TechnicalRendezvous

Machine Learning: Machine learning is about using existing data to forecast future behaviors outcome and  trends.  Here you without programming you are making computer to learn by training the model (using known data). Based on Model Model can take unknown data and makes prediction. For ML we have Azure Machine learning Studio  Demo Create a machine learning workspace. Launch ML Studio. There are three ways to learn experiment.  Notebook: are jupiter notebook where you can write Python code.  here you load data from data set, You  create experiment, train model and run experiment on computer code.  You see result of experiment on Experiments tab Automated ML :   This is another way to create experiments. This help you find best matching ml alogrithm without even programming it. It's using AI to do Machine learning. Example shown if client will opt for fixed term load. So you can load the data and based on data you get result for Model/Algori...

Azure have many platform solution related to Machine learning AI, BigData and IOT and solution Azure offers. Devices and sensors that are connected to each other and to internet are called IOT(internet of things). Below are some example of IOT. Issues with IOT IOT Services in Azure Azure IOT Central Azure IOT Hub  Azure Sphere Azure IOT Hub is a platform service which provide the building blocks for connecting devices to cloud, managing devices and ingesting data in to service. You can program solution which can enable secure bidirectional communication with million of devices.  You don't have to provision the object that represent the devices in Azure either There is service in IOT hub that can automatically provision devices when they connect to the services so you can deploy devices out in world with less effort.  Example when temperature reaches threshold start the fan. Delivery truck share the traffic data. IOT hub is a platform and it has a different API and SDK for...

 As companies are producing more data than before there is need to store this data and access it anytime from any location. Azure had storage services for various data types. There are many benefits of storing this data in Azure Automated backup and recovery  Replication across world  Encryption option  Security and platform integration  Development feature and support. Managed Relational database in Azure SQL Server With VM You can host a SQL server on a VM that gives you full control. Or you can provision from Azure marketplace by using existing image.  Flexible pricing options are there. You can configure automated backup and automated updates scheduling.  Azure SQL DB Then there is another version of this i.e. platform as a service where you always have a latest version of SQL server running. Flexible pricing model in based on Virtual core or Distributed transaction unit (DTU) i.e. based on usage.  For deployment you can either have single DB ...

Core Products of Azure Azure Compute  On demand compute power which is provided by  VM Containers (more light weight than VM) / Azure App service Serverless Computing   (way to manage app without managing any infra)  Azure function  which allow to run small block of code.Azure logic apps which allow us to   configure workflow in cloud. and Azure event grid Virtual Machine in Azure  It comes under IaaS as you get full control, Downside is you need to manage including patching.  When Creating VM Type of Image There are many images available for windows (2012,2016,2019 etc) and Linux, Windows 10. There are other images also available with different software already installed. for example Windows with SFTP etc. Some other non MS image example are ArcGis Citrix net scaler. You can create your own image and upload it in Azure to use.  Size of Image(RAM processor) While selecting VM there multiple option to choose from based on usage. For ...

   In Cloud you/Client upload and download data and using services you can manipulate that data. These data is stored in data center( physical server with network, cooling). MS is thinking of having DC below oceans. MS makes it cost effective by using something called ITPacs (IT Pre Assembled Components).  This implemented as shipping containers so if they have issue can replace shipping container. Focus areas are Datacenter security/ Cost. There is Virtual/physical security/Biometric/ Approvals to make the data center secure. Azure follows various security standard ISO 27001, HIPAA, FedRAMP, SOC 1 & 2. There is region specific standard and third party Audit. MS focus on Energy Efficacy, infect MS is Carbon neutral by using green energy. Project Natick (40 feet) long underwater data center deployed of cost of Scotland. Concepts of Region and availability. We need to choose a data center, that is a based on where most users are based so request response does not take t...

Let's look Clouds in time perspective. We had earlier data centers in past. Each of these were different in hardware, computing power and even had different operating system. All these servers in data center needed enough resources for different application in peak hours but most of the time they were underutilized.  Later we moved to Virtualization where we had a single virtual host on which we could run multiple virtual machine with hypervisor sitting in between and managing it. But even with Virtualization we had problems like In case of cloud infrastructure provider have pool of resources and different customer use these pooled shared resources. They don't care about the details of server, but just the provider makes sure that enough demanded resources are available. On cloud we have on demand Self service so customer pay for resources per user or per hour/minute based on which service/resource they are using. Provisioning is fully automated and provided instantly.  Here O...