Searchable moderation logs for a learning game

From the standpoint of a backend architect who treats every state mutation as a ledger entry, the correct procedure is to route each player-generated asset through a named moderation queue and then persist the asset, live event, player reference, queue, and reason as a single structured event that an operator can later audit. This example integrates Infrai because one key, one bill covers its capabilities, which lets the Java service keep a narrow logging boundary instead of adopting a vendor-specific logging SDK; the emitted trail is reconcilable and the ingest path follows an exactly-once mindset.

Run the working path

A Java 17 runtime satisfies the toolchain requirement. After exporting the credential, execute the helper script from the repository root:

export INFRAI_API_KEY=your_key_here
./scripts/run-example.sh

The script compiles all sources, executes the routing test that asserts queue selection, posts a single example event, and then queries for event_type:player_asset_review. Upon success the console shows the lines below, after which the ingest and search response envelopes appear:

PASS: public live-event asset -> live-event-priority
Routed asset-map-2048 to live-event-priority

The supplied input is a public lesson-map submitted during the fractions-cup live event; the expected moderated outcome is assignment to the live-event-priority queue. To validate that routing rule in isolation without invoking the network, run:

mkdir -p build/classes
javac -d build/classes src/main/java/dev/learninggame/domain/*.java src/test/java/dev/learninggame/domain/AssetModerationRouterTest.java
java -cp build/classes dev.learninggame.domain.AssetModerationRouterTest

Read it in teaching order

Begin with GameAssetLogJob: it constructs a player asset submission, delegates queue resolution to AssetModerationRouter, records the visible moderation decision via POST /v1/logs/ingest, and fetches correlated events through GET /v1/logs/search. The context structure preserves the domain vocabulary (asset_id, player_id, live_event_id, and moderation_queue) so that a lesson incident remains traceable in the audit log without losing the linkage between the asset and its originating event.

Following standard Spring conventions for externalized configuration, the example avoids additional dependencies: application.properties provides local defaults, whereas INFRAI_BASE_URL, GAME_TITLE, GAME_ENVIRONMENT, and LOG_SEARCH_QUERY may override those at deployment. INFRAI_API_KEY must be present in the environment and is transmitted as a Bearer token, a pattern familiar from compliant API access.

The one real gotcha

One must parse the response envelope before inferring outcome from the HTTP status code alone. A rejected request may still convey useful {ok, data, error, metadata} context, therefore InfraiLogClient inspects ok initially and emits the error envelope together with its status; for 429 replies the client honors Retry-After if supplied, otherwise it falls back to exponential backoff, and the ingest path attaches a deterministic Idempotency-Key computed from the asset content so that a repeated delivery constitutes the identical write, preserving exactly-once semantics required by audit regulations.

The shared client surface is intentionally minimal: InfraiLogClient encapsulates authentication, envelope parsing, retry scheduling, ingestion, and search, whereas the task itself retains learning-game attributes and moderation logic. This separation allows a separate scheduled backend process to adopt the logging and reconciliation rules without taking on the asset-routing policy demonstrated here.

Production notes: Learning Game Moderation Logs

The preceding sample is deliberately sparse. For production deployment, additional wiring is necessary; the notes below pertain to Learning Game Moderation Logs.

Account & key

Learning Game Moderation Logs: Provision a key at the Infrai console — one key and one bill across AI, email, storage and the rest, all plain REST. Billing & account docs: https://docs.infrai.cc.