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Maestro: Netflix's Workflow Orchestrator

netflixtechblog.com

11–20 of 165 posts

Re: Maestro: Netflix's Workflow Orchestrator

#12
The name Maestro has already been used for a workflow orchestrator which I worked on back in 2016. That maestro is SQL-centric and infers dependencies automatically by simply examining the SQL. It's written in Go and is BigQuery-specific (but could be easily adjusted to use any SQL-based system).

https://github.com/voxmedia/maestro/

Re: Maestro: Netflix's Workflow Orchestrator

#17
I wonder how many iterations we will need before engineers are happy with a workflow solution. Netflix had multiple solutions before Maestro, such as metaflow. Uber built multiple solutions too. Amazon had at least a dozen internal workflow engines. It's quite curious why engineers are so keen on building their own workflow engines.

Update: I just find it really interesting that many individuals in many companies like to build workflow engines. This is a not deriding comment towards anyone or Netflix in particular. To me, such observation is worth some friendly chitchat.

Re: Maestro: Netflix's Workflow Orchestrator

#18
post #15

Seems like they re-engineered Temporal: https://temporal.io/

They did use Temporal at Netflix, they gave a couple presentations 2 years ago. I think this is very much not-Temporal because it relies on a DSL instead of workflow as code.

I don't know if it's a scale-thing, I'm not a workflow expert but this seems more in line with the map-reduce of yore, as in you get some big fat steps and you coordinate them, although you could have coarse-grained activities in Temporal workflows.

I'd be curious to see what the tradeoffs are between the two and if they still have usages for Temporal. Maybe Maestro is better for less technical people? Latency? Scale?

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