Share a CPU between more than one application in Service Fabric - azure-service-fabric

This page on Microsoft Docs clearly shows how to share a single CPU between two code Packages inside an Application.
This is done by using CpuShares.
Is there a way to use CpuShares between two Applications?

All resource governance in Service Fabric is on the Service level.
The information you reference specifies how the CPU reservation for a service (not application) is divided between multiple code packages within the service.
From the article
Resource governance is supported in Service Fabric in accordance with the service package. The resources that are assigned to the service package can be further divided between code packages.
The above references this article about the service / application model in Service Fabric: https://learn.microsoft.com/en-us/azure/service-fabric/service-fabric-application-model

Related

Usage of custom resource definition (CRD) vs Service Catalog in k8s

I recently started to explore k8s extensions and got introduced to two concepts:
CRD.
Service catalogs.
They look pretty similar to me. The only difference to my understanding is, CRDs are deployed inside same cluster to be consumed; whereas, catalogs are deployed to be exposed outside the cluster for example as database service (client can order cluster of mysql which will be accessible from his cluster).
My query here is:
Is my understanding correct? if yes, can there be any other scenario where I would like to create catalog and not CRD.
Yes, your understanding is correct. Taken from official documentation:
Example use case
An application developer wants to use message queuing as part of their application running in a Kubernetes cluster.
However, they do not want to deal with the overhead of setting such a
service up and administering it themselves. Fortunately, there is a
cloud provider that offers message queuing as a managed service
through its service broker.
A cluster operator can setup Service Catalog and use it to communicate
with the cloud provider’s service broker to provision an instance of
the message queuing service and make it available to the application
within the Kubernetes cluster. The application developer therefore
does not need to be concerned with the implementation details or
management of the message queue. The application can simply use it as
a service.
With CRD you are responsible for provisioning resources, running backend logic and so on.
More info can be found in this KubeCon 2018 presentation.

Difference between Kubernetes and Service Fabric

I have worked on Kubernetes and currently reading about Service Fabric, I know Service Fabric provides microservices framework models like stateful, stateless and actor but other than that it also provides GuestExecutables or Containers as well which is what Kubernetes also does manage/orchestrate containers. Can anyone explain a detailed difference between the two?
You can see in this project paolosalvatori/service-fabric-acs-kubernetes-multi-container-appthe same containers implemented both in Service Fabric, and in Kubernetes.
Their "service" (for external ingress access) is different, with Kubernetes being a bit more complete and diverse: see Services.
The reality is: there are "two slightly different offering" because of market pressure.
The Microsoft Azure platform, initially released in 2010, has implemented its own Microsoft Azure Fabric Controller, in order to ensure the services and environment do not fail if one or more of the servers fails within the Microsoft data center, and which also provides the management of the user's Web application such as memory allocation and load balancing.
But in order to attract other clients on their own Microsoft Data Center, they had to adapt to Kubernetes, released initially in 2014, which is now (2018) either adopted or closely considered by... pretty much everybody (as reported in late December)
(That does not mean one is "better" than the other,
only that the "other" is more "visible" than the first ;) )
So it is less about "a detailed difference between the two", and more about the ability to integrate Kubernetes-based system on Microsoft Data Centers.
This is in line (source: detailed here) with Microsoft continued its unprecedented shift toward an open (read: non-proprietary) staging platform for Azure (with Deis).
And Kubernetes orchestrator is available on Microsoft's Azure Container Service since February 2017.
You can see other differences in their architecture of a deployed application:
Service Fabric:
Vs. Kubernetes:
thieme mentions in the comments the article "Service Fabric and Kubernetes comparison, part 1 – Distributed Systems Architecture", from Marcin Kosieradzki.
Both are different. Kubernetes manages rkt or other containers.
Service Fabric is not for managing containers. In case it manages some, that does not make it its purpose. That does not enable it for a comparison with Kubernetes.
eg: When a pod dies Kubernetes puts it to other nodes immediately. The part of SF that manages containers does not do this, it is done by some other area of Service Fabric. And outside containers. And was not designed with containers in mind.

