A Cloud Services Cheat Sheet for AWS, Azure, and Google Cloud
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Cloud/DevOps Handbook EDITOR'S NOTE AI AND MACHINE LEARNING ANALYTICS APPLICATION INTEGRATION BUSINESS APPLICATIONS COMPUTE CONTAINERS COST CONTROLS DATABASES DEVELOPER TOOLS IoT MANAGEMENT AND GOVERNANCE MIGRATION MISCELLANEOUS A cloud services cheat sheet for AWS, NETWORKING Azure, and Google Cloud SECURITY STORAGE DECEMBER 2020 EDITOR'S NOTE HOME EDITOR'S NOTE cloud directories—a quick reference sheet for what each AI AND MACHINE A cloud services LEARNING vendor calls the same service. However, you can also use this as a starting point. You'll ANALYTICS cheat sheet for need to do your homework to get a more nuanced under- APPLICATION AWS, Azure and standing of what distinguishes the offerings from one an- INTEGRATION other. Follow some of the links throughout this piece and take that next step in dissecting these offerings. BUSINESS Google Cloud APPLICATIONS That's because not all services are equal—each has its —TREVOR JONES, SITE EDITOR own set of features and capabilities, and the functionality COMPUTE might vary widely across platforms. And just because a CONTAINERS provider doesn't have a designated service in one of these categories, that doesn't mean it's impossible to achieve the COST CONTROLS same objective. For example, Google Cloud doesn't offer an DATABASES AWS, MICROSOFT AND GOOGLE each offer well over 100 cloud explicit disaster recovery service, but it's certainly capable services. It's hard enough keeping tabs on what one cloud of supporting DR. DEVELOPER TOOLS offers, so good luck trying to get a handle on the products Here is our cloud services cheat sheet of the services IoT from the three major providers. available on AWS, Google Cloud and Azure. The list is bro- Even trying to compare what's available in each cloud ken down by category to help you start your cross-cloud MANAGEMENT AND GOVERNANCE can quickly get convoluted, since naming conventions vary analysis. n by vendor and service. For example, you can be forgiven MIGRATION for not knowing AWS Fargate, Microsoft Azure Container MISCELLANEOUS Instances and Google Cloud Run all essentially serve the Editor's note: Cloud services are constantly evolving. All infor- same purpose. mation in this cheat sheet is up to date as of publication. We will NETWORKING So, if you ever feel at a loss for what's what, hopefully this periodically update the list to reflect the ongoing changes across SECURITY cloud services cheat sheet will help. Consider it a guide for all three platforms. STORAGE COVER IMAGE: METAMORWORKS/GETTYIMAGES A CLOUD SERVICES CHEAT SHEET FOR AWS, AZURE AND GOOGLE CLOUD • DECEMBER 2020 2 AI and machine learning HOME AWS AZURE GOOGLE CLOUD EDITOR'S NOTE AI containers AWS Deep Learning Containers GPU support on AKS Deep Learning Containers AI AND MACHINE AI machine images AWS Deep Learning AMIs Data Science Virtual Machines Deep Learning VM Image LEARNING Chat bots builder Amazon Lex Azure Bot Service, QnA Maker Dialogflow ANALYTICS Data labeling Amazon SageMaker Ground Truth Azure Machine Learning data labeling Cloud Data Labeling APPLICATION INTEGRATION Document extraction, Amazon