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Get Monitoring Right for Streaming and Fast Data Systems on Spark, Mesos, Akka, Cassandra, and Kafka [Video]

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Get Monitoring Right for Streaming and Fast Data Systems on Spark, Mesos, Akka, Cassandra, and Kafka [Video]

While these apps are powerful and create significant competitive advantages, they also impose new challenges for monitoring and managing the health of the overall system.

· Big Data Zone ·
Free Resource

How do you break a Monolith into Microservices at Scale? This ebook shows strategies and techniques for building scalable and resilient microservices.

Without a doubt, enterprises have begun to embrace Reactive system architectures that rely on continuous streams of data — whether between microservices or from external endpoints — and utilizing the power of Fast Data applications for providing actionable insights in more or less real-time.

So, while your traditional batch jobs from the Big Data world aren’t going away overnight, it’s these new types of streaming and Fast Data applications that are sparking the emergence of new business models and new services that drive user retention, growth, and profitability with real-time decision making and deeply personalized and timely offers.

But wait…this sounds a bit like a silver bullet, right? 

Well, the flip side is that while these applications are powerful and create significant competitive advantages, they also impose new challenges for monitoring and managing the health of the overall system, which ingests constant streams of data from tens or even hundreds of individual, distributed microservices, data sources, and external endpoints.

One of the primary challenges that we address looks at why traditional monitoring solutions built for monolithic applications are unable to effectively manage these intricately interconnected, distributed, and clustered systems.

What You Will Learn

In this Lightbend webinar by Paul Jasek, Senior Director of Global Solution Architects, we present what to look for in an effective monitoring solution for streaming and Fast Data applications. Paul also demos Lightbend Monitoring using sample scenarios to show how we can help your team not just in production, but also during development to catch performance issues before you even deploy.

In the video and corresponding slides, you'll learn:

  • Why traditional monitoring solutions, built for legacy monolithic applications, are unable to effectively manage these intricately interconnected, distributed, and clustered systems.
  • What to look for in an effective monitoring solution for streaming and Fast Data applications.
  • How Lightbend Monitoring’s deep telemetry, automated discovery, configuration, topology visualization, and data-science-driven anomaly detection capabilities help ensure the health, availability, and performance of your applications.
  • How Lightbend Monitoring helps businesses not just in production but also during development so they can optimize their applications for performance from Day 1.
  • A live demo that includes a product walkthrough and sample scenarios so you can understand how your team can use Lightbend Monitoring to quickly troubleshoot problems and issues and reduce MTTR.

Watch the Full Video (47 Minutes)

How do you break a Monolith into Microservices at Scale? This ebook shows strategies and techniques for building scalable and resilient microservices.

Topics:
fast data ,big data ,monitoring ,streaming

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