Blog Posts - October 2014

Announcing orchestrator-agent

Announcing orchestrator-agent

This post was written by Shlomi Noach

orchestrator-agent is a side-kick, complementary project of orchestrator, implementing a daemon service on one’s MySQL hosts which communicates with and accepts commands from orchestrator, built with the original purpose of providing an automated solution for provisioning new or corrupted slaves.

It was built by Outbrain, with Outbrain’s specific use case in mind. While we release it as open source, only a small part of its functionality will appeal to the public (this is why it’s not strictly part of the orchestrator project, which is a general purpose, wide-audience solution). Nevertheless, it is a simple implementation of a daemon, such that can be easily extended by the community. The project is open for pull-requests!

A quick breakdown of orchestrator-agent is as follows:

  • Executes as a daemon on linux hosts
  • Interacts and invokes OS commands (via bash)
  • Does not directly interact with a MySQL server running on that host (does not connect via mysql credentials)
  • Expects a single MySQL service on host
  • Can control the MySQL service (e.g. stop, start)
  • Is familiar with LVM layer on host
  • Can take LVM snapshots, mount snapshots, remove snapshots
  • Is familiar with the MySQL data directory, disk usage, file system
  • Can send snapshot data from a mounted snapshot on a running MySQL host
  • Can prepare data directory and receive snapshot data from another host
  • Recognizes local/remote datacenters
  • Controlled by orchestrator, two orchestrator-agents implement an automated and audited solution for seeding a new/corrupted MySQL host based on a running server.

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Announcing Aletheia – A streaming data delivery framework

This post was written by Stas Levin

Outbrain is proud to announce Aletheia, our solution for a uniform data delivery and flow monitoring across data producing and consuming subsystems. At Outbrain we have great amounts of data being constantly moved and processed by various real time and batch oriented mechanisms. To allow fast recovery and high SLA, we need to be able to detect problems in our data crunching mechanisms as fast as we can, preferably at near real time. The later problems are detected, the harder it is to investigate them (and thus fix them), and chances of business impact grow rapidly.

To address these issues, we’ve built Aletheia, a framework providing a uniform way to deliver and consume data, with built in monitoring capabilities allowing both producing and consuming sides to report statistics, which can be used to monitor the pipeline state in a timely fashion.

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