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Top 20 Microsoft Azure Fabric Interview Questions and Answers
Q1) Define Azure Service Fabric.
Ans: Azure Service Fabric is termed as a stage for distributed systems which eases the work of deploying, packaging and managing reliable and scalable microservices. It also handles noteworthy problems related to the development of cloud applications.
Q2) Define Service Fabric Cluster.
Ans: Service Fabric Cluster can be described as a shared pool of machines. These clusters can have thousands of machines and can expand their areas globally.
Q3) Describe the importance of application instance in Azure Service Fabric.
Ans: Application instance in Azure Service Fabric can be run as a separate process even though they are on the same Fabric Service node. One can have as many as application instances of any type as they want in a cluster. Each application instance will have a specific name in a cluster and independently managed and versioned from rest application instances of same or different type. Moreover, resources and security isolation can be defined by them.
Q4) Define cluster in Azure Fabric Service
Ans: A cluster can be described as a collection of virtual/physical machines that are connected by a network. On these machines only, application instances are getting deployed.
Q5) Define node in Azure Fabric Service
Ans: A node in a cluster is an addressable unit. It has unique IDs and placement properties. The cluster can be formed as different nodes.
Q6) Does a cluster have any minimum size limit? If yes, what and why?
Ans: Yes. Azure supports a minimum of 5 nodes for the production environment for a Service Cluster. For dev/test environments, Azure supports three nodes of the cluster. This minimum node requirement exists as Azure runs a collection of Stateful Services. These services are directly dependent on consistency. And this strong consistency is directly dependent on the ability of any service to obtain a quorum for an update to the state of them. Quorum amounts to the majority of replicas for a given service.
Q7) Define Service type in Azure Service Fabric.
Ans: A service type is a coding unit or a configuration which runs independently. An application type can have one or more service types. For example, Queue Service
Q8) Define Service instance in Azure Service Fabric.
Ans: The service instance can be defined as code which instantiated for each service type. Every service instance is associated with a specific application instance and will have a unique name.
Q9) Define application package in Azure Service Fabric
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Ans: Application packages are composed of service code packages and configuration files of a particular application. For example, an email application package is a combination of a front-end service package, queue service package and database service package.
Q10) Explain MicroService.
Ans: MicroService applications are formed of scalable, compact, stand-alone and customer-focused services, which converse with each other using standard protocols and well-defined interfaces.
Q11) Describe different types of MicroServices.
Ans: Below are two types of MicroServices:
1. Stateless Microservices – they don’t continue to keep an inconsistent state outside of any request and its response from the service. For example, Azure Cloud Services worker roles, web proxies etc.
2. Stateful Microservices – They continue to keep an inconsistent state beyond the request and its response from the service. For example, Shopping carts, queues etc.
Today’s Internet-scale applications composed of a combination of stateless and stateful microservices.
Q12) Define Application type in Azure Service Fabric.
Ans: The application type is a collection of one or more service types or we can describe them as a collection of microservices.
Q13) Brief about Programming models available in Azure Service Fabric.
Ans: To build applications in Azure Service Fabric, we have two programming models:
1. Reliable Services: An API to develop stateful and stateless services using StatelessService and StatefulService .NET classes and save state in .NET collections like dictionary and queue.
2. Reliable Actors: An API to build stateless and stateful objects using the virtual actor programming model that is suitable for applications with different independent units of state and compute.
Q14) How the Nodes in Service Fabric behave in case of OS updates?
Ans: As of now, nodes in Azure Service Fabric don’t receive OS updates automatically. Azure doesn’t support automatic OS updates in nodes of Service Fabric.
Q15) Is it feasible to turn off the cluster during weekends/night for saving money?
Ans: No, it is not at all a feasible option. If we turn off the cluster during weekends/nights when we restart them afterward, almost all the nodes will obtain a brand-new host and in turn makes the system unrecoverable.
Q16) What is a Container?
Ans: The container is an individual component which can be run independently and as an isolated instance to gain the benefits of virtualization which an OS gives. It provides a varying environment for the application to run with different types of isolation.
Q17) Explain the advantages of the container over virtual machines.
Ans: Below is the advantages of the container over virtual machines.
1. Smart: Use a single storage space and layer versions to increase efficiency
2. Fast: Start faster as no need to boot an operating system
3. Portability: Application image can be ported to run on the cloud, virtual machines, premises or physical devices
4. Resource Governance: Resources can be limited consumed by the host.
Q18) Which two metrics affects resource governance which is supported in Service Fabric?
Ans: Two metrics affects resource governance, supported in Service Fabric:
1. CPU: metric name - servicefabric:/_CpuCores
2. Memory: metric name - servicefabric:/_MemoryInMB
These two metrics maps total cluster capacity and how much load a node can bear.
Q19) Define horizontal scaling.
Ans: Horizontal scaling can be termed as scaling by increasing machine in the pool of resources.
Q20) Define vertical scaling.
Ans: Vertical scaling can be termed as scaling by increasing more power like CPU or RAM to a machine.