Q.1. Explain Docker and Containers.
Ans:
• Docker is an open platform for developing and running applications. Docker enables you to separate your applications from your infrastructure so you can deliver software quickly.
1. A container is a standard unit of software that packages up code and all its dependencies so the application runs quickly and reliably from one computing environment to another.
2. A Docker container image is a lightweight, standalone, executable package of software that includes everything needed to run an application: code, runtime, system libraries and settings.
3. Container images become containers at runtime.
Q.2. Explain Docker Client-Server architecture.
Ans:Docker uses a client-server architecture. The Docker client talks to the Docker daemon, which does the heavy lifting of building, running, and distributing your Docker containers.
The Docker client and daemon can run on the same system, or you can connect a Docker client to a remote Docker daemon. The Docker client and daemon communicate using a API.
The Docker daemon:
The Docker daemon (docker) listens for Docker API requests and manages Docker objects such as images, containers, networks, and volumes.
The Docker client:
The Docker client (docker) is the primary way that many Docker users interact with Docker. When you use commands such as docker run, the client sends these commands to dockerd, which carries them out. The docker command uses the Docker API. The Docker client can communicate with more than one daemon.
Docker registries:
A Docker registry stores Docker images. Docker Hub is a public registry that anyone can use, and Docker is configured to look for images on Docker Hub by default. When the docker pull or docker run commands, the required images are pulled from your configured registry.
Q.3. Explain about Kubernetes.
You are working as a DevOps engineer for a software development company. The company is planning to deploy a microservices-based application on Kubernetes clusters to ensure scalability and high availability. As part of the deployment process, you need to design and implement a rollout strategy that minimizes downtime and allows for easy rollback in case of any issues. Additionally, you need to ensure that the application's resources are efficiently managed within the Kubernetes environment. How would you approach this scenario, and what Kubernetes features and strategies would you employ to achieve these goals?
Ans:
• Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications.
• Containerization helps package software to serve these goals, enabling applications to be released and updated in an easy and fast way without downtime.
• Kubernetes helps you make sure those containerized applications run where and when you want, and helps them find the resources and tools they need to work.
• Kubernetes is a production-ready, open source platform designed with Google's accumulated experience in container orchestration, combined with best-of-breed ideas from the community.
• A container orchestrator is essentially an administrator in charge of operating a fleet of containerized applications. If a container needs to be restarted or acquire more resources, the orchestrator takes care of it for you.
Q.4. What is Kubernetes used for?
Ans:
Kubernetes keeps track of your container applications that are deployed into the cloud. It restarts orphaned containers, shuts down containers when they’re not being used, and automatically provisions resources like memory, storage, and CPU when necessary.
Q.5. How does Kubernetes work with Docker?
Ans:
Actually, Kubernetes supports several base container engines, and Docker is just one of them. The two technologies work great together, since Docker containers are an efficient way to distribute packaged applications, and Kubernetes is designed to coordinate and schedule those applications.
Q.6. What are Kubernetes architecture components?
The main components of a Kubernetes cluster include:
Nodes: Nodes are VMs or physical servers that host containerized applications. Each node in a cluster can run one or more application instance. There can be as few as one node, however, a typical Kubernetes cluster will have several nodes (and deployments with hundreds or more nodes are not uncommon).
Image Registry: Container images are kept in the registry and transferred to nodes by the control plane for execution in container pods.
Pods: Pods are where containerized applications run. They can include one or more containers and are the smallest unit of deployment for applications in a Kubernetes cluster.
Q.7.What is Kubernetes Control Plane architecture?
A Kubernetes control plane is the control plane for a Kubernetes cluster. Its components include:
• kube-apiserver. As its name suggests the API server exposes the Kubernetes API, which is communications central. External communications via command line interface (CLI) or other user interfaces (UI) pass to the kube-apiserver, and all control planes to node communications also goes through the API server.
• etcd: The key value store where all data relating to the cluster is stored. etcd is highly available and consistent since all access to etcd is through the API server. Information in etcd is generally formatted in human-readable YAML (which stands for the recursive “YAML Ain’t Markup Language”).
• kube-scheduler: When a new Pod is created, this component assigns it to a node for execution based on resource requirements, policies, and ‘affinity’ specifications regarding geolocation and interference with other workloads.
