The Hitchhiker’s Guide to the Cloud (AWS vs GCP vs Azure) and their AI/ML API’s capabilities
A presentation at NDC Oslo in in Oslo, Norway by Bruno Amaro Almeida
The Hitchhiker’s Guide to the Cloud Index and their AI/ML API’s capabilities NDC Oslo 2019 Bruno Amaro Almeida BERLIN · HELSIN K I · LON DON @bruno_amaro · MUN ICH · OSLO · STOCK HOLM · TAMPERE Photo by Greg Rakozy on Unsplash
FUTURE. CO-CREATED. Nordic Roots, Global Mindset PEOPLE NATIONALITIES 550+ 38 8 30% OFFICES Tampere Helsinki Oslo Stockholm YoY GROWTH Family of Companies eCommerce & Growth Hacking Berlin London Artificial Intelligence & Machine Learning Stuttgart Munich
Who is this guy? Principal Architect & Technology Advisor @ Futurice ! native, based in ” Cloud, DevOps, Security, Data Engineering & AI Reach out on: @bruno_amaro BERLIN · HELSIN K I · LON DON @brunoamaroalmeida · MUN ICH · OSLO · STOCK HOLM · TAMPERE
Public Cloud: What are my options? What is the best? BERLIN · HELSIN K I · LON DON 42 · MUN ICH · OSLO · STOCK HOLM · TAMPERE @bruno_amaro
Public Cloud: Global Landscape Public Cloud Global Market Share (CSA - 2017) Gartner Magic Quadrant for Cloud 2018 @bruno_amaro
Overview • Market leader year-over-year • Extreme Customer centric • Really good at providing services that do the heavy lifting of common things you can build by yourself but you don’t really have (or want) to • Very stable services • Built from Ops towards Devs point of view @bruno_amaro
Overview ● Gaining market share very rapidly. ● Good offering and value proposition for hybrid environments (on-prem <-> cloud or multi-cloud) ● ● Europe North == Ireland. Currently no region in the Nordics (but Oslo coming soon). A region has one or more AZs. Paired regions concept. ● Things-that-looked-quite-interesting: ● Service Fabric ● Azure DevOps ● Resource Manager Template (IAAS) ● PowerBI @bruno_amaro
Overview ● Strong focus on Innovation and providing services you can’t reasonably build by yourself ● Built from a Developer point of view, designed with a Site Reliability Engineering mindset ● Some services released as OpenSource (e.g. Kubernetes -> GKS), others fully commercialized (e.g. Dremel -> BigQuery) ● Things-that-looked-quite-interesting: ● ● ● ● Pub/Sub Service A lot of services were designed to be global ( internet scale) by default Very Interesting AI/ML offering and capabilities Datacenter in Finland @bruno_amaro
AWS vs GCP vs Azure: Core Building Blocks Compute Network Storage Security & Identity • AWS EC2 • AWS VPC • AWS EBS • AWS IAM • AWS ECS / EKS / Fargate • AWS Route 53 • AWS S3 • AWS KMS / CloudHSM • AWS Lambda • AWS Elastic Load Balancing • AWS EFS • AWS Inspector / Advisor / GuardDuty / Shield • AWS Elastic Beanstalk / Amplify • AWS CloudFront • Google Compute Engine • Google Cloud Virtual Network • Google Persistent Disk • Google Cloud IAM • Google Container Engine / GKE • Google Cloud DNS • Google Cloud Storage • Google Cloud KMS / Cloud HSM • Google Cloud Functions • Google Cloud Load Balancing • Google Cloud File Store • Google Cloud Security Scanner • Google App Engine • Google Cloud CDN • Azure Virtual Machines • Azure Virtual Network • Azure Disk Storage • Azure Active Directory • Azure Containers / AKS / Service Fabric • Azure DNS • Azure Blog Storage • Azure Key Vault / Dedicated HSM • Azure Functions • Azure Load Balancer • Azure File Storage • Azure Sentinel / Security Center / DDoS • Azure App Service • Azure CDN Protection @bruno_amaro
Public Cloud: AI & Analytics Capabilities What do they offer? How do they differ? BERLIN · HELSIN K I · LON DON · MUN ICH · OSLO · STOCK HOLM · TAMPERE
AI & Analytics Capabilities Data Engineering (ingest, prepare, transform, analyze) AI/ML Platform (build, train, deploy) AI/ML API’s (pre-trained models, serverless, out of the box) @bruno_amaro
AWS vs GCP vs Azure: Data Engineering Ingest • AWS Kinesis • Google Pub/Sub • Azure Event Hubs ETL • AWS Glue / EMR • Google Dataflow / DataProc • Azure DataFactory / DataBricks Raw Storage • AWS S3 • Google Cloud Storage • Azure Data Lake Storage Data Warehouse • AWS Redshift • Google Cloud BigQuery • Azure SQL Data Warehouse Machine Learning • AWS SageMarker • Google Cloud Datalab Analytics / BI • AWS QuickSight • Google Cloud Data Studio • Azure ML Studio / Workbench • Power BI @bruno_amaro
