AWS Vs Azure comparison
AWS Vs Azure comparison for services
Above all, with AWS Vs Azure comparison helps you understand how Microsoft Azure services compare to Amazon Web Services (AWS). For instance, whether you are planning a multi-cloud solution with Azure and AWS, or migrating to Azure, you can compare the IT capabilities of Azure and AWS services in all categories.
In addition, AWS Vs Azure comparison allows you can use to build your modern application in the AWS Cloud. Hence, AWS has its own merits. Thus, AWS is the fastest growing cloud platform.
AWS Vs Azure comparison. For example, like AWS, Microsoft Azure is built around a core set of compute, storage, database, and networking services. Therefore, in many cases, both platforms offer a basic equivalence between the products and services they offer. Furthermore, both AWS and Azure allow you to build highly available solutions based on Windows or Linux hosts. Thus, if you’re used to development using Linux and OSS technology, both platforms can do the job.
Above all. while the capabilities of both platforms are similar, the resources that provide those capabilities are often organized differently. For instance, exact one-to-one relationships between the services required to build a solution are not always clear. Moreover, in other cases, a particular service might be offered on one platform, but not the other. For example, see charts of comparable Azure and AWS services.
For instance, learn from AWS experts. Consequently, advance your skills and knowledge. In addition, build your future in the AWS Cloud. In addition, Azure and AWS for multi-cloud solutions.
Furthermore, as the leading public cloud platforms, Azure and AWS each offer a broad and deep set of capabilities with global coverage. For example, many organizations choose to use both platforms together for greater choice and flexibility. In addition, to spread their risk and dependencies with a multi-cloud approach. Furthermore, consulting companies and software vendors might also build on and use both Azure and AWS, as these platforms represent most of the cloud market demand. Therefore, you can do any of the following:
| AWS service | Azure service | Description |
|---|---|---|
| AWS Marketplace | Azure Marketplace | For instance, easy-to-deploy and automatically configured third-party applications, including single virtual machine or multiple virtual machine solutions. |
AWS Certified Solutions Architect Learning Path: AWS Vs Azure comparison
Hence, this path, for instance, includes the optional course Architecting on AWS – Accelerator. In addition, this course covers topics from two other courses in this path. Hence, Architecting on AWS and Advanced Architecting on AWS, and may be taken in place of those courses.
AI and machine learning
| AWS service | Azure service | Description |
|---|---|---|
| SageMaker | Machine Learning | Moreover, a cloud service to train, deploy, automate, and manage machine learning models. |
| Alexa Skills Kit | Bot Framework | Moreover, build and connect intelligent bots that interact with your users using text/SMS, Skype, Teams, Slack, Office 365 mail, Twitter, and other popular services. |
| Lex | Speech Services | In addition, API capable of converting speech to text, understanding intent, and converting text back to speech for natural responsiveness. |
| Lex | Language Understanding (LUIS) | Above all, allows your applications to understand user commands contextually. |
| Polly, Transcribe | Speech Services | Hence, enables both Speech to Text, and Text into Speech capabilities. |
| Rekognition | Cognitive Services | Computer Vision: For instance, extract information from images to categorize and process visual data. Face: For instance, Detect, identify, and analyze faces in photos. Emotions: For example, Recognize emotions in images. |
| Skills Kit | Virtual Assistant | For instance, the Virtual Assistant Template brings together a number of best practices we’ve identified through the building of conversational experiences. In addition, it automates integration of components |
Big data and analytics: AWS Vs Azure comparison
Data warehouse
| AWS service | Azure service | Description |
|---|---|---|
| Redshift | Synapse Analytics | For example, Cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data. |
| Lake Formation | Data Share | Therefore, a simple and safe service for sharing big. data |
Big data processing
| AWS service | Azure service | Description |
|---|---|---|
| EMR | Databricks | For instance, Apache Spark-based analytics platform. |
| EMR | HDInsight | In addition, managed Hadoop service. Deploy and manage Hadoop clusters in Azure. |
| EMR | Data Lake Storage | Whereas, massively scalable, secure data lake functionality built on Azure Blob Storage. |
Above all, learn the fundamentals of identifying AWS services so that you can make informed decisions about IT solutions based on your business requirements.