• kube-controller-manager: Although a Kubernetes cluster has several controller functions, they are all compiled into a single binary known as kube-controller-manager. Controller functions included in this process include:
• Replication controller: Ensures the correct number of pods is in existence for each replicated pod running in the cluster
• Node controller: Monitors the health of each node and notifies the cluster when nodes come online or become unresponsive
• Endpoints controller: Connects Pods and Services to populate the Endpoints object
• Service Account and Token controllers: Allocates API access tokens and default accounts to new namespaces in the cluster
• cloud-controller-manager: If the cluster is partly or entirely cloud-based, the cloud controller manager links the cluster to the cloud provider’s API. Only those controls specific to the cloud provider will run. The cloud controller manager does not exist on clusters that are entirely on-premises. More than one cloud controller manager can be running in a cluster for fault tolerance or to improve overall cloud performance.
Elements of the cloud controller manager include:
• Node controller: Determines status of a cloud-based node that has stopped responding, i.e., if it has been deleted
• Route controller: Establishes routes in the cloud provider infrastructure
• Service controller: Manages cloud provider’s load balancers
Q.8. What is Kubernetes node architecture?
Nodes are the machines, either VMs or physical servers, where Kubernetes place Pods to execute. Node components include:
• kubelet: Every node has an agent called kubelet. It ensures that the container described in PodSpecs are up and running properly.
• kube-proxy: A network proxy on each node that maintains network nodes which allows for the communication from Pods to network sessions, whether inside or outside the cluster, using operating system (OS) packet filtering if available.
• container runtime: Software responsible for running the containerized applications. Although Docker is the most popular, Kubernetes supports any runtime that adheres to the Kubernetes CRI (Container Runtime Interface).
Q.9. What are other Kubernetes infrastructure components?
• Pods: By encapsulating one (or more) application containers, pods are the most basic execution unit of a Kubernetes application. Each Pod contains the code and storage resources required for execution and has its own IP address. Pods include configuration options as well. Typically, a Pod contains a single container or few containers that are coupled into an application or business function and that share a set of resources and data.
• Deployments: A method of deploying containerized application Pods. A desired state described in a Deployment will cause controllers to change the actual state of the cluster to achieve that state in an orderly manner. Learn more about Kubernetes Deployments.
• ReplicaSet: Ensures that a specified number of identical Pods are running at any given point in time.
• Cluster DNS: serves DNS records needed to operate Kubernetes services.
• Container Resource Monitoring: Captures and records container metrics in a central database.
Note: (Q6-Q9 can be combined answer of cloud computing architecture).
Q.10. What is edge computing.
Ans:
• A part of a distributed computing topology in which information processing is located close to the edge – where things and people produce or consume that information.”
• Edge computing brings computation and data storage closer to the devices where it’s being gathered, rather than relying on a central location that can be thousands of miles away.
• Edge computing was developed due to the exponential growth of IoT devices, which connect to the internet for either receiving information from the cloud or delivering data back to the cloud.
Q.11. What is fog computing.
Ans:
• Fog computing can be perceived both in large cloud systems and big data structures, making reference to the growing difficulties in accessing information objectively.
• This results in a lack of quality of the obtained content. The effects of fog computing on cloud computing and big data systems may vary.
• However, a common aspect is a limitation in accurate content distribution, an issue that has been tackled with the creation of metrics that attempt to improve accuracy.
• Fog networking consists of a control plane and a data plane. For example, on the data plane, fog computing enables computing services to reside at the edge of the network as opposed to servers in a data-center.
Q.12. Explain Industrial Internet of Things (IIOT).
Ans:
• The Industrial Internet of Things (IIoT) is a methodology, a practice, an implementation sweeping through businesses and industries worldwide. On a basic level, IIoT is a way of congregating data that was previously inaccessible and locked within inflexible data streams. This provides all stakeholders with a more complete and comprehensive view of operations.
• Imagine smart TVs and watches or security cameras - devices that were historically lacking in internet connection but now have that capability. This is IoT, the Internet of Things. IIoT is used to refer to industrial equipment and plant assets that are now integrated.
• Developments in technology are ushering in the age of Industry 4.0, where real-time data is captured and made available within integrated digital ecosystems. Similarly, software is now increasingly platform-agnostic, this means that plant floor information won't be originating from a single platform, but there will be a multitude of systems that needs to feed into a companies digital nervous system.
Q.13. What is Green Cloud Computing.
