Recently came to know about Azure Service Fabric and seems a good way to develop scaling applications as bunch of micro services. Everywhere it is telling that we need to have stateless front end web services and stateful partitioned internal services. The internal services scale by partitioning the data.
But what happens to the front end services in load? .The chances are very less as they are doing nothing but relying to internal stateful services. Still should we use load balancer before front end services? If so, can we host the same too via Service Fabric's Stateless model using OWIN or any other web host?
The question is asked already in SO but as comment. It didnt get reply as the original question was different.
Azure Service Fabric usage
Yes, you'll definitely want to distribute load across your stateless services as well. The key difference is that since they are stateless, they can handle requests in a round-robin fashion.
Whereas stateful services have partitions, which map to individual chunks of the service's state, stateless services simply have instances, which are identical clones of each other, just on different nodes. You can set the number of instances in on the default service definition in the application manifest. For instance, this declaration will ensure that there are always 5 instances of your stateless service running in the cluster:
<Service Name="Stateless1">
<StatelessService ServiceTypeName="Stateless1Type" InstanceCount="5">
<SingletonPartition />
</StatelessService>
</Service>
You can also set the InstanceCount to -1, in which case Service Fabric will create an instance of your stateless service on each node.
The Azure load-balancer will round-robin your incoming traffic across each of your instances. Unfortunately, there isn't a good way to simulate this in a one-box environment right now.
Related
I've been studying the Azure documentation and the web for a while now and can't find any answer to my question: How is the internal service-to-service communication load balanced in Azure Service Fabric? I've read about load balancers, but they seem to be responsible for external traffic, so client-to-service communication. Is the naming service available in Service Fabric doing some kind of load balancing or round robin?
In the source code, you can see that - in communication with stateless services, or secondary replicas of stateful services - for every cached communication client, a random endpoint is selected.
The client is reused until it becomes invalid, due to service changes (crashes, moves).
This makes me say it's not round robin, but more like session affinity.
i have Service fabric Cluster Running on Azure ,i have deployed Application to Service Fabric.
Now i want to use azure Application Gateway on this Scenario like Request First served to Application Gateway and then it migrated to Fabric Load Ba-lancer. I am Quite Confused on this.How to meet above Challenges with ApplicationGateway
I also able to configure ApplicationGateway but dont have IDea how to use it for service fabric
Microsoft Azure Application Gateway offers layer 7 load balancing capabilities, SSL offloading, layer-7 routeing, cookie based session affinity, URL routeing and able to host multiple web application. Azure Application Gateway requires its subnet; sometimes it is confusing if you are not familiar with Azure VNet and Subnet segmentation.
First what you need to understand is the architecture pattern, how Microsoft Application Gateway would play a part in.
I have written some detail series documenting my journey throughout Azure ServiceFabric.
I would suggest you go through these posts, and it will explain Architecture viewpoint for having Application Gateway in front of Service Fabric Cluster.
Irrespective of Application Gateway, you would need Internal Loadbalancer or External Loadbalancer (depends on your topology).
Cloud Architecture Pattern: Azure Service Fabric and Microservices - Part 1 (Physical Architecture)
How to implement Application Gateway with Azure Service Fabric
Also try to understand how it is going to impact, security architecture of your implementation
Also, I would recommend you Reverse proxy in Azure Service Fabric.
Not fully sure your meaning, but you could create sf cluster and related resources using ARM teplates. Thats what I have done. I created appgw, cluster, vmss etc. In the virtualMachinesScalesets networkProfile you must configure the ApplicationGateway back endAddress pool instead of configuring loadBalancerBackendAddressPools. The appgw must exist before vmss deployment. You don't necessarily need lb at all. Appgw can handle the load balancing for you. Even though internal lb would bring in some nice additional features, which you could utilize later on...
I have to admit that these things are quite poorly documented...
I have a application that can be broken down into multiple communicating services. My current implementation is monolithic and I want to reorganize it so that individual components can be deployed,iterated upon, scaled independently. I see two ways to do this with Azure:
Service Fabric service composed of set of communicating micro-services (stateless, web-api etc.)
A collection of individual Azure Web Apps/ Cloud Services that call each other at the http end points.
Are there any obvious advantages of 1 over 2? Any rule of thumb to chose one over the other would also be very helpful.
I think this page compares it well: https://learn.microsoft.com/en-us/azure/service-fabric/service-fabric-cloud-services-migration-differences/
I can't tell it better than this.
There is not really a rule of thumb. Service Fabric might seem more complex but offers some things that Cloud Services / Web Apps don't.
A quick summary (taken from the link provided):
Service Fabric itself is an application platform layer that runs on Windows or Linux, whereas Cloud Services is a system for deploying Azure-managed VMs with workloads attached. The Service Fabric application model has a number of advantages:
Fast deployment times. Creating VM instances can be time consuming. In Service Fabric, VMs are only deployed once to form a cluster that hosts the Service Fabric application platform. From that point on, application packages can be deployed to the cluster very quickly.
