Describe Azure Database, IoT, ML, AI & DevOps services Flashcards
Azure Cosmos DB
-Globally distributed NoSQL (semi-structured data) Database service
-Schema-less
-Collections instead of “tables”
-Ability to replicate geographically
-Ability to read and write globally
-Multiple APIs (SQL, MongoDB, Cassandra, Gremlin, Table Storage)
Designed for:
-Highly responsive (real time) applications with super low latency responses <10ms
-Multi-regional applications
Azure SQL - Product Family
-Azure SQL Database – Reliable relational database based on SQL Server
-Azure Database for MySQL – Azure SQL version for MySQL database engine
-Azure Database for PostgreSQL – Azure SQL version for PostgreSQL database engine
-Azure SQL Managed Instance – Fully fledged SQL Server managed by cloud provider
-Azure SQL on VM – Fully fledged SQL Server on IaaS
-Azure SQL DW (Synapse) – Massively Parallel Processing (MPP) version of SQL Server
Azure SQL Database
-Build apps faster on a fully managed SQL database
-Relational database service in the cloud (PaaS) (DBaaS - Database as a Service)
-Structured data service defined using schema and relationships
-Rich Query Capabilities (SQL)
-High-performance, reliable, fully managed and secure database for building - applications
Azure IoT Hub
-Managed service for bi-directional communication
-Platform as a Service (PaaS)
-Highly secure, scalable and reliable
-Integrates with a lot of Azure Services
-Programmable SDKs for popular languages (C, C#, Java, Python, Node.js)
-Multiple protocols (HTTPS, AMQP, MQTT)
Azure IoT Central
-IoT App Platform - Software as a Service (SaaS)
-Industry specific app templates
-No deep technical knowledge required
-Service for connecting, management and monitoring IoT devices
-Highly secure, scalable and reliable
-Built on top of the IoT Hub service and 30+ other services
Azure Sphere
Is a secured, high-level application platform with built-in communication and security features for internet-connected devices.
Secure end-2-end approach to build secure IoT Solutions:
-Azure Sphere certified chips (microcontroller units - MCUs)
-Azure Sphere OS based on Linux
-Azure Security Service trusted device-to-cloud communication
Azure Synapse Analytics
Is an enterprise analytics service that accelerates time to insight across data warehouses and big data systems.
-Big data analytics platform (PaaS)
Multiple components:
-Azure Data Explorer for log and time series analytics
-Apache Spark technologies for big data
-Synapse SQL - SQL technologies used in enterprise data warehousing
–SQL pools (dedicated – pay for provisioned performance)
–SQL on-demand (ad-hoc – pay for TB processed)
-Synapse Pipelines (Data Factory – ETL)
-Studio (unified experience)
Azure Data Factory
Azure Data Factory is a cloud-based data integration service. It allows you to create, schedule, and manage data-driven workflows for moving data between supported data stores. Azure Data Factory is a key component of Azure’s data platform and is commonly used for ETL (Extract, Transform, Load) and data integration tasks.
Azure HDInsight
Is a full-spectrum, managed cluster platform which simplifies running big data frameworks in large volume and velocity
-Flexible multi-purpose big data platform (PaaS)
-Effortlessly process massive amounts of data and get all the benefits of the broad open-source project ecosystem
-Multiple technologies supported (Hadoop, Spark, Kafka, HBase, Hive, Storm, Machine Learning)
Azure Databricks
-Fully managed first-party service that enables an open data lakehouse in Azure
-Big data collaboration platform (PaaS)
-Unified workspace for notebook, cluster, data, access management and collaboration
-Based on Apache Spark
-Integrates very well with common Azure data services
Azure Machine Learning Studio
-Cloud-based platform for creating, managing and publishing machine learning models
-Platform as a Service (PaaS)
-Machine Learning Workspace – top level resource
-Machine Learning Studio – web portal for end-2-end development
Features:
-Notebooks – using Python and R
-Automated ML – run multiple algorithms/parameters -combinations, choose the best model
-Designer – graphical interface for no-code development
-Data & Compute – management of storage and compute resources
-Pipelines – orchestrate model training, deployment and management tasks
Azure Cognitive
Is a set of cloud-based APIs that you can use in AI applications and data flows. It provides pretrained models that are ready to use in your applications, requiring no data and no model training on your part.
Key benefits:
-Minimal development effort for state-of-the-art AI services. Use predefined algorithms or create custom algorithms on top of pre-built libraries.
-Easy integration into apps via HTTP REST interfaces.
-Developers and data scientists of all skill levels can easily add AI capabilities to apps.
Azure Logic Apps
-Serverless enterprise integration service (PaaS)
-Deploy and run Logic Apps anywhere to increase scale and portability while automating business-critical workflows anywhere
-200+ connectors for popular services
Designed for orchestration of: business processes, integration workflows for applications, data, systems and services
-No-code solution
Azure Event Grid
-Fully managed serverless event routing service
-Uses publish-subscribe model
-Designed for event-based and near-real time applications
-Supports dozen of built-in events from most common Azure services
Azure DevOps
DevOps aims to shorten the development life cycle by providing continuous integration and delivery (CI/CD) capabilities while ensuring high quality of deliverables.
-Collection of services for building solutions using DevOps practices
Services included:
-Boards – tracking work
-Pipelines – building CI/CD workflows (build, test and deploy apps)
-Repos – code collaboration and versioning with Git
-Test Plans – manual and exploratory testing
-Artifacts – manage project deliverables
-Extensible with Marketplace – over 1000 of available apps
-Evolved from TFS (Team Foundation Server), through VSTS (Visual Studio Team Services)
