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In the last post: Load Balancing - MQTT Broker Clustering Part 1, we introduced MQTT load balancing in general: load balancing can be applied either on the transport layer or the application layer.
Now it’s time to dive into application layer load balancing, the most interesting part: sticky-session.
I use Distillery to generate Erlang releases for my Elixir applications. Through this post, I'll explain how I generate the releases that get shipped to production.
I use Docker to ensure that the final Erlang release is always the same across production instances. This approach also allows me to avoid generating the release on production, which means my production instances stay slimmer by not having Erlang, Elixir, and Node installed natively.
With the advent of blockchain technology, we’re witnessing an explosion of interest in bringing to life the decentralized applications of the future. Some of the best-known programming languages used in the development of blockchain platforms are object-oriented languages. Languages such as C++, Python, and the purpose-built Solidity have so far dominated the blockchain scene.
Functional programming languages are quickly becoming a developer’s first choice when building Dapps, as they largely influence what can and can’t be done, and possess unique features that help them exhibit important comparative advantages.