have a pretty complex silverlight app that gets its data from a WCF service (asp.net hosted service layer) which in turn calls into a data layer that calls stored procedures in a SQL 2005 DB to extract the needed data. So the round trip goes like this:
Silverlight App --> WCF Service --> Data Layer --> DB --> Data Layer --> WCF Service transforms Data Entity into corresponding DTO (Data Transfer Object) or List<> thereof --> Silverlight App
Much of the data is highly relational (so it needs to exist in the DB), but it will change infrequently. It seems that I have several choices of locations to cache this "semi-constant" data:
I can cache it in the data layer. My data layer is already set up to use the SQLDependency class and cache the results from a stored procedure call. I think that this is or can be an application level cache.
I can cache the resulting DTO in an application level (or session level depending on the call) cache within the WCF service itself.
2(a) I could even take this a step further by serializing the XML for the resulting DTO(s) into a file on the WCF service side so that I could (a) check memory cache, then (b) check file cache and (c) hit the data layer
I could do something similar to 2(a) with isolated storage on the client side within the SL app. I could serialize the data to the local isolated storage with a hash (or a moddate or something) and then just make a call to check that.
One more thing to add: I am hosting this WCF service in IIS7 with dynamic compression turned on so that the (often very large and easily compressed) XML response gets gzip-ed. Ideally, it would seem, I would like IIS to cache this gzip-ed result to avoid all the extra processing. I think that it may do this already but I am not sure.
I am pretty sure that the final answer to this is some flavor of "it depends", but I would love to hear how others are approaching this. A good tactical recipe of Do X, Test Performance with tool Y, the do Z if needed would be great to have.
A few links (I will add to this as I research this):
WCF Caching Approach
If you have data that are user that will change quite rarely and need fast response, going for a custom mechanism bases on local storage is a great advantage quite faster than having to wait for a server roundtrip.
Dino Sposito published an interesting article about local storage and caching on MSDN Magazine there you can find as well an approach to catch assemblies (imagine just loading the minimum package required and just go loadin the rest of assemblies in background, ... performance rocket, more complexity on your code :)).
As you said is matter to go putting in a balance and decide.
HTH
Braulio
My approach would be this:
Determine if there is actually a problem with performance (isn't it alreade acceptable to my users?)
Measure the performance at each teir (how long does it take the database to come up with data? how long does it take the service to respond with data? how much time does it take from the service to the client?)
Based on the measurements I would then determine where to do my caching. Remember that, the closer to your data storage you do caching, the easier it is, but the closer to the client you do caching, the better the performance gain (usually).
Also remember that caching should not be the first thing to do to improve performance. You should also look into other performance gains as well. Are the stored procedures slow? Is there a lot of overhead in the WCF messages? Is there some inefficient processing in the service? Do I realy need all that data in one message?
HTH,
Jonathan
I think #2 is your best bet for maintainability and architecture. IIS provides caching, why not use it?
You don't want to have to reference System.Web from a data layer. Client side is not the best option either, because you'd have to write a bunch of additional code to keep the data synchronized.
Is System.Web caching even available to WCF when it's not running in ASP.NET compatible mode? Probably best not to depend on it and write your own.
On the other hand, look into Microsoft's Velocity project, which looks like it will produce a very interesting caching technology not dependant on ASP.NET.
We just recently implemented #3, the client-side caching using Isolated Storage.
In our app we have lot of drop downs and custom fields which the app used to get from the server every time it loads. Moving these data to IS really helped. The app now makes a call to check if there were any changes on the server, and if not - loads the data from the IS, otherwise ( which is pretty rare ) refreshes IS.
That eliminated a lot of WCF calls and data transfers, the SL pages' loading time is shorter, and the app in general became more scalable because of the reduced network traffic and db access.
Yes, there are some coding involved, but the benefits for the end users are essential.
Andrew
If you use RIA Services, then a simple approach is to have two separate edmx definitions. One for cached entities, one for transactional ones.
One domain context can reference the entities on another domaincontext via AddReference see.
The cached entities could be loaded immediately after user has authenticated. For simplicity, transactional data should not load until cached entities have loaded.
Depending on the size of the cache, you may also wish to consider serializing these values to local storage.