Other Azure Services

Web

Azure Notification Hubs
- Send push notifications to any platform from any back end.
Azure API Management
- Publish APIs to developers, partners, and employees securely and at scale.
Azure Cognitive Search
- Fully managed search as a service.
Azure SignalR Service
- Add real-time web functionalities easily.

Internet allows any item that’s online-capable to access valuable information
- This ability is for devices to garner & relay information for data analysis is called Internet of Things (IoT).
- E.g. smart watches, smart thermostats, smart refrigerators. Personal computers used to be the norm.
IoT Central
- 📝 SaaS to manage IoT devices
Azure IoT Hub
- Takes data, coordinates in and out
- Integrates sensors, devices and manages them.
- Messaging hub that provides secure communications between and monitoring of devices
- IoT Edge
  - Allows pushing data analysis models directly onto IoT devices
  - Allowing them to react quickly to state changes without needing to consult cloud-based AI models.

Big Data = large volumes of data
- E.g data from weather systems, communications systems, genomic research, imaging platforms
Hard to analyze and make decisions
- Traditional forms of processing and analysis becomes no longer appropriate.
- Solution: Open source cluster technologies
Azure supports a broad range of technologies and services to provide big data and analytic solutions.
📝 Some examples
- Azure Synapse Analytics
- Azure HDInsight
  - Process big data through Hadoop clusters
  - More complete than Azure Data Lake Analytics
- Azure Data Lake Analytics
  - Transform big data on Azure data lake
- Azure Databricks
  - Apache Spark–based analytics service
  - Can be integrated with other Big Data services in Azure.
- Data Lake Store
  - Secure, massively scalable and built to the open HDFS standard
- Azure Data Factory
  - Pipelines for data analysis

The core is Machine Learning.
- Allows computers to use existing data to forecast future behaviors, outcomes, and trends.
- Computers learn without being explicitly programmed.
Forecasts or predictions can make apps and devices smarter.
- E.g. when you shop online, machine learning helps recommend other products you might like based on what you’ve purchased.

Cloud-based environment you can use to develop, train, test, deploy, manage, and track machine learning models.
Can auto-generate a model and auto-tune it for you.
Lets you start training on your local machine, and then scale out to the cloud

📝 AI SaaS services (pre-built APIs)
Vision: Image-processing algorithms to smartly identify, caption, index, and moderate your pictures and videos.
Speech: Convert spoken audio into text, use voice for verification, or add speaker recognition to your app.
Knowledge mapping: Map complex information and data in order to solve tasks such as intelligent recommendations and semantic search.
Bing Search: Add Bing Search APIs to your apps and harness the ability to comb billions of webpages, images, videos, and news with a single API call.
Natural Language processing: Allow your apps to process natural language with pre-built scripts, evaluate sentiment and learn how to recognize what users want.

Collaborative, drag-and-drop visual workspace for machine learning solutions
Allows to build, test, and deploy machine learning models with algorithms and data-handling modules

Brings together people, processes, and technology, automating software delivery to provide continuous value to your users.

📝 Azure DevOps Services (formerly known as Visual Studio Team Services, or VSTS)
Provides development collaboration tools including pipelines, Git repositories, configurable Kanban boards, and automated load testing
- Consists of:
  - Azure Repos: Source control for your code.
  - Azure Pipelines: providing build & release services for continuous integration & delivery
  - Azure Boards: Agile tools that support planning and tracking work items
  - Azure Test Plans: Tools for testing your applications
  - Azure Artifacts: Allows teams to work with maven, npm and NuGet packages, like purpose as artifactory

📝 Creates labs consisting of pre-configured Windows & Linux environments or Azure Resource Manager templates.
Good for testing can use to test or demo your applications directly from your deployment pipelines.