Building a Photo Gallery with Kubernetes Jobs is a practical project for Kubernetes beginners who want a visible result from batch processing. You will turn licensed garden photographs into real thumbnails and deliver a usable gallery, source index and image archive.
Two Guided Labs introduce a one-group sample, a complete Indexed Job, and recovery from a controlled temporary source failure. An independent Challenge changes the group mapping, concurrency limit and failing index. Each unit includes its own prepared inputs and resources; no files need to cross between environments.
What You Will Learn
After completing this course, you will be able to:
- map input photographs to zero-based completion indexes, including a short final group;
- save and apply an Indexed Job with the correct completion count and bounded requested parallelism;
- connect native Job conditions and completion indexes to owned Pods and actual worker logs;
- use a new Job with finite per-index retries, a global failure budget and an active deadline;
- preserve a failed attempt and already correct images while repeated processing finishes missing work;
- verify real source-derived JPEGs and deliver matching CSV and ZIP downloads with source credits.
Who This Course Is For
This course is for learners who know basic Kubernetes objects and want a small, complete batch-processing project.
Prerequisites: You should be comfortable entering terminal commands, recognizing paths and switching browser tabs. You should already recognize Pods, Deployments, Services, labels and simple YAML. The Guided Labs teach the Job, completion-index, shared-volume, literal editing and retry workflow used here. You do not need Python or image-processing experience.
Learning environment: LabEx provides a prepared Kubernetes cluster, processing image, licensed source photographs, storage, a Workspace terminal and a Gallery browser tab. The website, labels and command output are in English.
Frequently Asked Questions
Do I need to install Kubernetes or build the processor?
No. Each unit includes a prepared browser-based environment and a ready-to-use image processor. Your work is to configure and verify the real Kubernetes batch.
Are the gallery images real files?
Yes. Workers fetch actual licensed source copies and produce 320 × 220 JPEGs. The gallery displays existing output; its downloads contain the actual images and a source index with creator and license information.
Does successful retry mean work runs exactly once?
No. A Job can execute work again. The supplied processor keeps an already matching JPEG unchanged, and you retain both the original failure evidence and the new successful attempt. This one-node storage exercise does not promise distributed exactly-once processing.
How does the Challenge extend the Guided Labs?
The club has a different number of groups, requested parallelism limit and failing index. You combine the same taught grouping, bounded-retry, preservation and handover methods using that environment's actual brief.
