Master the design, implementation, and optimization of production-ready streaming data pipelines using Apache Kafka and Flink. This intermediate-level course teaches you to evaluate log configurations against governance requirements (PCI-DSS, GDPR, SOC2) and cost constraints, design stream processing topologies that join and aggregate data in real time with exactly-once semantics, and optimize pipelines through partition tuning, compression, and cost modeling. You'll work through hands-on labs that mirror real-world scenarios at DoorDash, Netflix, and Robinhood: comparing retention policies against compliance rules, building a Kafka Streams application that joins orders and payments to calculate 5-minute revenue totals, and diagnosing performance bottlenecks to meet SLAs within budget.
Stream & Optimize Real-Time Data Flows
您将学到什么
Evaluate log configurations to recommend tiered storage, retention policies, and access controls.
Design stream processing topologies that implement join patterns, aggregation windows, and state management for real-time data transformation.
Optimize real-time data flows by analyzing throughput bottlenecks, partition strategies, and resource allocation to meet SLAs within budget limits.
您将获得的技能
- Data Architecture
- Computer Architecture
- Apache Kafka
- Data Pipelines
- Cloud Storage
- Payment Card Industry (PCI) Data Security Standards
- Capacity Management
- Real Time Data
- System Monitoring
- Performance Tuning
- Apache
- Compliance Management
- Governance
- Data Governance
- Multi-Tenant Cloud Environments
- Application Performance Management
- Scalability
- Operational Data Store
- 技能部分已折叠。显示 9 项技能，共 18 项。
要了解的详细信息
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1 项作业
January 2026
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该课程共有3个模块
Learn to analyze logging architectures against regulatory requirements and budget constraints. You'll evaluate retention policies for audit logs versus operational events, map data classifications to storage tiers, and quantify the cost impact of different configuration choices. By working through cost modeling exercises and compliance gap analysis, you'll recommend concrete changes to log configurations that balance compliance mandates with infrastructure costs.
涵盖的内容
4个视频2篇阅读材料1次同伴评审
Learn to architect stream processing pipelines that transform and enrich data in real time. You'll design topologies that join multiple event streams (orders with payments), implement windowing for time-based aggregations (5-minute revenue totals), and manage stateful operations with exactly-once semantics. By working through concrete patterns like stream-stream joins and fan-out architectures, you'll build production-ready data flows that power operational dashboards and decision systems.
涵盖的内容
3个视频1篇阅读材料1次同伴评审
Learn to diagnose and resolve performance bottlenecks in streaming pipelines while controlling costs. You'll analyze partition strategies against throughput requirements, evaluate replication factors versus latency SLAs, and implement compression and batching optimizations. Through cost modeling exercises and performance benchmarking, you'll balance throughput targets with infrastructure budgets and use monitoring data to make evidence-based recommendations for scaling streaming applications.
涵盖的内容
4个视频1篇阅读材料1个作业2次同伴评审
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