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
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Stream & Optimize Real-Time Data Flows
Dieser Kurs ist Teil von Spezialisierung für Real-Time, Real Fast: Kafka & Spark for Data Engineers
Dozenten: Starweaver
Bei enthalten
Empfohlene Erfahrung
Was Sie lernen werden
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.
Kompetenzen, die Sie erwerben
- Kategorie: Performance Tuning
- Kategorie: Apache Kafka
- Kategorie: Operational Data Store
- Kategorie: Multi-Tenant Cloud Environments
- Kategorie: Payment Card Industry (PCI) Data Security Standards
- Kategorie: Computer Architecture
- Kategorie: Data Architecture
- Kategorie: Apache
- Kategorie: Application Performance Management
- Kategorie: Data Pipelines
- Kategorie: Real Time Data
- Kategorie: Governance
- Kategorie: Data Governance
- Kategorie: System Monitoring
- Kategorie: Cloud Storage
- Kategorie: Compliance Management
- Kategorie: Scalability
- Kategorie: Capacity Management
Wichtige Details
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Januar 2026
1 Aufgabe
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In diesem Kurs gibt es 3 Module
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.
Das ist alles enthalten
4 Videos2 Lektüren1 peer review
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.
Das ist alles enthalten
3 Videos1 Lektüre1 peer review
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.
Das ist alles enthalten
4 Videos1 Lektüre1 Aufgabe2 peer reviews
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Status: Kostenloser Testzeitraum
Status: Kostenloser Testzeitraum
Status: Kostenloser Testzeitraum
Status: Kostenloser Testzeitraum
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