AWS and Azure are most comprehensive cloud platform. Recently, I have gone through a video which explains fundamentals of Azure and AWS cloud platform. If you are AWS professional, then your knowledge of AWS platform makes it easier for you to start your journey with Azure. The learning curve is not very huge. In this post, we will see how you can transfer the fundamental knowledge of Amazon AWS platform to Microsoft Azure.
This post is based on the 5-minute comparison video by Matt McSpirit. He explains how your knowledge as an AWS Professional easily translates to Microsoft Azure. Get the critical differences between these two comprehensive cloud platforms in the 5 minutes video. This post is an Azure Beginners Guide for AWS Professionals.
Key Concepts of AWS and Azure
Fundamental differences of AWS and Azure are the concepts of subscriptions and accounts. In Azure account owner can delegate the task of managing subscription to application owners. This delegation is essential when the person is paying the bill not the person operating the technology. Also, imagine if you could run AWS services in your private Data Center? With Azure, you can deploy Azure services in your data center with Azure stack. Azure also supports first-party integration between your cloud and on-premises solutions.
Common Identity Management and Security Data Platform Artificial Development
Like AWS, Azure Architecture gives you the flexibility to build solutions with Windows and Linux. AWS and Azure have vibrant market place of growing 3rd party echo system of apps and solutions.
Three Pillars of Azure and AWS Cloud Platform
Azure Beginners Guide for AWS Professionals is based on three main pillars of these cloud offering. There are three core services in AWS and Azure cloud platform. I will cover each component in this post as Matt explained in the above video.
Compute Data Storage Management
AWS Vs. Azure Compute Options
Virtual Machine Templates
Compute options are very similar to AWS and Azure. You can find the same range of on-demand virtual machines sizes in Azure and a similar variety of Amazon EC2 instances in AWS. There are some differences in Memory, CPU, and Storage options.
You can create AWS instances of virtual machines in AWS management console. You can create Azure VMs in Azure portal using APIs or Azure Command line inter-phase for Windows or Linux. Following are the variety of options I have captured for Azure Beginners Guide for AWS Professionals.
Azure Virtual Machine Offerings
Small Workloads (A, Av2, B, D, Dv2) General purpose (Dv3, N) Storage workloads (L) Database workload (Ev3) Enterprise applications (M) SAP HANA workloads (SAP)
AWS Virtual Machine Offerings
Accelerated Graphics (P2, G3) Storage Optimized (I3, D2) General purpose (T2, M4) Compute Optimized (C4) Memory Optimized (X1, R3 and R4)
Automatic Scalability Options
In both AWS and Azure, you can use Auto Scaling options to scale your application or service dynamically. This can be done without any downtime for most of the scenarios. In Azure, you can use virtual machine scale sets to add or remove VMs automatically based on the metrics and threshold you define. Where in AWS, AWS CloudFormation can be used to scale your application or services automatically.
In Azure, you can use Azure Resource manager or ARM templates to define the architecture of your application or service for the multi tiered workload. Again, AWS CloudFormation templates can be used to architect your application or services.
Amazon has AWS Elastic (EC2) Container Service for containers. Azure has Azure Container Service (AKS) to provide you the container service options. Use a fully managed Kubernetes container orchestration service or choose other orchestrators. Azure supports both Linux and Windows containers. Azure also offers a range of orchestration options including Kubernetes, Mesosphere DC/OS, and Docker Swarm.
AWS Lambda and AWS API Gateway (plus another services) are the solutions to build and deploy applications in AWS. In Azure, Azure Functions and another platform services are the solutions for Serverless platform. This also includes Azure Logic Apps to model and automate your process workflows visually. Other options for serverless in Azure are Azure Database as a Service and Azure Service Fabric Cluster.
AWS Vs. Azure Data Storage Options
Persistent data storage is the heart of many applications. Azure and AWS offer a range of storage options. AWS Simple Storage Service (AWS S3) is the cloud storage solution in AWS. Where in Azure, you can use Azure Blob Storage as cloud storage solution for your application and services. Storage speed and performance are important to cover in Azure Beginners Guide for AWS Professionals.
In AWS, there is an option to have cold storage using AWS S3 Standard IA. And Amazon Glacier is archival cold storage in AWS. In Azure, this cold storage maps to Azure storage standard COLD (Access tier) and Azure Archival storage.
Relational Database Options
Database options in AWS and Azure also similar. But there is the essential difference which IT Pros need to understand. Amazon offers a verity of AWS Relational Database (AWS RDS) options. In Azure, Azure Relational Database options are Azure SQL Databases, Azure DB for MySQL, and Azure DB for PostgreSQL.
Non Relational Database Options
Azure offers Cosmos DB (Azure Cosmos DB) to build non relational Database for your applications and services. Azure Cosmos DB provides additional features like SQL query, unstructured data, low latency, and Geo replication Where in AWS offers Amazon DynamoDB to have Fast and flexible non relational database service in the cloud.
Traditional Data Warehousing
Traditional Data Warehousing options are available for both AWS and Azure. Amazon AWS offers AWS Redshift database for traditional data warehousing requirements of your applications and services. Where in Azure offers you Azure SQL Data Warehouse solution to meet your application requirements. Similar to AWS Redshift, Azure SQL Date Warehouse is fast, fully managed, and petabyte scale data warehouse.
Big Data Offerings
Amazon and Azure offers Big data analysis offerings as part of their cloud services. AWS offers Amazon Elastic MapReduce (Amazon EMR) for big data analytics including Hadoop framework. Where in Azure offers Azure HDInsights as big data analytics options. HDInsight provides fully managed, full spectrum open-source analytics service for enterprises. There is an additional offer from Azure for Big Data, and that is Azure Data Lake Store. Azure Data Lake Store allows you to store massive unstructured or structured data sets which enables analysis of all your data from one place.
AWS Vs Azure Management Options
Management is an important topic. Azure and AWS offer a variety of options to manage your cloud resources. In AWS, you can start with AWS management console. Azure provides management options through Azure management portal. Management options for both the platform are essential with Azure Beginners Guide for AWS Professionals.
Azure Cloud Shell is an interactive, browser-accessible shell for managing Azure resources.You can also use Azure Cloud Shell for custom troubleshooting. Azure Cloud Shell supports Bash Shell for Linux and PowerShell for Windows workloads. There are other varieties of options available including CloudWatch, CloudTrail, and X-Ray. There are lot other 3rd party solutions for AWS cloud management.
AWS and Azure offer different monitoring options. In AWS, you can use 3rd party analytics engine like Splunk. Azure’s build in monitoring options is log analytics, Azure application insights, etc.
Proactive Resource Optimisation
Azure and AWS provide proactive resource optimisation tools to help you. AWS comes with AWS Trusted Advisor Dashboard. Trusted Advisor helps you to observe best practices for the use of AWS by inspecting your AWS environment and provide proactive resource optimisation. Whereas, Azure provides a complimentary tool called Azure Advisor to provide proactive resource optimisation for your Azure environment.