Tag: streaming

Stream LLM responses to clients in real-time using Server-Sent Events with FastAPI, OpenAI streaming, and async generators for token-by-token output

How to read large files efficiently without running out of memory.

How to write large files efficiently using buffered and streaming output.

Create Kafka consumer groups in Python with partition assignment, offset management, commit strategies, rebalance handling, and exactly-once semantics for scalable stream processing.

Build Kafka consumers in Spring Boot using @KafkaListener annotations, concurrent consumers, error handlers, DLQ patterns, and batch listeners with manual acknowledgment.

How to bridge batch and streaming pipelines with a data lake. Covers Lambda architecture, Kafka Connect S3 sink, schema alignment, and unified serving layer.

How to stream database changes to downstream consumers with CDC. Covers log-based CDC, Debezium, Kafka Connect, outbox pattern, and consumer reconciliation.

How to manage schema versions for streaming pipelines with a schema registry. Covers Avro, backward compatibility, forward compatibility, and consumer migration.

Stream data lazily with async generators. Yield values one at a time as they become available, enabling memory-efficient processing of large or infinite data sequences.

Prevent upstream systems from overwhelming downstream consumers by propagating flow-control signals backward through the pipeline, ensuring stable throughput under load.

Build production LLM applications end-to-end. Covers API layers, prompt management, streaming, caching, guardrails, observability, evaluation, and deployment patterns for reliable LLM-powered systems.

Master the OpenAI API in production. Covers chat completions, streaming, function calling, structured outputs, embeddings, fine-tuning, batch API, assistants API, rate limits, error handling, and cost optimization patterns.

A practical guide to gRPC for microservices: Protocol Buffers, streaming, load balancing, and migration from REST for high-performance RPC.

Master data pipeline architecture: batch processing, streaming, lambda and kappa patterns, ETL vs ELT, and choosing the right approach for your data workloads.

A practical guide to real-time analytics: event collection, stream processing, data warehousing, and building sub-second dashboards with Kafka, ClickHouse, Druid, and modern OLAP databases.

Master React Server Components: RSC architecture, data loading, streaming, server actions, and client component boundaries in Next.js App Router.

Run Apache Kafka in production with confidence. Covers partitions, replication, consumer groups, monitoring, performance tuning, and operational best practices for high-throughput streaming pipelines.