Serverless Image Processing Pipeline
An event-driven cloud pipeline where an upload triggers functions that resize, watermark and catalogue images automatically.
Project overview
Uploading an image to a storage bucket triggers a chain of serverless functions that generate thumbnails, apply a watermark, extract metadata and write a catalogue entry to a database — with no server running between uploads.
This is a cloud computing project in the proper sense: the architecture, not the application, is the deliverable, and it demonstrates event-driven design, cold starts, retries and idempotency.
Problem statement
Image processing on the web server blocks request handling, wastes capacity that sits idle most of the time, and fails badly when a burst of uploads arrives at once.
Proposed solution
Decouple processing from the request path with a storage event trigger. Each function does one thing, writes its output to a derived location, and reports completion, so the pipeline scales automatically with load and retries safely on failure.
Key features
- Storage event trigger on new object creation
- Multi-size thumbnail generation in parallel
- Watermarking with configurable position and opacity
- EXIF metadata extraction into a queryable catalogue
- Idempotent processing so a retry never duplicates work
- Dead letter handling for objects that fail repeatedly
- Monitoring dashboard with invocation counts, duration and error rate
Technology stack
Compute
Storage & data
Processing
Operations
System architecture
The flow below is what goes into your architecture diagram and the corresponding chapter of the report.
- Upload lands in the ingest bucket through a pre-signed URL
- Object-created event invokes the orchestrator function
- Resize function writes thumbnails to the derived bucket prefix
- Watermark function composites the overlay and stores the public variant
- Metadata function extracts EXIF and writes the catalogue record
- Failures route to a dead letter queue with the original event payload preserved
Expected output
- Processed image variants generated automatically on upload
- Catalogue records queryable by capture date, camera and dimensions
- Architecture diagram and event flow documentation
- Cost and latency measurements including cold start times
Suitable branches, difficulty and duration
Documentation, review, demo and viva support
Documentation support
Abstract, problem statement, literature survey guidance, system architecture, ER and UML diagrams, module descriptions, test cases and screenshots — prepared in your department format.
Project review support
Delivery is split across your review calendar so review one has a design and plan, review two has working modules, and the final review has the integrated, tested system.
Demo support
A rehearsed demo path, seeded sample data, a reset script, and a recorded walkthrough kept as a backup in case something fails in the review room.
Viva preparation
A written question bank for this domain, a code walkthrough session, and practice at explaining each module in your own words — because the examiner will ask you.
Customisation options
Colleges reject duplicate topics, so most projects are adjusted before we start. These are the usual directions for this one.
- Add content moderation using a cloud vision API
- Add video thumbnail extraction alongside images
- Add a scheduled cleanup function for orphaned derivatives
- Rebuild the same pipeline on a second provider and compare cost and latency
Related projects
Cloud-Based File Storage System
A personal cloud drive built on object storage with deduplication, versioning and signed sharing links.
CI/CD Pipeline for Microservices
An automated build, test and deploy pipeline for containerised services with staged environments and rollback.
DevOps Monitoring and Alerting Dashboard
A Prometheus and Grafana observability stack with custom application metrics, alert rules and incident history.
Enquire about the Serverless Image Processing Pipeline project
Send your branch, college and first review date. You will get confirmation of scope, what the customisation would look like, and a delivery plan mapped to your reviews.