Real world example of Apache Helix, Zookeeper, Mesos and Erlang?

Question

I am new in

• Apache ZooKeeper : ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services.

• Apache Mesos : Apache Mesos is a cluster manager that simplifies the complexity of running applications on a shared pool of servers.

• Apache Helix : Apache Helix is a generic cluster management framework used for the automatic management of partitioned, replicated and distributed resources hosted on a cluster of nodes.

• Erlang Langauge : Erlang is a programming language used to build massively scalable soft real-time systems with requirements on high availability.

It sounds to me that Helix and Mesos both are useful for Clustering management System. How they are related to ZooKeeper? It'd better if someone give me a real world example for their usage.

I am curious to know How [BOINC][1] are distributing tasks to their clients? Are they using any of the above technologies? (Forget about Erlang).

I just need a brief view on it :)

Answer 1

Erlang was built by Ericsson, designed for use in phone systems. By design, it runs hundreds, thousands, or even 10s of thousands of small processes to handle tasks by sending information between them instead of sharing memory or state. This enables all sorts of interesting features that are great for high availability distributed systems such as:

• hot code reloading. Each process is paused, it's relevant module code is swapped out, and it is resumed where it left off, so deploys can happen without restarting or causing significant interruption.
• Easy distributed messaging and clustering. Sending a message to a local process or a remote one is fairly seamless in most instances.
• Process-local GC. Garbage collection happens in each process independently instead of a global stop-the-world even like java, aiding in low-latency results.
• Supervision trees and complex process hierarchy and monitoring/managing.

A few concrete real-world examples that makes great use of Erlang would be:

• MongooseIM A highly performant and incredibly scalable, distributed XMPP / Chat server
• Riak A distributed key/value store.

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Mesos, on the other hand, you can sort of think of as a platform effectively for turning a datacenter of servers into a platform for teams and developers. If I, say as a company, own a datacenter with 10,000 physical servers, and I have 1,000 engineers developing hundreds of services, a good way to allow the engineers to deploy and manage services across that hardware without them needing to worry about the servers directly. It's an abstraction layer over-top of the physical servers to that allows you to share and intelligently allocate resources.

As a user of Mesos, I might say that I have Service X. It's an executable bundle that lives in location Y. Each instance of Service X needs 4 GB of RAM and 2 cores. And I need 8 instances which will be attached to a load balancer. You can specify this in configuration and deploy based on that config. Mesos will find hardware that has enough ram and CPU capacity available to handle each instance of that service and start it running in each of those locations.

It can handle a lot of other more complex topics about the orchestration of them as well, but that's probably a bit in-depth for this :)

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Zookeepers most common use cases are Service Discover and configuration management. You can think of it, fundamentally, a bit like a nested key value store, where services can look at pre-defined paths to see where other services currently live.

A simple example is that I have a web service using a shared database cluster. I know a simple name for that database cluster and where the configuration for it lives in zookeeper. I can look up (or repeatedly poll) that path in zookeeper to check what the addresses of the active database hosts are. And on the other side, if I take a database node out of rotation and replace it with a new one, the config in zookeeper gets updated with the new address, and anything continually looking at it will detect this change and change where it's connected to.

A more complex use case for zookeeper is how Kafka uses it (or did at the time that I last used Kafka). Kafka has streams, and streams have many shards. Each consumer of each stream use zookeeper to save checkpoints in each shard after they have read and processed up to a certain point in the stream. That way if the consumer crashes or is restarted, it knows where to pick up in the stream.