Building a Secure IoT Solution: Summit 2017

How do customers build an end-to-end IoT solution using commercial grade, open source products? This is the question we (Patrick Steiner, Maggie Hu and I) wanted to address with our session at the Red Hat Summit, Boston. The end-to-end solution is based on three-tier Enterprise IoT Architecture, which integrates IoT data with existing business processes and the human element.

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Log aggreator using Fuse and Data Grid

Implementing a Log Collector using Red Hat JBoss Fuse and Red Hat JBoss Data Grid

Most of the time, when we think about collecting, parsing and storing Logs, the first thing that pops in our mind is the ElasticStack or ELK. It is well positioned in developer and sysadmin’s minds. The stack combines the popular Elasticsearch, Logstash and Kibana projects together to easy the collection/aggregation, store, and visualization of application logs. As an Apache Camel rider and Infinispan enthusiast, I prepared this exercise to produce my own log collector and store stack using Red Hat’s products, JBoss Fuse and JBoss Data Grid, instead.

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Enabling LDAP Security for DataGrid Cache

Expanding on Tristan’s blog, where he spoke of enabling security for JBoss Data Grid caches, in this post we will cover how to add LDAP based security to the JDG caches. The principles and techniques remain defined by Tristan, but there are some minor changes that I will be highlighting in this blog for a successful working configuration of JDG enabled with LDAP security.

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Offload your database data into an in-memory data grid for fast processing made easy

An in-memory data grid is a distributed data management platform for application data that:

  • Uses memory (RAM) to store information for very fast, low-latency response time, and very high throughput.
  • Keeps copies of that information synchronized across multiple servers for continuous availability, information reliability, and linear scalability.
  • Can be used as distributed cache, NoSQL database, event broker, compute grid, and Apache Spark data store.

The technical advantages of an in-memory data grid (IMDGs) provide business benefits in the form of faster decision-making, greater productivity, and improved customer engagement and experience.

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