AWS vs GCP vs Azure: AI/ML Platform AWS Sagemaker Google Cloud ML Engine • Amazon SageMaker automatically configures and optimizes TensorFlow, Apache MXNet, PyTorch, Chainer, Scikit-learn, SparkML, Horovod, Keras, and Gluon. • Commonly used machine learning algorithms are built-in and tuned for scale, speed, and accuracy with over a hundred additional pretrained models and algorithms available in AWS Marketplace. • You can also bring any other algorithm or framework by building it into a Docker container. Source: AWS • Cloud Machine Learning Engine: Massively scalable managed service for training ML models & making predictions. • Enables apps/devs to use Tensorflow on datasets of any size Azure ML Studio • Azure Machine Learning: End to End Data Science Solution • Uses PyTorch, Tensorflow and Keras • Multiple Components: • ML Workbench • ML Experimentation Service • ML Model Management Service • Supports online & batch predictions, prioritising latency (online) & job time (batch) • Or download models & make predictions anywhere: desktop, mobile, own servers • ML Libraries for Spark • Visual Studio Code tools for AI • HyperTune automatically tunes model hyper parameters to avoid manual tweaking Source: Google Cloud Source: Azure @bruno_amaro
AWS vs GCP vs Azure: AI/ML API’s AI/ML Service APIs AI/ML Service APIs AI/ML Service APIs • AWS Lex • Google Dialogflow • Azure Bot Service • AWS Rekognition • Google Vision API • Azure Vision • AWS Translate • Google Text-to-Speech API (ASR) • Azure Speech • AWS Polly (TTS) • Google Speech-to-Text API • AWS Transcribe (ASR) • Google Natural Language API (NPL) • AWS Textract (OCR) • Google Translation API • Azure Knowledge • AWS Comprehend (NPL) • Google Video Intelligence API • Azure Search • AWS Forecast (Time-series forecast) • Google Inference API (Time-series forecast) • Translator Speech API, Bing Speech API • Google Job Discovery • Bing News/Web/Image/Video/Custom Search • Azure Language • Google Cloud Genomics (Store and process genomes and related experiments ) Source: AWS • In preview: Speaker Recognition API, Custom Speech Service Source: Google Cloud • Language Understanding (LUIS), Bing Spell Check, Text Analytics, Translator Text API Source: Azure @bruno_amaro
A Practical Example What can Serverless AI/ML APIs tell us about news media websites? • • • How good are they? How much can they tell us? Will there be differences between “credible” vs “fake” media sites? What will they say about the “credible” media? BERLIN · HELSIN K I · LON DON · MUN ICH · OSLO · STOCK HOLM · TAMPERE Photo by Elijah O’Donnell on Unsplash
Website Metadata Extraction Methods xvfb-run (…) wkhtmltoimage (…) lynx —dump image-scraper Pressure on Theresa May to resign will ‘increase dramatically’ following extension, warns David Davis + Review set for June 21 after Macron opposes long delay + EU already talking about possibility of further extension + Britain’s EU ambassador formally accepts extension [51]ReconstructionHow Emmanuel Macron raged against Britain’s chaotic [52]Janet DaleyAny Brexit solution with Theresa May in post is impossible [53]How long does the PM have left after being forced to accept a six month (…) @bruno_amaro
Enrich website metadata with AI/ML API Google Vision API: • Text • Labels • Safe Search • Web Entities Tusk recommends EU insist on year-long Brexit extension after MPs + PM arrives in France to meet Macron after talks with Merkel + Four Cabinet ministers rebel against vote to extend Brexit + Tusk: ‘Little reason’ to believe Brexit can be delivered by [51]ExclusiveLiam Fox tells Tory MPs that customs union will be ‘worst of [52]Daniel KawczynskiERG members are putting Brexit in jeopardy, I had no [53]Is Macron seeking his Charles de Gaulle moment over Brexit? (…) Google Natural Language API: • Analyze Sentiment • Text Classify @bruno_amaro
Enrich website metadata with AI/ML API @bruno_amaro
What did we learn about that website? @bruno_amaro
“ How about Azure?
Enrich website metadata with AI/ML API Azure Cognitive Services • Computer Vision • Text Analytics: Sentiment @bruno_amaro
Enrich website metadata with AI/ML API @bruno_amaro
Microsoft Sample QuickStart for Vision API
Microsoft Sample QuickStart for Text Analytics API
Microsoft Sample QuickStart for Text Analytics API
Microsoft Sample QuickStart for Text Analytics API
“ How about AWS?
Enrich website metadata with AI/ML API AWS Services • Rekognition • Comprehend @bruno_amaro
Enrich website metadata with AI/ML API @bruno_amaro
AWS Comprehend for Sentiment Detection
… d n a g n o so l Thank you! Kiitos! Danke! Tack! Bruno Almeida h s i f e h t l l a r o …f P RINC IP AL ARC HITE C T & TE C HNOL OGY ADV ISOR Cloud, CyberSecurity, DevOps, Data Engineering & AI Reach out on: @bruno_amaro @brunoamaroalmeida BERLIN · HELSIN K I · LON DON · MUN ICH · OSLO · STOCK HOLM · TAMPERE
In this talk we will learn about the three major public cloud providers (AWS, GCP and Azure) by having an overview and gain insights about each other pros and cons. In addition, we are going to explore their AI/ML Cloud API’s that allow us to leverage ready-made capabilities such as: Text to Speech, Image & Video Classification, Translation, Speech Recognition, Sentiment Analysis, etc.
Video
Buzz and feedback
Here’s what was said about this presentation on social media.
