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StreamSets Kafka Webinar Series


According to the 2018 Apache Kafka Report, 94% of organizations plan to deploy new applications or systems using Kafka this year. At the same time, 77% of those same organizations say that staffing Kafka projects has been somewhat or extremely challenging.



In this multi-part webinar series, StreamSets will take learnings from our customers and share practical tips for making headway with Kafka. Each session will discuss common challenges and provide step-by-step details for how to avoid them. By the end of the series you'll have many more tools at your disposal for ensuring your Kafka project is a success.



Session 1 (On-Demand): Dead Easy Kafka Pipeline Development

When it comes to scaling out Apache Kafka, there's often a trade off between complexity, performance and cost. In this session, we'll look at five different ways to scale up to handle massive message throughput with Kafka and StreamSets In this session you'll learn:

  • Scaling pipelines vertically and horizontally
  • Getting scale by streaming in a cluster
  • Leveraging Kubernetes to elastic scaling

Session 2 (On-Demand) at 10AM PST: Five Ways to Scale Kafka

When it comes to scaling out Apache Kafka, there's often a trade off between complexity, performance and cost. In this session, we'll look at five different ways to scale up to handle massive message throughput with Kafka and StreamSets In this session you'll learn:

  • Scaling pipelines vertically and horizontally
  • Getting scale by streaming in a cluster
  • Leveraging Kubernetes to elastic scaling

Session 3 (On-Demand) at 10AM PST: Machine Learning with Tensorflow and Apache Kafka

Kafka and Tensorflow can be used together to build comprehensive machine learning solutions on streaming data. Unfortunately, both can become black boxes and it can be difficult to understand what's happening as pipelines are running. In this talk we'll explore how StreamSets can be used to build robust machine learning pipelines with Kafka. In this session you'll learn:

  • How to easily build pipelines with Tensorflow and Kafka
  • Visualizing data in Tensorflow pipelines
  • Creating reusable code fragments for standardizing pipeline best practices

Session 4 (Nov. 27) at 10AM PST: Monitoring and Protecting Data in Kafka

With streaming platforms like Kafka, data arguably never rests. As data flows through and across data sources and destinations, it's possible that sensitive data goes unnoticed and potentially gets in the hands of the wrong people or land in the wrong application. In-stream data protection helps ensure that any data flowing from Kafka is protected from unwanted use and exposure. In this session you'll learn:

  • How to implement global data policies for all streaming data
  • Detecting and protecting sensitive data within individual Kafka pipelines
  • Implementing multiple data security policies to augment data at rest solutions


Speakers

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Clarke Patterson
Head of Product Marketing
StreamSets
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Arvind Prabhakar
Co-Founder and CTO
StreamSets
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Kirit Basu
Head of Product Management
StreamSets
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