Ans:
• With Green cloud computing, world is looking forward to higher energy efficient mechanism, managed security services, cloud security solutions at one place by offering equivalent and cloud management platform benefits with enormous environmental impact!
• Cloud computing, is an important facet for any IT operations of any organization, continuous attempts have been made to make it- much “greener”.
• “The green cloud”- certainly a superior marketing label, is employed by organizations for handling environmental considerations and concerns effectively. With contribution, towards the critical business operational goals and reduced costs across the servers, green cloud is most environment friendly initiative.
Q.13. What are the factors of Green Cloud Computing.
Ans:
1. Product longevity:
Gartner maintains that the PC manufacturing process accounts for 70% of the natural resources used in the life cycle of a PC. More recently, Fujitsu released a Life Cycle Assessment (LCA) of a desktop that show that manufacturing and end of life accounts for the majority of this desktop's ecological footprint.
2. Data center design:
Energy efficient data center design should address all of the energy use aspects included in a data center: from the IT equipment to the HVAC equipment to the actual location, configuration and construction of the building.
3. Resource allocation
Algorithms can also be used to route data to data centers where electricity is less expensive. .Larger server centers are sometimes located where energy and land are inexpensive and readily available. Local availability of renewable energy, climate that allows outside air to be used for cooling, or locating them where the heat they produce may be used for other purposes could be factors in green siting decisions.
4. Power management
The Advanced Configuration and Power Interface (ACPI), an open industry standard, allows an operating system to directly control the power-saving aspects of its underlying hardware. This allows a system to automatically turn off components such as monitors and hard drives after set periods of inactivity. In addition, a system may hibernate, when most components (including the CPU and the system RAM) are turned off. ACPI is a successor to an earlier Intel-Microsoft standard called Advanced Power Management
5. Materials recycling
Recycling computing equipment can keep harmful materials such as lead, mercury, and hexavalent chromium out of landfills, and can also replace equipment that otherwise would need to be manufactured, saving further be given for recycling, and they typically sign a non-disclosure agreement.
6. Algorithmic efficiency
The efficiency of algorithms has an impact on the amount of computer resources required for any given computing function and there are many efficiency trade-offs in writing programs. Algorithm changes, such as switching from a slow (e.g. linear) search algorithm to a fast (e.g. hashed or indexed) search algorithm can reduce resource usage for a given task from substantial to close to zero.
Q.14. Write the Comparison of Cloud Computing,Fog computing and Edge Computing.
Ans:
Q.15. What is AWS and its advantages and disadvantages?
Ans:
AWS stands for Amazon Web Services, which is a comprehensive cloud computing platform offered by Amazon. It provides a wide range of services and tools for computing power, storage, databases, networking, analytics, machine learning, and more. AWS is known for its scalability, flexibility, and global infrastructure, allowing businesses and individuals to leverage cloud resources to meet their specific needs.
Advantages of AWS:
• Scalability: AWS offers on-demand scalability, allowing users to easily scale their resources up or down based on demand. This flexibility helps businesses handle variable workloads and avoid overprovisioning or under provisioning resources.
• Global Infrastructure: AWS has a vast network of data centers located worldwide, enabling businesses to deploy their applications and services close to their target audience. This global infrastructure provides low-latency performance and improved user experience.
• Broad Service Portfolio: AWS offers a wide range of services, including computing power, storage, databases, AI/ML, analytics, security, and more. This extensive service catalog provides users with the flexibility to choose the services that best suit their specific requirements.
• Reliability and Resilience: AWS is designed to provide high availability and reliability. It offers redundant infrastructure, automatic data replication, backup services, and fault-tolerant architecture, ensuring minimal downtime and data loss.
• Security: AWS has robust security measures in place to protect customer data and applications. It provides various security features, including identity and access management (IAM), encryption, monitoring, and compliance certifications, helping users meet their security and compliance requirements.
Disadvantages of AWS:
• Complexity: The vast array of services and features offered by AWS can make it complex for users, especially those who are new to cloud computing. Understanding and navigating the various services may require a learning curve.
• Cost Management: While AWS offers cost-effective options, managing costs can be challenging, especially if resources are not properly optimized or monitored. Users need to carefully plan and monitor their resource usage to avoid unexpected expenses.
• Vendor Lock-In: As AWS is a proprietary cloud platform, there is a risk of vendor lock-in, where users become heavily dependent on AWS-specific technologies and may face difficulties migrating to another cloud provider in the future.
