GCP Services

GCP includes IaaS and PaaS. SaaS, such as Gmail, fall outside of the scope of GCP.

IaaS

1. Takes care of the hardware level.
2. Requires more overhead as you're responsible for creating and managing instances etc.
3. Pay only for what you use.

• Compute Engine
  • raw computing
  • granular control
• Container Engine
  • datacenter as computer
  • declarative management

PaaS

1. Takes care of both the hardware and software, e.g. runtimes, dependencies, redundancy etc.
2. Write code and go - focus on app logic by making use of pre-set runtimes.
3. Pay only for what you use.

• App Engine
  • pre-set runtimes
  • focus on app logic
• Cloud Endpoints
• Manage VMs
  • bring your own runtime
  • health-checked VMs

Compute Services

Compute Engine

Sort of like building a real pc, but through an API instead of physical components.

• run large-scale workloads on Google's VMs
• robust networking features
• instance metadata & startup scripts
• high CPU, high memory, standard, & shared-core machines
• persistent disk snapshots
• APIs for auto-scaling & group management

Container Engine

Container is Kubernetes and Docker

• based on Kubernetes
• orchestrate & schedule docker containers
• consumes Compute Engine instances
• uses declarative syntax to manage applications
• manages and maintains:
  • logging
  • health management
  • monitoring
  • scaling

App Engine

Focus on features rather than infrastucture.

• managed runtimes for specific versions of python, node, Go, etc.
• autoscale web workloads to meet demand
• free daily quotas and usage-based pricing
• local SDK for dev and deployment
• must conform to sandbox constraints:
  • no writing to local fs
  • request timeouts at 60s
  • limit on 3rd-party software installations

Storage Services

Cloud Bigtable

• NoSQL db service for web, mobile, and large-workload apps
  • starts at terabyte, scales up to petabyte range
• integrated
  • accessed using Apache HBase API
  • native comppatbility with big data ecosystem - let Google do the heavy lifting
• protected
  • replicated storage
  • data encryption
• proven
  • drives many major Google apps

CLoud Storage

Useful for storing backups and archiving data - where most people get started.

• high performance immutable blob storage
• not a file system (Fuse can be used to treat it as such)
• simple administration and does not require capacity management
• all storage options accessed through the same APIs and include client libs:
  • JSON API
  • XML API

Cloud SQL

Fully managed SQL databases

• Google-managed SQL
• pay-per-use model
• REST API for management
• used for affordability and performance
• Google security
• Vertical scaling (reading and writing)
• Horizontal scaling (reading)
• seamless integration with GAE and GCE

Cloud Datastore

• NoSQL store for billions of rows
• Schemaless access - no need to think about underlying data structure
• local dev tools
• auto-scaling and fully managed
• built-in redundancy
• support for ACID transactions
• includes free daily quota
• access from anywhere via RESTful interface

Bigtable vs Datastore

Bigtable - what it's good for (opens in a new tab)

Cloud Datastore - what it's good for (opens in a new tab)

Big Data

BigQuery

• near real-time interactive analysis of massive datasets (Tb's of data in seconds)
• columnar storage for high performance
• queries using SQL-like syntax
• only pay for storage and processing
• zero admin for perf and scale
• supports open standards

Cloud Pub/Sub

• scalable and reliable messaging
• supports many-to-many async messaging
• includes support for offline consumers
• based on proven Google tech
• integrates with Cloud Dataflow for data processing pipelines

Cloud Dataflow

• construct scalable and reliable data pipelines
• executes data processing on GCE instances
• provices support for
  • ETL
  • analytics
  • real-time computations
  • process orchestration
• integrates with GCP services
  • Cloud Storage
  • Cloud Pub/Sub
  • BigQuery

Cloud Datalab

Get insights from your data

• interactive tool for large-scale data exploration, transformation, analysis, and visualisation
  • analyze data in GBQ, GCE, GCS
  • easily deploy analyis models for GBQ
• integrated and open source
  • runs on App Engine
  • built on Jupiter
  • use Google Charts for easy visualisations
• code, docs, results, and visualisations combine in an intuitive notebook format

Cloud Dataproc

• fast, easy, managed way to run Hadoop and Spark on GCP
• benefit from cloud integration
  • Cloud Storage
  • Cloud Monitoring
  • Cloud Logging
• Dataproc clusters are billed minute-by-minute
• any-time scaling - manually scale clusters even while jobs are running
• RESTful API and Cloud SDK integration

App Services

Cloud Endpoints

• build your own API running on App Engine
• expose your API using a RESTful interface
• includes support for OAuth 2.0
• Generate client libraries
• includes some App Engine features:
  • scaling
  • denial of service protection
  • high availability
• supports iOS, Android, and JS clients

Translate API

• translate arbitrary string between thousands of language pairs
• programmatically detect a language
• support for many languages
• supports standard Google API client libs

Prediction API

• pattern-matching and machine-learning
• predict trends based on historical data
• use cases include spam detection and product recommendations
• data replicated using Cloud Storage
• integrates with other GCP services
  • App Engine
  • BigQuery
  • Cloud Storage

Networking

Cloud DNS

• create and manage DNS programmatically

HTTP(S) Load Balancing

• balance HTTP-based traffic across multiple GCE regions
• simple DNS setup
• scalable - requires no pre-warming

Network Load Balancing

• spread TCP & UDP traffic over a pool of instances within a region
• only healthy instances handle traffic
• scalable, requires no pre-warming

Cloud Management Services

Cloud Monitoring

• dashboards and alerts for cloud apps
• review metrics fro cloud services, VMs, and commong open source apps

Cloud Launcher

• launch software packages on GCE in seconds
• WordPress, LAMP, Jenkins etc.

Cloud Deployment Manager

Declarative management

• infrastructure management service
• create a template describing your environment and use deployment manager to create resources

Cloud Logging

• collect and store logs from GCE and GAE
• view logs with log viewer
• export logs to GCS and GBQ