High-density hosting. In Cloud Services, a Worker Role VM hosts one workload. In Service Fabric, applications are separate from the VMs that run them, meaning you can deploy a large number of applications to a small number of VMs, which can lower overall cost for larger deployments.
The Service Fabric platform can run anywhere that has Windows Server or Linux machines, whether it's Azure or on-premises. The platform provides an abstraction layer over the underlying infrastructure so your application can run on different environments.
Distributed application management. Service Fabric is a platform that not only hosts distributed applications, but also helps manage their lifecycle independently of the hosting VM or machine lifecycle.
Peter has done a great summary. And here are my additional points:
Cloud Service is not designed for micro service pattern, while Service Fabric is. If you want to enjoy the benefits brought by micros service, Service Fabric is your best choice.
With Cloud Service, if you want separate your application into autonomous services, you either
Create multiple cloud services. Which is difficult to monitor and manage since there is not a unified interface for a group of cloud services, Cloud Service is just not designed for this pattern.
Or add multiple roles into a single cloud service, this will lead to a) bloat of your cloud service configuration file, because all service configurations are in a single config file; and b) to upgrade a single role, you end up redeploy the whole cloud service!
Cloud Service doesn't support cross region/DC deployment, while Service Fabric does. That means you can turn a DC level disaster recovery into a normal failover, which automatically handled by Service Fabric, see this.
I'm looking into migrating an application to Service Fabric running on Azure. It's a realtime chat-style application using SignalR. I'd like to have an instance of a service running, self-hosting a SignalR hub (via OWIN) for each "affinity group" in which users are communicating. This is so I can avoid having to scale out SignalR with a backplane. I'd like to be able to spin these services up and down as groups of users enter and leave my application. I would expect I could host tens of these services per VM with a typical load of hundreds of users per group.
My idea is that I'd have a service locator that clients connect to initially to discover which service (port) is hosting their group. I would also have a service that spun up an instance of the chat service when the first request for that group came in.
How would I architect this in Service Fabric on Azure so that a) each of the services/actors is accessible with a SignalR client from the internet? and b) I'm only running as many services as necessary to serve m active groups out of n total groups? The demand for this app is very transient and spiky, so I'm hoping to take advantage of the fact that services are simply processes and can be provisioned in a matter of seconds vs. my current scenario where I have to spin up entire cloud services and wait tens of minutes to handle spikes (at which point it's too late)
You would do a few things:
Have a "service manager service" that intercepted initial join requests and created new Service Fabric services on the fly if they didn't already exist OR if they did already exist resolve the service's current location and then return that address to the client
Alternatively they could just pass back the internal service name (if you're ok exposing that information) and the client could do the resolution and then connection. To some degree this will depend on how much info you want to expose to the client, whether you can or want to modify it to "know about" Service Fabric, etc.
The client would then connect to the actual backing service directly
You would have to come up with some sort of mechanism for the actual chat services to know that there is nobody left and to either delete themselves or to go back through the manager.
You probably would be best off modeling the chat service as a Reliable Service rather than an actor as the Reliable Services stack allows more flexibility around communication protocols/stacks.
I am trying to scale a web app on Azure from a single web instance to multiple instances. The web app does a fair amount of processing of per-user state, it's also fairly interactive so latency is important. We currently have a single database, testing has shown it is not the bottleneck so for this question let's assume we don't have to worry about scaling it, all instances will hit the same database. In this case, I think per-user load balancing is the best option, as per-request will result in per-user state being duplicated in lots of web instances. Apart from the issue of maintaining consistency, I am concerned this would result in unacceptable latency for end users.
This link says that ARR does per-user load balancing by default on Azure. However, the Traffic Manager, which from what I can gather is automatically enabled when you spin up multiple web instances on Azure, does per-request load balancing.
So my question is, which of these two load balancing schemes will I be using if I add a few more instances to my Web Hosting Plan? If I need to manually disable the Traffic Manager, what is the best way to do this?
Calum - you can leverage the standard SQL Session State Provider in Azure or you could look at the Azure Redis Cache provider as well for backing stores for user session state.
When deploying to Cloud Service Web Roles you automatically get a load balancer instance in front of your hosts. It's relatively transparent other than configuration of Endpoints. Each newly added/removed auto-scaled instance gets added to the Cloud Service and is automatically added/removed to the load balancer.
As others have said, Azure Traffic Manager provides a higher level service which can direct traffic to multiple Azure Regions (data centers) and even on-premises endpoints.
A good overview of Load Balancing can be found here: http://azure.microsoft.com/blog/2014/04/08/microsoft-azure-load-balancing-services/