Data orchestration / ETL
| AWS service | Azure service | Description |
|---|---|---|
| Data Pipeline, Glue | Data Factory | Moreover, processes and moves data between different compute and storage services, as well as on-premises data sources at specified intervals. Furthermore, create, schedule, orchestrate, and manage data pipelines. |
| Glue | Data Catalog | Above all, it is a fully managed service that serves as a system of registration and system of discovery for enterprise data sources |
| Dynamo DB | Table Storage, Cosmos DB | Whereas, NoSQL key-value store for rapid development using massive semi-structured datasets. |
Analytics and visualization: AWS Vs Azure comparison
Therefore, analytics and visualization with AWS tools like Athena and Glue are helpful. Thus, it is highly recommended to use them.
| AWS service | Azure service | Description |
|---|---|---|
| Kinesis Analytics | Stream Analytics Data Lake Analytics Data Lake Store | Moreover, storage and analysis platforms that create insights from large quantities of data, or data that originates from many sources. |
| QuickSight | Power BI | Nevertheless, business intelligence tools that build visualizations, perform ad hoc analysis, and develop business insights from data. |
| CloudSearch | Cognitive Search | In addition, delivers full-text search and related search analytics and capabilities. |
| Athena | Data Lake Analytics | Hence, provides a serverless interactive query service that uses standard SQL for analyzing databases. |
In addition, learn the fundamentals of building IT infrastructure on AWS so you can build scalable and resilient solutions in the cloud.
Compute: AWS Vs Azure comparison
Virtual servers
| AWS service | Azure service | Description |
|---|---|---|
| Elastic Compute Cloud (EC2) Instances | Virtual Machines | For example, virtual servers allow users to deploy, manage, and maintain OS and server software. Moreover, instance types provide combinations of CPU/RAM. Users pay for what they use with the flexibility to change sizes. |
| Batch | Batch | In addition, run large-scale parallel and high-performance computing applications efficiently in the cloud. |
| Auto Scaling | Virtual Machine Scale Sets | Above all, allows you to automatically change the number of VM instances. In addition, you set defined metric and thresholds that determine if the platform adds or removes instances. |
| VMware Cloud on AWS | VMware by CloudSimple | In addition, redeploy and extend your VMware-based enterprise workloads to Azure with Azure VMware Solution by CloudSimple. Moreover, keep using the VMware tools you already know to manage workloads on Azure without disrupting network, security, or data protection policies. |
| Parallel Cluster | CycleCloud | Moreover, create, manage, operate, and optimize HPC and big compute clusters. Therefore, they can be of any scale. |
Containers and container orchestrators: AWS Vs Azure comparison
| AWS service | Azure service | Description |
|---|---|---|
| Elastic Container Service (ECS) Fargate | Container Instances | Moreover, Azure Container Instances is the fastest and simplest way to run a container in Azure. After all, without having to provision any virtual machines or adopt a higher-level orchestration service. |
| Elastic Container Registry | Container Registry | As a result, allows customers to store Docker formatted images. Furthermore, it is used to create all types of container deployments on Azure. |
| Elastic Kubernetes Service (EKS) | Kubernetes Service (AKS) | Above all, deploy orchestrated containerized applications with Kubernetes. Therefore, simplify monitoring and cluster management through auto upgrades and a built-in operations console. |
| App Mesh | Service Fabric Mesh | In addition, fully managed service that enables developers to deploy microservices applications without managing virtual machines, storage, or networking. |
Database: AWS Vs Azure comparison
Above all, database is also important within AWS. Consequently, relational database service and Dynamo DB are great tools.
| Type | AWS | Azure | Description |
|---|---|---|---|
| Relational database | RDS | SQL Database Database for MySQL Database for PostgreSQL | In addition, managed relational database service where resiliency, scale, and maintenance. Above all, these are primarily handled by the platform. |
| NoSQL / Document | DynamoDB SimpleDB Amazon DocumentDB | Cosmos DB | Hence, a globally distributed, multi-model database. Basically, it natively supports multiple data models: key-value, documents, graphs, and columnar. |
| Caching | ElastiCache | Cache for Redis | In addition, an in-memory–based, distributed caching service that provides a high-performance. Therefore, it stores typically used to offload nontransactional work from a database. |
| Database migration | Database Migration Service | Database Migration Service | Therefore, migration of database schema and data from one database format to a specific database technology in the cloud. |
For example, in this AWS Vs Azure comparison, you’ll learn the key differences between the two platforms. Thus, for instance, understand core areas.
