Different ThreadPools for Seam's #Asynchronous? - asynchronous

We have an application based on Java EE 5 and the JBoss Seam 2 framework. There we use the #Asynchronous annotation a lot for background jobs.
Now, we have the problem, that those jobs may be of different priority and using a global limitation of the ThreadPool may prevent important jobs from running.
So, the question is, how to use different ThreadPools (say a low and a high prio), which have different limitations and assign the jobs to one of it?

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Best .Net Actor/Process framework for coordinating Local and Networked clusters

We have a process that involves loading a large block of data, applying some transformations to it, and then outputting what has changed. We currently run a web app where multiple instances of these large blocks of data are processed in the same CLR instance, and this leads to garbage collection thrashing and OOM errors.
We have proven that hosting some tracked state in a longer running process works perfectly to solve our main problem. The issue we now face is, as a stateful system, we need to host it and manage coordination with other parts of the system (also change tracking instances).
I'm evaluating Actors in Service Fabric and Akka at the moment, there are a number of other options, but before I proceed, I would like peoples thoughts on this approach with the following considerations:
We have a natural partition point in our system (Authority) which means we can divide our top level data set easily. Each partition will be represented by a top level instance that needs to organise a few sub-actors in its own local cluster, but we would expect a single host machine to be able to run multiple clusters.
Each Authority Cluster of actors would ideally be hosted together on a single machine to benefit from local communication and some use of shared local resources to get around limits on message size.
The actors themselves should be separate processes on the same box (Akka seems to run local Actors in the same CLR instance, which would crash everything on OOM - is this true?), this will enable me to spin up a process, run the transformation through it, emit the results and tear it down without impacting the other instances memory / GC. I appreciate hardware resource contention would still be a problem, but I expect this to be more memory than CPU intensive, so expect a RAM heavy box.
Because the data model is quite large, and the messages can contain either model fragments or changes to model fragments, it's difficult to work with immutability. We do not want to clone every message payload into internal state and apply it to the model, so ideally any actor solution used would enable us to work with the original message payload. This may cause problems with restoring an actor state as it wants to save and replay these on wakeup, but as we have state tracking internally, we can just store the resulting output of this on sleep.
We need a coordinator that can spin up instances of an Authority Cluster. There needs to be some elasticity in terms of the number of VM's/Machines and the number of Authority Clusters hosted on them, and something needs to handle creation and destruction of these.
We have a lot of .NET code, all our models, transformations and validation is defined in it, and will need to be heavily re-used. Whatever solution will need to support .Net
My questions then are:
While this feels like a good fit for Actors, I have reservations and wonder if there is something more appropriate? Everything I have tried has come back to a hosted processes of some kind.
If actors are the right way to go, which tech stack would put me closest to what I am trying to achieve with the above concerns taken into account?
IMO (coming at this from a JVM Akka perspective, thus why I changed the akka tag to akka.net; I don't have a great knowledge about the CLR side of things), there seems to be a mismatch between
We do not want to clone every message payload into internal state and apply it to the model, so ideally any actor solution used would enable us to work with the original message payload.
and
The actors themselves should be separate processes on the same box (Akka seems to run local Actors in the same CLR instance, which would crash everything on OOM - is this true?)
Assuming that you're talking about the same OS process, those are almost certainly mutually incompatible: exchanging messages strongly suggests serialization and is thus isomorphic to a copy operation. It's possible that something using shared memory between OS processes could work, but you may well have to make a choice about which is more important.
Likewise, the parent/child relationship in the "traditional" (Erlang/Akka) style actor model trivially gives you the local cluster of actors (which, since they're running in the same OS process allows the Akka optimization of not copying messages until you cross an OS process boundary), while "virtual actor" implementations as found in Service Fabric or Orleans (or, I'd argue Cloudstate or Lagom) basically assume distribution.
Semantically, the virtual actor models implicitly assume that actors are eternal (though their eternal essence may not always be incarnate). For your use-case, this doesn't necessarily seem to be the case.
I think a cluster of Akka.Net instances with sharded Authority actors spawning shorter-lived child actors best fits, assuming that you're getting OOM issues from trying to process multiple large blocks of data simultaneously. You would have to implement the instance scale-up/down logic yourself.
I have not worked with Akka.net so I can't speak to that at all, but I'd be happy to speak to what you're talking about in a Service Fabric context.
Service Fabric has no issue with the concept of running multiple clusters. In its terminology, the whole of your system would be called an Application and would have a version when deployed to the SF cluster. If you wanted to create multiple instances of it, all you'd need to do is select what you wanted to call the deployed app instance and it'll stand up provisioning for you.
SF has a notion of placement constraints, metric balancing and custom rules that you can utilize if you think you can better balance the various resources than its automatic balancing (or you need to for network DMZ purposes). While I've never personally grouped things down to a single machine, I frequently limit access of services to single VM scale sets (we host in Azure).
To the last point though, you'll still have message size limits, but you can also override them to some degree. In your project containing service interfaces, just set the following attribute above your namespace:
[assembly:FabricTransportRemotingSettings(MaxMessageSize=<(long)new size in bytes>)] and you're good to go.
Services can be configured to run using a Shared or Exclusive process model.
Regarding your state requirement, it's not necessarily clear to me what you're trying to do, but I think you're saying that that it's not critical that your actors store any state since they can work from some centrally-provided model.
You might look then at volatile state persistence then as it'll mean that state is saved for the actors in memory, but should you lose the replicas, nothing is written to disk so it's all lost. Or if you don't care and are ok just sending the model to the actors for any work, you can configure them to be stateless.
On the other hand, if you're still looking to retain state in the actors and simply are concerned about immutability, rest assured that actor state isn't immutable and can be updated trivially. There are simply order of operation concerns you need to keep in mind (e.g. if you retrieve the state, make a change, save it, 1) you must commit the transaction for it to take and 2) if you modify the state but don't save it, it'll obviously not persist - pull a fresh copy in a new transaction for any modifications). There's a whole pile of guidelines here.
Assuming your coordinator is intended to save some sort of state, might I recommend a singleton stateful service. Presumably it's not receiving an inordinate amount of use so a single instance is sufficient and it can easily save state (without the annoyance of identifying which state is on which partition). As for spinning up services, I covered this in the first bullet, but use the ApplicationManager on the built-in FabricClient to set up new applications and the ServiceManager to create instances of necessary services within each.
Service Fabric supports .NET Core 3.1 through .NET 5 as of the latest 8.0 release though note a minor serialization issues with an easy workaround with .NET 5.
If you have an Azure support subscription, I'd encourage you to write to the team under Development questions and share your concerns. Alternatively, on the third Thursday of each month at 10 AM PST, they also have a community call on Teams that you're welcome to join and you can find past calls here.
Again, I can't speak to whether this is a better fit than Akka.NET, but our stack is built atop Service Fabric. While it has some shortcomings (what framework doesn't?) it's an excellent platform for distributed software development.