• Support: While AWS provides extensive documentation and support resources, some users may find it challenging to get personalized support or may need to rely on third-party resources for specific assistance.
Q.16. Explain AWS Architecture.
Ans:
• It is considered as the basic structure of AWS architecture or AWS EC2. Simply, EC2 is also called Elastic Compute cloud which will allow the clients or else the users of using various configurations in their own project or method as per their requirement.
• There are also different amazing options such as pricing options, individual server mapping, configuration server, etc. S3 which is present in the AWS architecture is called Simple Storage Services. By using this S3, users can easily retrieve or else store data through various data types using Application Programming Interface calls. There will be no computing element for the services as well.
1. Load Balancing:
The load balancing is a component of the AWS architecture which helps to enhance the application and the server’s efficiency in the right way. According to the diagrammatic representation of AWS architecture, this Hardware load balancer is mostly used as the common network appliance and helps to perform skills in the architectures of the traditional web applications.
It also makes sure to deliver the Elastic Load Balancing Service, AWS takes the traffic gets distributed to EC2 instances across the various available sources. Along with this, it also distributes the traffic to dynamic addition and the Amazon EC2 hosts removals from the load-balancing rotation.
2. Elastic Load Balancing
This load balancing can easily shrink and increase the capacity of load balancing by tuning some of the traffic demands and supporting sticky sessions to have advanced routing services.
3.Amazon Cloud Front
Amazon Cloud Front is mostly used for the delivery of content that is directly used for website delivery. The content in the Amazon Cloud Front can also be the type of content such as static, dynamic as well as streaming content that can also take the usage of global network locations as well. From the user end, the content can be requested in an automatic way based on the nearest location that also shows the diverse effect on the performance which will be enhanced in the right way. There will be no commitments in the monthly wise and the contracts.
4.Secuity Management
It also makes sure to provide a security feature namely known as security groups. It will also work the same as the inbound network firewall and will also have to specify the ports, protocols, and also source IP ranges where all these can be reached to the EC2 instances. With the help of specific subnets or else IP addresses, the security groups can be configured that can also limit the access to EC2 instances effectively.
5.Elastic Cache
Amazon Elastic Cache is an efficient web service where the memory cache can be managed in the cloud with ease. This cache plays a vital role in terms of memory management and will also help to reduce the service's load in a reliable manner. It also makes sure to enhance the performance along with the scalability on the tier of the database by caching the information which is used in a frequent manner.
6.Amazon RDS
Amazon Relational Database Service helps to deliver the same access that is similar to the MySql, Microsoft SQL Server database engine or else Microsoft SQL. These applications, queries, and tools will be useful in the Amazon RDS as well.
Q.17. Explain AWS Well-Architecture Framework.
Ans:
The AWS Well-Architected Framework consists of five key pillars that help guide the design and evaluation of architectures built on AWS. These pillars are:
1. Operational Excellence: This pillar focuses on optimizing operations and continuously improving processes and procedures. It involves automating tasks, monitoring system health, and responding to events efficiently. It also emphasizes the ability to understand and manage the workload and resources effectively.
2. Security: The security pillar focuses on protecting data, systems, and assets. It involves implementing appropriate security controls, managing access and identity, encrypting sensitive data, and establishing secure communication channels. It also emphasizes the importance of regular security assessments and incorporating security best practices.
3. Reliability: The reliability pillar ensures that systems are designed to recover from failures and withstand disruptions. It involves implementing measures such as fault tolerance, redundancy, and backup mechanisms. It also includes techniques for testing and validating system behavior under different scenarios and ensuring high availability and fault tolerance.
4. Performance Efficiency: This pillar focuses on optimizing the use of computing resources to achieve maximum performance and cost efficiency. It involves selecting the appropriate instance types, optimizing storage, and designing for scalability. It also emphasizes monitoring and fine-tuning system performance to achieve optimal resource utilization.
5. Cost Optimization: The cost optimization pillar focuses on optimizing costs without sacrificing performance, reliability, or security. It involves understanding and managing costs, monitoring resource usage, and utilizing cost-effective architectures and services. It also emphasizes the importance of regularly evaluating cost optimization opportunities and making informed decisions to optimize the cost-efficiency of the system.
Q.18. What is google app engine explain its advantages and disadvantages?
