Processing

Question 1

AppEngine

Answer 1

Platform as a service
No direct machine control

Use cases:
Applications w/ managed scaling, consistent or spiking traffic

Classic websites, app servers, etc.

Question 2

GCP Compute

Answer 2

Infrastructure as a service - direct VM control, highly flexible.

Use cases:
Applications incompatible with AppEngine or requiring direct machine control, e.g.

Non-Kubernetes containerised solutions
Migration of existing solution to cloud
Custom kernel or arbitrary OS needed
Solution requires use of GPUs

Question 3

Dataproc

Answer 3

No-ops Hadoop cluster with fast creation / destruction, auto setup, resize, and balance.

Use cases:
Hadoop systems (migrating existing Hadoop systems or creating job oriented Hadoop clusters for BI)

Question 4

Dataprep

Answer 4

Visual ETL workflow, compatible with JSON, CSV and relational databases.

Use cases:
Explore, clean and prep data for analysis
Especially for use with BigQuery, Dataproc jobs, etc.

Question 5

Data flow

Answer 5

Hadoop + Apache beam ETL pipelines with noOps Hadoop execution

Use cases:
Complex ETL with scaleable, fault tolerant pipelines e.g.
Pushing data to multiple storage locations
Merging stream data
Calling external data enrichment
Providing a real time cache of steam data

Question 6

Pub/Sub

Answer 6

Platform as a service (no ops) message delivery. Decouples communication in multi part systems.

Use cases:
Collecting data for processing / storage
Intro-system messaging

Question 7

Cloud Functions

Answer 7

Functions as a service (no ops) - Node.js execution triggered by events (can be Pub/Sub, data flow, Google Storage bucket or HTTP API).

Use cases:
Serverless function execution
E.g. no ops mobile / IoT back ends, or real time ETL for stream data