Microsoft Azure – Handy Cloud to Operate and Develop In

Microsoft is the second largest cloud provider on the market. Microsoft Azure cloud offers rich PaaS functionality and integrable SaaS products beneficial for:

SaaS Startups

Achieving faster time to market due to Azure’s compoundable services.

Small and mid-sized businesses

Getting automated migration and infrastructure construction with Azure’s PaaS services.

Businesses using Microsoft products in-house

Which then benefit from lift-and-shift migrations of their IT infrastructures to Azure.

Featured Services of Microsoft Azure

Cloud computing
Azure Functions

Serverless event- and request- triggered computing at scale with declarative access to Azure’s and third-party services.

Azure CycleCloud

Dynamically scaled computing, networking and caching environment for high-performance data processing.

Virtual Machine Scale Sets

Centralized management of autoscaled and dynamically balanced virtual machines for large workloads and big data.

Azure VMware Solution

VMware-compatible service for migration and management of your sets of VMs at scale.


Container Instances

Running scalable isolated containers (ACIs) in Azure’s serverless environment.

Azure Kubernetes Service

A native Kubernetes orchestration tool integrable with multiple Azure development services.

Azure Red Hat OpenShift

Running OpenShift container clusters in Azure environment managed by Microsoft and Red Hat.

Azure Service Fabric

Cross-platform service to arrange and manage containers with on-demand scalability.


Azure SQL Database

Building scalable relational databases.

Azure Cosmos DB

Fast clustered NoSQL database with multi-model sub-DBs deployed in each cluster for horizontal scalability.

Azure Cache for Redis

Management of distributed Redis server instances yielding low latencies through caching.

Azure Database for MySQL/ PostgreSQL/MariaDB

Virtualization services to implement scalable databases

Azure Database Migration Service

DB migration wizard for automated migration of workloads.

Common Use Cases for Microsoft Azure

Enterprise cloud
  • Semi-automated migration and hosting of legacy apps.
  • Platform for cloud-native applications.
  • Data warehouse and data lake.
  • Building advanced solutions with off-the-shelf services: AI, big data, IoT, blockchain, computer vision, etc.
  • Native integration with Microsoft products: Office 365, Dynamics 365, Power BI.
  • Perimeter and intra-component firewalls, monitoring and security automation tools.
Enterprise multi-cloud
  • Virtual networking bridging services (VPN, Virtual WAN, Private Link).
  • Single-point infrastructure management via Azure Arc.
  • Native SIEM and SOAR solutions (Azure Security Center, Azure Sentinel).
  • Identity and access management via Azure Active Directory for federated authentication.
Hybrid enterprise cloud
  • Synchronization of on-premises Azure environments, services and clients with the Azure cloud.
  • Single-spot management of extensively evolving IT infrastructures with Azure Resource Manager.
  • Global content delivery and edge cloud computing.
  • Unified security management for cloud and on-premises IT components.
SaaS, XaaS applications
  • Numerous cloud services for app enrichment: AI, analytics, computer vision, IoT and blockchain.
  • Globally spread content delivery network.
  • Low latency on-demand computing for better end user experience.
  • Scalable serverless data storage.
  • CI/CD and IaC services for web and mobile development.
  • Native containerization services and orchestration tools.
DWH and data analytics
  • DWH and analytics management in a single point – Azure Synapse Analytics.
  • Implementation of serverless and virtualized DBs.
  • Big data.
  • Building ML models with no technical expertise required.
  • Automated database migration.
Big data
  • Aggregation and storage of unstructured and structured data in Azure Synapse Analytics.
  • Azure Data Lake Storage
  • Cosmos DB – scalable and globally available DB structures.
  • Real-time big data processing with Azure Stream Analytics and Spark-driven Azure Databricks.
  • Open-source data analytics engines plugged via HDInsight: (Apache Hadoop, Spark, and Kafka).
Computer vision and mixed reality
  • Object recognition and data extraction services.
  • Gear-driven SDKs for spatial computing.
  • APIs for computer vision with a rich portfolio of use scenarios.
  • IoT devices controlled and connected to Azure services through Azure IoT Hub.
  • Intelligent analytics for live and logged IoT data in Azure Time Series Insights.
  • Hardware and software IoT security.
HIPAA-compliant cloud
  • Encryption of data in transit and at rest.
  • Native SIEM, perimeter and component-level security and access management services.
  • FHIR-compliant APIs for secure data exchange