Ans:
Google App Engine is a fully managed platform as a service (PaaS) offered by Google Cloud Platform (GCP). It allows developers to build and deploy web applications and services without the need to manage infrastructure or servers. Here are the advantages and disadvantages of Google App Engine:
Advantages of Google App Engine:
1. Scalability and Automatic Resource Management: App Engine automatically scales the application based on the incoming traffic and workload. It can handle sudden spikes in traffic without manual intervention, ensuring high availability and performance.
2. Serverless Architecture: With App Engine, developers can focus on writing code and building applications without worrying about server management. The underlying infrastructure is abstracted away, allowing developers to focus on application logic rather than infrastructure concerns.
3. Easy Deployment and Management: Google provides a streamlined deployment process, making it easy to deploy applications to App Engine. It handles application updates and provides built-in monitoring and logging tools for application management and troubleshooting.
4. Multi-Language Support: App Engine supports multiple programming languages, including Python, Java, Node.js, Ruby, Go, and more. Developers can choose their preferred language and frameworks to build their applications.
5. Integration with Google Services: App Engine integrates seamlessly with other Google Cloud services, such as Cloud Storage, Datastore, Pub/Sub, and Cloud SQL. This allows developers to leverage additional services for storage, databases, messaging, and more, enhancing the functionality of their applications.
Disadvantages of Google App Engine:
1. Limited Flexibility: App Engine abstracts away much of the underlying infrastructure, which can limit the flexibility and customization options for developers who require fine-grained control over the environment or have specific infrastructure requirements.
2. Vendor Lock-In: Since App Engine is a proprietary platform, there is a potential risk of vendor lock-in. Migrating applications from App Engine to another platform may require significant effort and potentially rewrite parts of the application to be compatible with the new platform.
3. Limited Runtime Environment: While App Engine supports multiple programming languages, it may not support all language features or frameworks. Developers may face limitations when using specific libraries or frameworks that are not fully compatible with the App Engine runtime environment.
4. Performance Trade-offs: While App Engine automatically scales applications, the automatic scaling mechanism may introduce slight latency or response time delays due to the time required for scaling and spinning up new instances. Fine-tuning performance for specific use cases may require additional configuration and optimization.
Q.19. What is Azure and its advantages and disadvantages?
Ans:
Azure is a cloud computing platform offered by Microsoft. It provides a wide range of services and tools for building, deploying, and managing applications and services in the cloud. Here are the advantages and disadvantages of Azure:
Advantages of Azure:
1. Comprehensive Service Portfolio: Azure offers a vast array of services, including virtual machines, databases, storage, AI/ML, analytics, networking, and more. This extensive service catalog provides users with a wide range of options to meet their specific needs.
2. Hybrid Capabilities: Azure provides strong support for hybrid cloud scenarios, allowing businesses to seamlessly integrate their on-premises infrastructure with the cloud. This hybrid capability enables organizations to extend their existing investments and resources into the cloud environment.
3. Global Presence: Azure operates in a large number of regions worldwide, providing users with the ability to deploy applications and services closer to their target audience. This global footprint ensures low-latency performance and improved user experience.
4. Scalability and Elasticity: Azure allows users to easily scale their resources up or down based on demand. It provides features such as virtual machine scale sets, Azure Functions, and Azure App Service that enable automatic scaling, ensuring optimal performance and cost efficiency.
5. Integration with Microsoft Ecosystem: Azure seamlessly integrates with other Microsoft products and services, such as Active Directory, Office 365, and Dynamics 365. This integration simplifies management, identity and access management, and provides a unified experience for users already utilizing Microsoft technologies.
Disadvantages of Azure:
1. Complexity: Azure, similar to other cloud platforms, can have a steep learning curve, especially for users new to cloud computing. The vast array of services and features, along with their configurations and interdependencies, can be complex to navigate and understand.
2. Cost Management: While Azure offers cost-effective options, managing costs can be challenging. Users need to carefully plan and monitor their resource usage to avoid unexpected expenses. Azure provides cost management tools, but proper monitoring and optimization are necessary to control costs effectively.
3. Support: Azure provides support resources and documentation, but some users may face challenges in getting personalized or timely support. Depending on the level of support required, additional costs may be incurred for premium support plans.
4. Vendor Lock-In: As with any cloud provider, there is a risk of vendor lock-in when heavily dependent on Azure-specific technologies and services. Migrating applications or services to another cloud provider or on-premises infrastructure may require significant effort and potentially involve application modifications.
 |
