Closed lauraGgit closed 5 years ago
@lauraGgit I can draw it when I finished task in this Sprint
graph LR
A[Production Application] -->|User driven event| B[AWS CloudWatch]
A -. User driven event.-> L[Google Analytics]
B --> C[Lambda Parser]
C --> G[Intermediate S3 bucket]
D --> I[Lamdba -RedShift Loader]
I --> J[RedShift]
J --> H[AWS QuickSite]
J -.-> K[Blazer]
B --> D[Logstash]
D --> E[ElastiSearch]
E --> F[Kibana]
graph LR
A[Production Application] -->|User driven event| B[AWS CloudWatch]
A -. User driven event.-> L[Google Analytics]
D --> M[Raw data s3 bucket]
M --> C[Lambda Parser]
C --> G[Hot bucket -Intermediate S3 bucket]
G --> I[Lamdba -RedShift Loader]
I --> J[RedShift]
J --> H[AWS QuickSite]
J -.-> K[Blazer]
B --> D[Logstash]
D --> E[ElastiSearch]
E --> F[Kibana]
Now with Kinesis future implementation:
graph TD
A[Production Application] -->N[User driven event]
N -.-> L[Google Analytics]
N --> B[AWS CloudWatch]
B -.-> O[Kinesis]
O-.->J
D --> M[Raw data s3 bucket]
M --> C[Lambda Parser]
C --> G[Hot bucket -Intermediate S3 bucket]
G --> I[Lamdba -RedShift Loader]
I --> J[RedShift]
J --> H[AWS QuickSite]
J -.-> K[Blazer]
N --> D[Logstash]
D --> E[ElastiSearch]
E --> F[Kibana]
@lauraGgit I think we can mark this one https://github.com/18F/identity-analytics-etl/issues/180#issuecomment-461181600, as out-of-dated
.
And I think we can mark this as done
User story
As a new member of the analytics team, I would like to see a diagram of the data pipeline, so that I can understand the implications of the data quality and breath.
Notes
What is the value to the user in this story?* better grok our data structures
What are things we should consider when making this story * this will be evolving
Acceptance Criteria
[ ]
Tasks to complete the story
Definition of Done