aws-samples / lambda-refarch-imagerecognition
The Image Recognition and Processing Backend reference architecture demonstrates how to use AWS Step Functions to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition.
Summary
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| Main Code: 1,082 LOC (14 files) = JS (46%) + YML (27%) + YAML (11%) + GRAPHQL (8%) + CSS (4%) + HTML (1%) Secondary code: Test: 6 LOC (1); Generated: 59,703 LOC (8); Build & Deploy: 2 LOC (2); Other: 63,138 LOC (52); |
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| Duplication: 5% | |||
| File Size: 0% long (>1000 LOC), 76% short (<= 200 LOC) | |||
| Unit Size: 0% long (>100 LOC), 38% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 100% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (12 components) | ||
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5 years old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
Latest commit date: 2021-09-25
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