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Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
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The Training Apache Flink 2026 - Mastering Real-Time Streaming Data training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
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Discover the 2026 evolutions of Apache Flink through practical workshops on optimized TaskManagers, configure RocksDB State Backends for durability, implement keyed state with advanced TTL, test timers and ValueState on real healthcare datasets, produce scalable topology UML diagrams, analyze logs for memory tuning, generate initial performance reports for the company.
Dive into Flink Table API 2026 with dynamic SQL queries on patient Kafka streams, perform temporal as-of and interval joins for well-being event correlation, optimize execution plans via EXPLAIN, integrate custom Python UDFs for advanced aggregations, simulate real hospital cases with 1M events/second, export results to Elasticsearch, validate accuracy with golden datasets.
Master tumbling/sliding/session windowing in Flink 2026 on healthcare IoT data, generate advanced watermarks for late data handling, implement session windows with gaps for continuous monitoring, test reduced aggregations on remote clusters, analyze data skew with rebalance, produce deliverable Kibana dashboards, apply to company psychological well-being cases, measure latency under load.
Configure exactly-once semantics via incremental checkpointing 2026, simulate JobManager failures for HA recovery, generate programmable savepoints in healthcare production, integrate Exactly-Once Kafka Sink, test resume from savepoints on Kubernetes, optimize S3 storage backend, produce company DRP procedures, validate RPO/RTO <5min on real workloads.
Deploy Flink 2026 on AWS/GCP cloud with autoscaling, integrate Prometheus/Grafana for backpressure metrics, tune parallelism and slots via benchmarks, secure with Kerberos OAuth for sensitive healthcare streams, migrate Spark jobs to Flink, produce deliverable Terraform blueprints, train company teams post-training, certify setup with full audit.
Target audience
Data engineers in healthcare, hospital big data architects, BI well-being experts, company IT managers for streaming skills development
Prerequisites
Advanced mastery of Java/Scala/Python, 3 years of streaming experience with Kafka/Spark, knowledge of Flink State Backend, Kubernetes cluster deployment
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