Textract Azure Form Recognizer, Ink Vision API image content analysis Recognizer, Computer Vision, BUSINESS Custom Vision APPLICATIONS Image and video Amazon Rekognition Azure Face, Video Indexer Video AI COMPUTE recognition, indexing CONTAINERS Inference accelerator Amazon Elastic Inference GPUs on AKS Cloud TPU, Edge TPU COST CONTROLS Language recognition, Amazon Comprehend Language Understanding, Text Natural Language sentiment analysis Analytics DATABASES Language translation Amazon Translate Speech Translation, Translator Translation DEVELOPER TOOLS Machine learning AWS Inferentia, AWS Trainium FPGA Cloud TPU hardware (preview*) IoT Managed machine Amazon SageMaker Azure Machine Learning Cloud AutoML MANAGEMENT learning platform AND GOVERNANCE Online fraud detection Amazon Fraud Detector N /A reCAPTCHA Enterprise MIGRATION Prediction review Amazon Augmented AI, Amazon Azure Content Moderator N /A MISCELLANEOUS and moderation SageMaker Clarify NETWORKING Recommendation Amazon Personalize Personalizer Recommendations AI integration (preview) SECURITY Speech recognition Amazon Transcribe Speaker Recognition, Speech to Text Cloud Speech-to-Text API STORAGE CONTINUED A CLOUD SERVICES CHEAT SHEET FOR AWS, AZURE AND GOOGLE CLOUD • DECEMBER 2020 3 CONTINUED AI and machine learning HOME AWS AZURE GOOGLE CLOUD EDITOR'S NOTE Text-to-speech Amazon Polly Text to Speech Cloud Text-to-Speech API AI AND MACHINE Time-series forecasting Amazon Forecast N /A N /A LEARNING Vision/speech modeling AWS DeepLens Azure Kinect DK N /A ANALYTICS packaged devices APPLICATION *AWS, GOOGLE AND MICROSOFT USE DIFFERENT TERMINOLOGY TO DESCRIBE SERVICES THAT ARE IN PREVIEW, BETA OR ALPHA. INTEGRATION FOR THE PURPOSES OF THIS PIECE, ANY SERVICE THAT IS NOT GENERALLY AVAILABLE IS LISTED AS BEING IN PREVIEW. BUSINESS Analytics APPLICATIONS AWS AZURE GOOGLE CLOUD COMPUTE Big data processing Amazon EMR Azure Databricks, Azure HDInsight Dataproc CONTAINERS Business analytics Amazon QuickSight Power BI Embedded Looker, Google Data Studio COST CONTROLS Data lake creation Amazon HealthLake (preview), Azure Data Lake Storage Cloud Storage DATABASES AWS Lake Formation DEVELOPER TOOLS Data sharing AWS Data Exchange, AWS Lake Azure Data Share Cloud Dataprep Formation (partnership with Trifacta) IoT Data warehousing Amazon Redshift Azure Synapse Analytics BigQuery MANAGEMENT AND GOVERNANCE ETL AWS Glue, Amazon Kinesis Data Azure Data Factory Cloud Data Fusion, Firehose, Amazon SageMaker Data Dataflow, Dataproc MIGRATION Wrangler Hosted Hadoop/Spark Amazon EMR Azure HDInsight Dataproc MISCELLANEOUS Managed search Amazon CloudSearch, Amazon Azure Cognitive Search, Bing Search Cloud Search NETWORKING Elasticsearch Service, Amazon Kendra services SECURITY Managed Kafka Amazon Managed Streaming Azure Event Hubs for Apache Kafka N/A (available through a for Apache Kafka partnership with Confluent) STORAGE CONTINUED A CLOUD SERVICES CHEAT SHEET FOR AWS, AZURE AND GOOGLE CLOUD • DECEMBER 2020 4 CONTINUED Analytics HOME AWS AZURE GOOGLE CLOUD EDITOR'S NOTE Real-time data streaming Amazon Kinesis Data Analytics, Azure Stream Analytics Dataflow, Pub/Sub Amazon Kinesis Data Streams AI AND MACHINE LEARNING Query service, data Amazon