Difference between native and guest service with Service Fabric

I have a bunch of services deploying as guest executables to service fabric and all seems fine. I was wondering if there was any point in porting the services to be native Fabric Service services.
Looking at the documentation I can't seem to find any benefits of having implementing them as such, am I missing something obvious?
If your services are stateless there is probably no compelling reason to migrate them into native stateless services. It could be different if your services were stateful; in this context I mean that they store some state inside the process.
The state in native stateful services is stored redundantly, so your services can cope with node failures. This could increase the resilience of your service. In general, you usually create native services in green field situations and rely on guest executables and containers in migration/hybrid situations.
Guest Executable is missing out on some advanced features but it is up to you to decide if you need them.
Benefits of running a guest executable in Service Fabric
There are several advantages to running a guest executable in a Service Fabric:
High availability. Applications that run in Service Fabric are made highly available. Service Fabric ensures that instances of an application are running.
Health monitoring. Service Fabric health monitoring detects if an application is running, and provides diagnostic information if there is a failure.
Application lifecycle management. Besides providing upgrades with no downtime, Service Fabric provides automatic rollback to the previous version if there is a bad health event reported during an upgrade.
Density. You can run multiple applications in a cluster, which eliminates the need for each application to run on its own hardware.
Discoverability: Using REST you can call the Service Fabric Naming service to find other services in the cluster.
I.e. There is something called Stateless Reliable Services - http://www.jamessturtevant.com/posts/Service-Fabric-Service-Types/
The above link will explain it more.

Application insights and service fabric?

I found this from several months back on Application Insights and Service Fabric and I'm wondering if there is any new information.
I would really like to get CPU, Memory, Storage and other metrics out of service fabric and the reliable actors. Having it presented in a user friendly HUD like app insights provides would be awesome!
Thanks!
On the azure portal, you can now create a resource called 'Service Fabric Analytics' to create a nice dashboard for your cluster. Configure as cluster like described here. It's OMS based, not Appinsights though.
The Service Fabric Solution helps identify and troubleshoot issues
across your Service Fabric cluster, by providing visibility into how
your Service Fabric virtual machines are performing and how your
applications and micro-services are running. Available features
include: • Get insight into your Service Fabric framework • Get
insight into the performance of your Service Fabric applications and
micro-services • View events from your applications and micro-services
Data collected: Service Fabric Reliable Service Events, Service Fabric
Actor Events, Service Fabric Operational Events, Event tracing for
Windows events and Windows event logs. Requirements: This solution
will only work if you have set up Azure Diagnostics on your Service
Fabric VMs, and have configured OMS to collect data for your WAD
tables.
In service fabric with Eventflow https://github.com/Azure/diagnostics-eventflow you had a option to send the diagnostics data to multiple data stores like WAD Tables, OMS, elastic search and application insights.
Have a look at it. It is really straight forward and easily integrate with ETW events and will serve your purpose.

Azure vs On-premise Service Fabric

I have a bit of trouble finding differences about Azure and on-premise Service Fabric versions. I did read somewhere that on-premise version does not support auto-scaling, but this is easy to understand.
However, does on-premise version offer any type of operational capabilities such as resource managers, visual management of cluster, etc.?
The core Service Fabric platform is simply a runtime that gets installed on a set of virtual or physical machines. Once you tell those machines how to find each other, they form a cluster and provide a set of management capabilities that includes the Service Fabric Explorer UI, a REST API, and a TCP endpoint for PowerShell. All of that is common whether you're running on Azure, on-premises, or in another public cloud.
What's different in those environments is everything that lives outside of the machines that form the cluster. That includes:
Autoscaling
While Service Fabric can easily handle new machines being added and removed from the cluster, it has no knowledge of how that process actually works, so some external agent needs to handle it. In Azure, that's a virtual machine scale set.
Failure domain/Upgrade domain management
Good management of failure and upgrade domains is critical to ensuring availability and data reliability in Service Fabric. In Azure, clusters are automatically spread across FDs/UDs and maintenance is coordinated to avoid impact to your clusters. In other environments, this is your responsibility.
Cluster setup and management
In Azure, a Service Fabric cluster is a 1st class resource that can be created and managed through the Azure Resource Manager and the Azure portal. Outside of Azure, you must do that management using the cluster configuration JSON template.
Incidentally, just so there's no confusion since there are overloaded terms... you can't currently use the Azure Resource Manager (ARM) with Service Fabric outside of the Azure environment. However, Service Fabric's cluster resource manager is part of the core runtime and is available everywhere.
Diagnostics pipeline
By default, Service Fabric logging (on Windows) is done via ETW. However, without any component to pick up those events from the individual machines in the cluster and ship them somewhere for easy aggregation and inspection, the logs aren't very useful. In Azure, that process is handled by the Windows Azure Diagnostics (WAD) agent, whereas in other environments you are responsible for setting up that pipeline.
You don't get to use the resource manager on premises. You can access the Service Fabric Explorer at port 19080.
https://azure.microsoft.com/en-us/documentation/articles/service-fabric-deploy-anywhere/
https://azure.microsoft.com/en-us/documentation/articles/service-fabric-visualizing-your-cluster/
Powershell management & deployment will also work.