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Interview questions for Hiring Azure Cloud Engineers (Part 11) Question 51: How much storage can a user with a virtual machine use? Each data disk on a virtual machine can be up to 1 TB in size. The number of data disks you can use depends on the size of the virtual machine. Hashtags: #AzureStorage #VirtualMachine #DataDisk #StorageLimits Question 52: Name three types of disks used by VMs Three types of disks used in VMs are Operating System Disk, Temporary Disk, and Data Disk. Hashtags: #VMDisks #AzureVM #OperatingSystemDisk #DataDisk Question 53: Name two types of cloud services Two common types of cloud services are Public Cloud and Private Cloud. Hashtags: #CloudServices #PublicCloud #PrivateCloud #Azure Question 54: What is BYOL pricing in Azure? BYOL, or "Bring Your Own License," is a pricing model that allows users to bring their own software licenses to Azure, reducing the cost associated with licensing. Hashtags: #BYOL #AzurePricing #SoftwareLicensing #CostReduction Question 55: What is the use of Availability Sets in Azure? Availability Sets are used to ensure high availability and fault tolerance of applications and data by distributing virtual machines across multiple physical servers in a datacenter. #AvailabilitySets #Azure #HighAvailability #FaultTolerance Thank you for exploring these Azure Cloud interview questions. I hope they help you in your hiring process!

Confidential computing is changing the way enterprises think about Cloud adoption. E.g., privacy preserving federated AI workloads. Here's an opportunity on my team to work on foundational technology in this area. You will hone your cloud software architecture skills and enhance them to include cutting edge confidential computing concepts for the Cloud. https://lnkd.in/geGVh4pS

How much are you spending in the cloud? Oh, you don't know? What about moving it to another cloud to save money? Hitachi Vantara can help!!! At its core, FinOps is a three-step process that aims to inform, optimize and operate. We go even further to help you gain full visibility into your cloud spend to simplify your financial management. This ensures costs are aligned with your business goals.  #iworkforhitachivantara #channelpartners #aws #gcp #azure  Check out the video at the link below (click the pic!!)

Scaling in Cloud Environment 🗣 Let us talk about how and when to auto scaling provision to be planned. It is the process of automatically adjusting the compute capacity of an application or service based on demand. This can be done by adding or removing instances, or by changing the configuration of existing instances. Auto scaling can help to improve the performance and availability of applications, while also reducing costs. ✌ There are two main types of auto scaling: dynamic scaling and predictive scaling. 🌟 Dynamic scaling Dynamic scaling is the process of adjusting compute capacity based on real-time demand. This is typically done by monitoring metrics such as CPU utilization, memory usage, or request latency. When a metric exceeds a tertentu threshold, an auto scaling policy will trigger the addition or removal of instances. There are two main types of dynamic scaling policies: Target tracking scaling: This policy scales the compute capacity to a target value for a tertentu metric. For example, you could set a target CPU utilization of 80%. If the CPU utilization falls below 80%, the auto scaling policy will remove instances. If the CPU utilization rises above 80%, the auto scaling policy will add instances. Step scaling: This policy scales the compute capacity in a series of steps. For example, you could set a step scaling policy that adds one instance if the CPU utilization exceeds 80%, and removes one instance if the CPU utilization falls below 60%. Dynamic scaling is a good choice for applications with unpredictable demand patterns. It can help to ensure that applications always have the capacity they need to meet demand, while also avoiding the cost of overprovisioning. 🌟 Predictive scaling Predictive scaling is the process of adjusting compute capacity based on forecasts of future demand. This is typically done by using machine learning algorithms to analyze historical demand data and predict future demand. When a forecast indicates that demand is going to increase, the auto scaling policy will add instances. When a forecast indicates that demand is going to decrease, the auto scaling policy will remove instances. Predictive scaling is a good choice for applications with seasonal or predictable demand patterns. It can help to reduce the cost of overprovisioning, and ensure that applications always have the capacity they need to meet demand. #azuredevops #java #cloud #cloudcomputing #devops #javaarchitect #aiml #azurearchitect #awscloud #googlecloud #techinnovation #cloudarchitecture #multicloud #artificialintelligence 🚌 Do share your experience about Predictive Scaling and how effective it is in the AI world. Thank you 🤝 DM | follow me Vijayakumar Rajendran for more information and learning.

The world of #cloud computing ☁️ Dive into our latest #blog and read all about the top roles of 2023's cloud landscape, and how the range available reflects the industry's massive growth and evolution ⚡ 👇👇👇 https://lnkd.in/e3bh95Fz #Hiring #CloudComputing #DevOps #Recruitment #Engineer #MachineLearning

Cloud computing is involved in many aspects of modern life, and there is a great need for cloud professionals. Whether you’re already involved in the technology industry or looking to take the steps to get started, we wanted to share this great article which touches on some of the cloud-based roles worth looking into! Including cloud security engineering, cloud AI/ML engineerings and more... https://bit.ly/3vORbla #CloudComputing #CloudJobs #CloudBasedRoles

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Virtual machine (VM) migration is a necessary evil in cloud computing and data center management. But it doesn't have to be scary. #cloud #datacenter https://lnkd.in/ecsk5nbh

Are you a #cloud architect, engineer, or neither? We're obtaining engineering certifications that say “architect” and #architecture certifications that say “engineer.” The former is the most common, leading to considerable confusion. A cloud engineer is fundamentally involved in the hands-on aspects of cloud computing, such as the design, development, and maintenance of cloud systems. They are tasked with implementing cloud-based #applications, including coding, ensuring scalability, and managing the technical health of the cloud platform. What's critical to being a cloud engineer is being “hands-on” in dealing with the complexities of cloud systems, databases, #AI, governance, and security. In many cases, there are special engineering disciplines around these subtechnologies, and certainly certifications that address specifics, such as certified cloud #database engineer

Embark on a digital odyssey with Cloud Engineers. Explore their toolkit, triumphs, and how to shape the future of tech. #CloudEngineering #TechJourney