Athena, Amazon SQL Server ML Services, Big Data BigQuery exploration Elasticsearch Service, Amazon Clusters (Spark), Data Lake Analytics, ANALYTICS Managed Service SQL Server Analysis Services, for Grafana (preview) Azure Data Explorer APPLICATION INTEGRATION BUSINESS Application integration APPLICATIONS AWS AZURE GOOGLE CLOUD COMPUTE API development and Amazon API Gateway, AWS AppSync Azure API Apps API Gateway (preview), management Apigee, Cloud Endpoints CONTAINERS Distributed app Amazon Simple Workflow Service, Logic Apps Cloud Tasks coordination AWS Step Functions COST CONTROLS Event routing, third-party Amazon AppFlow, Amazon Event Grid Pub/Sub DATABASES integration EventBridge, Amazon Simple Notification Service DEVELOPER TOOLS Messaging Amazon MQ, Amazon Simple Queue Queue Storage, Service Bus Pub/Sub IoT Service MANAGEMENT Service discovery AWS Cloud Map N /A N /A AND GOVERNANCE Service mesh AWS App Mesh Azure Service Fabric Mesh (preview) Anthos Service Mesh MIGRATION Workflow orchestration AWS Data Pipeline Logic Apps Cloud Composer MISCELLANEOUS NETWORKING SECURITY STORAGE A CLOUD SERVICES CHEAT SHEET FOR AWS, AZURE AND GOOGLE CLOUD • DECEMBER 2020 5 Business applications** HOME AWS AZURE GOOGLE CLOUD EDITOR'S NOTE Collaboration tool suite N /A Microsoft 365 Google Workspace AI AND MACHINE Document sharing and Amazon WorkDocs Microsoft Word Google Docs LEARNING storage ANALYTICS Email and calendar Amazon WorkMail Outlook Gmail APPLICATION Low-code/no-code Amazon Honeycode (preview) Microsoft PowerApps, Project Bonsai AppSheet INTEGRATION (preview) BUSINESS Video calls and chat Amazon Chime Microsoft Teams Google Meet APPLICATIONS Voice assistant Alexa for Business Cortana Google Assistant COMPUTE **SEVERAL GOOGLE AND MICROSOFT SERVICES IN THIS SECTION ARE NOT EXPLICITLY AVAILABLE THROUGH GOOGLE CLOUD PLATFORM AND MICROSOFT AZURE, RESPECTIVELY. THEY ARE PART OF EACH VENDOR'S BROADER CLOUD PORTFOLIO. CONTAINERS COST CONTROLS Compute AWS AZURE GOOGLE CLOUD DATABASES Autoscaling AWS EC2 Auto Scaling Azure Autoscale, Azure virtual Managed instance groups DEVELOPER TOOLS machine scale sets (MIGs) IoT Batch scheduling, AWS Batch Azure Batch Batch on GKE (preview) executing and processing MANAGEMENT AND GOVERNANCE Functions as a service AWS Lambda Azure Functions Cloud Functions MIGRATION 5G-based infrastructure AWS Wavelength Azure Edge Zones Global Mobile Edge Cloud (GMEC) MISCELLANEOUS High performance AWS ParallelCluster Azure CycleCloud N /A computing cluster NETWORKING management SECURITY Isolated servers Dedicated Instances Azure Dedicated Host Sole-tenant Nodes, Shielded VMs STORAGE CONTINUED A CLOUD SERVICES CHEAT SHEET FOR AWS, AZURE AND GOOGLE CLOUD • DECEMBER 2020 6 CONTINUED Compute HOME AWS AZURE GOOGLE CLOUD EDITOR'S NOTE PaaS AWS Elastic Beanstalk App Service, Azure Cloud Services, App Engine Azure Spring Cloud, Azure Red Hat AI AND MACHINE OpenShift LEARNING On-premises/edge devices AWS Outposts, AWS Snow Family Azure Stack Hub, Azure Stack HCI N /A ANALYTICS (preview), Azure Stack Edge APPLICATION Quantum computing Amazon Braket Azure Quantum (preview) N /A INTEGRATION Virtual machines Amazon EC2 Virtual Machines Compute Engine BUSINESS APPLICATIONS Virtual private