DevOps and application monitoring: AWS Vs Azure comparison
In addition, DevOps and application monitoring is equally important. Hence, it is easy to use as well.
| AWS | Azure | Description |
|---|---|---|
| CloudWatch, X-Ray | Monitor | In addition, comprehensive solution for collecting, analyzing, and acting on telemetry from your cloud. In addition from on-premises environments. |
| CodeDeploy CodeCommit CodePipeline | DevOps | Thus, a cloud service for collaborating on code development. |
| Developer Tools | Developer Tools | Furthermore, collection of tools for building, debugging, deploying, diagnosing, and managing multiplatform scalable apps and services. |
| CodeBuild | DevOps | Therefore, fully managed build service that supports continuous integration and deployment. |
| Command Line Interface | CLI PowerShell | Moreover, it is built on top of the native REST API across all cloud services, various programming language-specific wrappers provide easier ways to create solutions. |
| OpsWorks (Chef-based) | Automation | Thus, configures and operates applications, for instance, of all shapes and sizes, and provides templates to create and manage a collection of resources. |
| CloudFormation | Resource Manager VM extensions Azure Automation | In other words, provides a way for users to automate the manual, long-running, error-prone, and frequently repeated IT tasks. |
In addition, while AWS allows a resource to be tagged into multiple resource groups, an Azure resource is always associated with one resource group. For instance, a resource created in one resource group can be moved to another group. Thus, it can only be in one resource group at a time. Hence, resource groups are the fundamental grouping used by Azure Resource Manager.
Furthermore, failures can vary in the scope of their impact. For instance, some hardware failures, such as a failed disk, may affect a single host machine.
In other words, a failed network switch could affect a whole server rack. Moreover, less common are failures that disrupt a whole datacenter, for instance, such as loss of power in a datacenter. Hence, rarely, an entire region could become unavailable.
Above all, one of the main ways to make an application resilient is through redundancy. Therefore, you need to plan for this redundancy when you design the application.
In addition, the level of redundancy that you need depends on your business requirements, for example, not every application needs redundancy across regions to guard against a regional outage. Thus, in general, a tradeoff exists between greater redundancy and reliability versus higher cost and complexity.
For example, in Azure, a region is divided into two or more Availability Zones. For instance, an Availability Zone corresponds with a physically isolated datacenter in the geographic region.
Therefore, Azure has numerous features, for instance, providing application redundancy at every level of potential failure, including availability sets, availability zones, and paired regions.
For instance, the following table summarizes each option.
| Availability Set | Availability Zone | Paired region | |
|---|---|---|---|
| Scope of failure | Rack | Datacenter | Region |
| Request routing | Load Balancer | Cross-zone Load Balancer | Traffic Manager |
| Network latency | Very low | Low | Mid to high |
| Virtual networking | VNet | VNet | Cross-region VNet peering |
Availability sets
Moreover, to protect against localized hardware failures, such as a disk or network switch failing, for instance, deploy two or more VMs in an availability set. For instance, an availability set consists of two or more fault domains that share a common power source and network switch in AWS Vs Azure comparison
Therefore, VMs in an availability set are distributed across the fault domains. In addition, so if a hardware failure affects one fault domain, network traffic can still be routed to the VMs in the other fault domains. For example, for more information about Availability Sets, see Manage the availability of Windows virtual machines in Azure. Therefore, Azure is a great cloud platform. In addition, it is easy to use.
Moreover, when VM instances are added to availability sets, they are also assigned an update domain. For example, an update domain is a group of VMs that are set for planned maintenance events at the same time. Therefore, distributing VMs across multiple update domains ensures that planned update and patching events affect only a subset of these VMs at any given time in AWS Vs Azure comparison
In addition, availability sets should be organized by the instance’s role in your application to ensure one instance in each role is operational. For example, in a three-tier web application, create separate availability sets for the front-end, application, and data tiers.
Moreover, learn more about our AWS Certification courses and DevOps Engineer E-Degree program