Service Fabric: Should I split my API up into multiple little APIs?

I have been building .Net Web API's for years... normally I have one API that has 10 or so different controllers who handle everything from signing users up, handling business logic, payment, etc. Those all talk to class libraries to talk to the database and such. Nothing fancy, but it has been effective.
Fast forward to today... I am building a version 2 for an app that gets a good amount of traffic. I know my app is gonna get hit hard so I am looking for something with a foundation of efficiency and scale.
This has led me to embrace the coolness of Service Fabric and ASP.Net Core Web APIs. I have been reading lots of tutorials, articles, and SO questions and from what I understand, the beauty of Service Fabric is that it will spawn up multiple nodes in a single VM when things get busy.
So, if I maintain my normal pattern and make a single Web API with 10+ controllers, can Service Fabric do what it needs to do? Or am I supposed to create multiple little API's that are more focused so that the Service Fabric can add/remove them as things get busy?
That sounds like the right thing to do, and I have set up my code to do just that by putting my Models and Data classes in their own class libraries so they can be reused by the different API's, but I just wanted to double check before I do something potentially stupid.
If I split up, say each controller into its own Service Fabric service, will the Azure server be more efficient and scale better?
Nodes
In Service Fabric clusters (on Azure / stand alone) a Node equals a VM. If you increase the amount of machines, more Nodes appear in the cluster. (This is not the case for your local dev cluster.) Scaling in Azure Clusters is simple: just change the VMSS instance count.
Only if you configure Stateless Services with instance count -1, Service Fabric will spawn new instances of it. This is caused by the addition of nodes, not by load itself.
You can configure autoscaling for VMSS'es.
Web API
Service Fabric just tries to balance the load of all running SF Services across the available resources. That could be one instance of one service type on every node, or multiple instances of many types. So one service can just use all the resources of the node it's running on, like with IIS. (This is why Container support is coming by the way.)
Web API design isn't directly influenced by Service Fabric. The same rules apply as when running on IIS or elsewhere. It's really your choice.
Microservices
Your normal pattern will work. But making smaller services from it could help reduce the impact of changes. (At the cost of increased complexity.) Consider creating services that offer common functionality following the Microservices paradigm.
In Microservices, your code changes are scoped to smaller modules, less testing is needed, performance is less degraded during updates. This way, in theory, you can release new features in less time.
It depends.
If you have a natural division in your controllers regarding the resources they use then you may get some benefit if you split your services along that division line. Say service A uses lots of CPU and service B uses mostly HTTP then giving SF the ability to split CPU loads on their own may mean fewer affected HTTP calls.
You can optimize how SF distributes load by reporting load from inside your app but do so in the simplest way possible and don't add numerous dimensions, maybe one per service at most.
If all your controllers use the same type of resources roughly the same then there's no real benefit to splitting them away in separate services, just complications in code management, deployments and potentially inter-service communications.

