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Other Azure Services
- 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 of things
- 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.
Azure Machine Learning Service
- 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
Azure Cognitive services
- 📝 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.
Azure Machine Learning Studio
- 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
NuGet packages, like purpose as artifactory
Azure DevTest Labs
- 📝 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.