Kastor-DSP Source Client: Quick Setup Guide for DevelopersThis guide walks you through installing, configuring, and using the Kastor-DSP Source Client so you can quickly integrate it into your ad tech stack. It’s aimed at developers familiar with digital signal processing in advertising technology (DSP) concepts, HTTP/RTB flows, and basic DevOps procedures.
What is the Kastor-DSP Source Client?
The Kastor-DSP Source Client is a lightweight, developer-focused client library that connects publishers or supply-side platforms (SSPs) to Kastor’s demand-side platform (DSP) infrastructure. It handles bid request creation, event reporting, response parsing, and optional enrichment (user segments, contextual metadata). The client abstracts transport details (HTTP/HTTPS, batching, retries), implements the required authentication and signing schemes, and provides hooks for custom logging, metrics, and business logic.
Key benefits:
- Rapid integration with Kastor-DSP endpoints
- Built-in resilience (retry/backoff, circuit breaker patterns)
- Extensible plugin hooks for enrichment and targeting
- Production-ready telemetry and observability patterns
Prerequisites
- Familiarity with RTB and programmatic advertising concepts.
- Node.js (>= 16) or Java (11+) depending on the SDK you’ll use; a Docker environment can be helpful.
- Access credentials for Kastor-DSP (API key, client ID/secret, or certificate depending on auth mode).
- Network access to Kastor-DSP endpoints (allowlist IPs if behind firewall).
- Optional: Kafka or a message queue if you plan to use async event ingestion.
Installation
Below are typical installation steps for the two most common SDKs: Node.js and Java.
Node.js (npm):
npm install kastor-dsp-source-client Java (Maven):
<dependency> <groupId>io.kastor</groupId> <artifactId>kastor-dsp-source-client</artifactId> <version>1.2.0</version> </dependency> Include the relevant client JAR in Gradle or add to your classpath for other build systems.
Basic Configuration
The client is configured via a combination of a JSON/YAML config file and environment variables. Environment variables override file values for secrets and runtime alterations.
Example YAML configuration:
kastor: endpoint: "https://api.kastor-dsp.example/v1" apiKey: "${KASTOR_API_KEY}" clientId: "publisher-123" timeoutMs: 3000 maxRetries: 3 backoff: initialMs: 200 multiplier: 2.0 batching: enabled: true maxBatchSize: 50 flushIntervalMs: 1000 telemetry: metricsPrefix: "kastor.client" enableTracing: true Environment example:
export KASTOR_API_KEY="your_api_key_here" export KASTOR_ENV="production" Initialization (Code Examples)
Node.js:
const { KastorClient } = require('kastor-dsp-source-client'); const client = new KastorClient({ endpoint: process.env.KASTOR_ENDPOINT || 'https://api.kastor-dsp.example/v1', apiKey: process.env.KASTOR_API_KEY, clientId: 'publisher-123', timeoutMs: 3000, maxRetries: 3 }); await client.init(); Java:
KastorConfig cfg = KastorConfig.builder() .endpoint(System.getenv().getOrDefault("KASTOR_ENDPOINT", "https://api.kastor-dsp.example/v1")) .apiKey(System.getenv("KASTOR_API_KEY")) .clientId("publisher-123") .timeoutMs(3000) .maxRetries(3) .build(); KastorClient client = new KastorClient(cfg); client.init(); Creating and Sending Bid Requests
The client provides data models for bid requests compatible with OpenRTB-like schemas. Typical flow: build impression(s) and user/context objects, then send the request and handle the response.
Node.js example:
const bidRequest = { id: "req-001", imp: [{ id: "imp-1", banner: { w: 300, h: 250 }, bidfloor: 0.5 }], site: { id: "site-123", domain: "example.com" }, device: { ua: "Mozilla/5.0", ip: "203.0.113.5" }, user: { id: "user-abc" }, tmax: 120 }; const response = await client.requestBids(bidRequest); console.log("Bids received:", response.seatbid || []); Java example:
BidRequest req = new BidRequestBuilder() .id("req-001") .imp(Collections.singletonList(new Impression("imp-1", new Banner(300, 250), 0.5))) .site(new Site("site-123", "example.com")) .device(new Device("Mozilla/5.0", "203.0.113.5")) .user(new User("user-abc")) .tmax(120) .build(); BidResponse resp = client.requestBids(req); System.out.println("Bids: " + resp.getSeatbid()); Handling Bid Responses
Responses include bids, creative metadata, and notification URLs. Validate required fields, filter by bid price and creative size, and prepare win notifications.
Important checks:
- Presence of bid ID, imp ID, price, adm or nurl
- Creative dimensions match impression
- Bid price >= bidfloor
Example win notification (Node.js):
await client.notifyWin({ impId: 'imp-1', bidId: 'bid-xyz', price: 0.75, winUrl: 'https://notify.kastor-dsp.example/win?bid=bid-xyz' }); Event Reporting & Post-Event Enrichment
Use the client’s async event API for impressions, clicks, conversions. Batch and compress events to reduce network overhead. Include GDPR/CCPA flags and user consent where required.
Event payload example:
{ "events": [ {"type":"impression","impId":"imp-1","ts":1690000000}, {"type":"click","impId":"imp-1","ts":1690000050} ], "publisherId":"publisher-123" } Resilience & Best Practices
- Use retries with exponential backoff and jitter.
- Implement circuit breakers to avoid cascading failures.
- Validate and sanitize all incoming/outgoing payloads.
- Respect tmax and synchronous time limits — offload heavier enrichment to async flows.
- Log at appropriate levels and emit structured metrics (request latency, success rate, error codes).
- Use local caching for frequently used targeting/enrichment data to reduce latency.
Security and Compliance
- Store API keys and secrets in a secrets manager (Vault, KMS).
- Use mTLS if provided for client authentication.
- Respect user privacy: honor consent strings and do not send PII unless explicitly allowed.
- Ensure GDPR/CCPA flags are attached to event and bid payloads.
Observability
Instrument with:
- Tracing (OpenTelemetry) for request flows
- Metrics (Prometheus) for latency, error counts, throughput
- Structured logs (JSON) with request ids and correlation ids
Example Prometheus metrics:
- kastor_client_request_duration_seconds
- kastor_client_requests_total{status=“success|error”}
- kastor_client_retries_total
Testing and Local Development
- Use provided sandbox endpoint to run integration tests.
- Mock network failures and high-latency scenarios.
- Create unit tests for bid selection logic and event serialization.
- Use contract tests to validate schema compatibility between client and server.
Deployment Checklist
- Secrets configured in production-grade secrets manager
- Health checks configured (liveness/readiness)
- Circuit breaker thresholds tuned
- Rate limits and concurrency set per environment
- Monitoring alerts for elevated error rates or latency spikes
Troubleshooting
Common issues:
- Authentication errors: check API key, clock skew for signed tokens.
- Timeouts: increase tmax or optimize enrichment, verify network routes.
- Missing bids: verify impression IDs, sizes, and targeting parameters.
- High error rates: inspect payloads for schema mismatches; enable debug logging.
Further Reading and Resources
- OpenRTB specification (for bid request/response schemas)
- Your organization’s DSP integration docs (for account-specific details)
- OpenTelemetry and Prometheus docs for instrumentation
This guide provides a practical, developer-oriented path to get Kastor-DSP Source Client running quickly and reliably. If you want, I can produce a minimal runnable example repository (Node.js or Java), configuration templates, or a troubleshooting playbook next.
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