MagicalRecord: Setting up core data stack on a background thread

One of the things Marcus Zarra recommends in his Core Data book when talking about setting up an app's core data stack is to put calls to addPersistentStoreWithType:configuration:URL:options:error: on a background thread, because it can take an indeterminate amount of time (e.g., to run migrations). Is there a simple way to tell MagicalRecord to do that? It looks like all of its setupCoreDataStack... methods perform everything on the calling (presumably main) thread.
I don't think it makes sense to just move the top-level setup calls onto a background thread, because it wouldn't be safe to start using MR from the main thread until at least the contexts had been created, right? Do I need to implement my own setupCoreDataStackWithAsyncMigration or somesuch thing?
There is the wwdc2012 example code for setting up iCloud on a background thread (Shared Core Data sample). You could refractor the CoreDataController to use MagicalRecord (and ignore anything iCloud). IIRC the locking mechanism, to stop other threads from accessing the store while the setup is in progress, is already present.
Before you go down that route measure the time needed to startup on the device. If the startup is fast enough for your needs then you might want to stick with the setup on a main thread.
Migrations can take some time but migration won't occur on every app launch. Migration time depends on data volume and complexity of changes between model versions. So again it is a judgment call to invest time to move the migration to a background thread or to keep the user waiting.

Workflow Foundation - Can I make it fit?

I have been researching workflow foundation for a week or so now, but have been aware of it and the concepts and use cases for it for many years, just never had the chance to dedicate any time to going deeper.
We now have some projects where we would benifit from a centralized business logic exposed as services as these projects require many different interfaces on different platforms I can see the "Business Logic Silos" occuring.
I have had a play around with some proof of concepts to discover what is possible and how it can be achieved and I must say, its a bit of a fundamental phase shift for a regular C# developer.
There are 3 things that I want to achieve:
Runtime instanciated state machines
Customizable by the user (perform different tasks in different orders and have unique functions called between states).
WCF exposed
So I have gone down the route of testing state machine workflows, xamlx wcf services, appfabric hosted services with persistance and monitoring, loading xamlx services from the databse at runtime, etc, but all of these examples seem not to play nicely together. For example, a hosted state machine service, when in appfabric, has issues with the sequence of service method calls such as:
"Operation 'MethodName' on service instance with identifier 'efa6654f-9132-40d8-b8d1-5e611dd645b1' cannot be performed at this time. Please ensure that the operations are performed in the correct order and that the binding in use provides ordered delivery guarantees".
Also, if you call instancial workflow services at runtime from an sql store, they cannot be tracked in appfabric.
I would like to Thank Ron Jacobs for all of his very helpful Hands On Labs and blog posts.
Are there any examples out there that anyone knows of that will tie together all of these concepts?
Am I trying to do something that is not possible or am I attempting this in the right way?
Thanks for all your help and any comments that you can make to assist.
Nick
Regarding the error, it seems like you have modified the WF once deployed (is that #2 in your list?), hence the error you mention.
Versioning (or for this case, modifying a WF after it's been deployed) is something that will be improved in the coming version, but I don't think it will achieve what you need in #2 (if it is what I understood), as the same WF is used for every instance.

How do I prevent static member variables from being accessed by more than one request at a time in IIS?

I’m having some trouble with understanding how IIS is handling static variables on its threads. My understanding has always been that if IIS has 4 worker processes that it can handle 4 requests simultaneously and that it would be the same as having 4 separate threads running the website. Any static variables would persist in each individual thread. The reason I’m a bit confused is that I have a scope that I’ve made which manages connections and caching transactions. When I’m testing the app I don’t notice any issues but after I’ve compiled it and hit it at the same time from two different locations I seem to get a sort of conflict. Now if these worker processes are separate why would this be? Can more than one request be processed on a single worker thread at the same time? This is tremendously important as there are unique ID’s that are held in these static members to handle escalation of the objects that manage these functions and it appears that they are trying to access the same object.
I'm running this on Vista's IIS server on an x64 machine.
EDIT
For values that need to persist through the thread on a single request, I put these values into Web.HttpContext.Current.Items which seems to do the trick.
<ThreadStatic()> can be used but it may not be available during the entirity of the request process. In one module that I have, is only used on a variable to indicate if that thread has already loaded the settings for the cahcing server. If true then the tread (not asp.net) is ready to fetch data from the caching server.
First concept to change: if you're using ASP.NET, they are ASP.NET threads, not IIS threads.
Second, this is a .NET issue. static variables are shared throughout the AppDomain in .NET. Since you'll have one AppDomain per IIS application (more or less), that means your static variables will be shared across all worker threads in the application.
There will be a lot more than four threads, and they'll all be sharing the same variables, which means you'll either need to do locking, or you'll need to not use static variables.
Whatever your understanding has always been, I suggest you go back and figure out where you got that understanding from; then update it, because it doesn't have much to do with ASP.NET.
EDIT: The subject has changed, so I'll change the answer a little.
You have to interlock access to these variables. Alternatively, you should consider reevaluating your design. Your design apparently assumed some different model for access to statics. This assumption has turned out not to be correct. It's possible that this assumption may have cascaded throughout your design. You should reevaluate your design in the light of reality.
Each worker process runs in its own AppDomain, so each WP will have its own instance of a static variable.
In the answer here it suggests the AppDomain is shared across WPs which is incorrect.
You should be using the .NET connection pooling though and you should investigate the using(IDisposable){} method of scoping your connections.

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