Day #125 - Google Cloud Platform Notes

Containers

• Built in capability to isolate environment from one another
• Software containers built on isolation
• Containers starts faster than VM
• Light weight container run time determines image format
• Kubernetes uses Docker container

Kubernetes

• Cluster networking and naming system built on google scale (Kubernetes)
• Runs from Laptop to Cloud providers
• Support Rolling Updates (Update without downtime)
• Built in scaling / load-balancing capability

Kubernetes Engine

• Managed Service
• Built in Monitoring / Logging Capabilities
• Kubernetes cluster nodes are compute engine VM machines

Sample commands for web server deployment
kubectl run nginx --image=nginx:1.10.0
kubectl get services
kubectl get pods
kubectl scale deployment nginx --replicas 3

Data Platform

• ApacheHadoop based on map-reduce programming model
• Map runs in parallel produces intermediate results
• Reduce gets those intermediate results and consolidates

Cloud Pub / Sub

• For stream Analytics
• Publishers / Subscribers
• Receiving messages need not be synchronous
• Atleast one delivery in case of low latency
• For Streaming data it works well

Google ML Model
Structured data 

• Classification and Regression
• Recommendation
• Anamoly Detection - Sensor Diagnostics, Log Metrics
• Forecasting, Cross Sales, UpSales

For unstructured data

• Image and video analytics (Damaged Shipments)
• Text Analytics  - Call centre log analysis, Topic Identification

Cloud Vision API

• Categorize images
• Detect individual objects within images
• Moderate content, Image Sentiment Analysis

Cloud Speech API (Dictate, Command through voice, transcribe audio files)
Cloud Natural Language API (Entity Recognition, Overall Sentiment, Multiple language Support)
Cloud Translation API
Cloud Video Intelligence API

Happy Learning!!!