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Hazelcast Common Mistakes and Best Practices

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Viktor G.
Hazelcast Common Mistakes and Best Practices

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IMPORTANT: Make sure you have FIRST and LAST name on your profile. Please, bring ID to enter the building!

Food and refreshments will be provided.

Please, use the following link to RSVP.

DON'T RSVP ON MEETUP

https://hugnyc.splashthat.com

DON'T RSVP ON MEETUP

Hello Hazelcasters,

I'm so excited to announce our next meetup!

This time we're going to have Fuad Malikov - Hazelcast Co-Founder and VP Technical Operations - to talk about Hazelcast Pitfalls and Best Practices and Ray Tsang from Google to talk about Hazelcast Discovery API.

Common Mistakes and Best Practices

Hazelcast is a popular open source In-Memory Data Grid that is extremely powerful and easy to use. Hazelcast provides many distributed and highly scalable data structures such as Map, Queue, Lock and Executor Service. It also has many powerful capabilities like listeners, WAN replication, and query functionality. It is possible to implement applications that are very scalable and capable. However, power comes with responsibility and misuse can cause degrading performance and application scalability. In this talk, we will talk about some of the best practices and mistakes to avoid while using Hazelcast. We assume that the audience is familiar with Hazelcast or an alternative IMDG. You will leave this session knowing the core principles and best practices for the following features: - WAN Replication

  • Queries
  • Listeners
  • Executor Service
  • Queue

Introduction to Hazelcast Discovery SPI

This is a short session that gives you a preview into the Discover Client SPI, and how you can leverage it to bring Hazelcast to even more cloud platforms! We'll take a look at challenges that Ray ran into prior to the SPI when trying to use Hazelcast on Google Compute Engine and Kubernetes. With the SPI, it's now very easy to implement Hazelcast node discovery for many different cloud platforms.

Ray Tsang is a Developer Advocate for the Google Cloud Platform. Ray had extensive hands on cross-industry enterprise systems integration delivery and management experiences during his time at Accenture, managed full stack application development, DevOps, and ITOps. Ray specialized in middleware, big data, and PaaS products during his time at Red Hat while contributing to open source projects, such as Infinispan. Aside from technology, Ray enjoys traveling and adventures

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