Deep Dive into Autoscaling in Apache Flink
Details
Managing data workloads in real-world scenarios can feel like a rollercoaster — unpredictable spikes, sudden drops, and fluctuating demands. Setting high parallelism in Flink jobs ensures performance during peaks but wastes resources during lighter loads. Set it too low, and you risk slow processing and bottlenecks.
Enter Autoscaling!
In this webinar, we'll explore how the Flink Kubernetes Operator Autoscaler tackles dynamic workloads by intelligently scaling jobs up or down. We'll break down the algorithms driving rescaling decisions, dive into configuration fine-tuning, and show you how to make your Flink workloads leaner, faster, and more resource-efficient.
Title: Deep Dive into Autoscaling in Apache Flink
Date & Time: 28th-March-2025 | 05:00 PM - 06:00 PM IST
Location Online: Register Now
What You’ll Learn:
- The mechanics behind Flink Autoscaling
- How the Flink Kubernetes Operator Autoscaler works
- Key algorithms driving scaling decisions
- Configuration tuning for custom Flink jobs
- Practical strategies to boost performance and efficiency
Who Should Attend:
- Data Engineers & Developers
- Big Data Architects
- Apache Flink enthusiasts
- Anyone scaling data workloads with Flink
🎤 Meet the Speaker:
Samrat is a Senior Software Engineer at Confluent and an active contributor to Apache Flink. He’s authored FLIPs (Flink Improvement Proposals) in the connector space and works on enhancing Flink’s reliability. Previously, he worked at AWS EMR specializing in HDFS and YARN components. When he's not optimizing data pipelines, he loves traveling and exploring new places.
Don’t miss out! Join us for this deep dive into Apache Flink’s autoscaling capabilities — discover how to supercharge your Flink jobs with smarter scaling.
🔗 Register now to save your spot!
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