website: update scheduling links
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@ -77,8 +77,8 @@ Looking at only a single region, at a high level Nomad looks like:
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![Regional Architecture](/assets/images/region-arch.png)
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Within each region, we have both clients and servers. Servers are responsible for
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accepting jobs from users, managing clients, and computing task placements. Each
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region may have clients from multiple datacenters, allowing a small number of servers
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accepting jobs from users, managing clients, and [computing task placements](/docs/internals/scheduling.html).
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Each region may have clients from multiple datacenters, allowing a small number of servers
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to handle very large clusters.
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In some cases, for either availability or scalability, you may need to run multiple
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@ -126,7 +126,8 @@ ensuring PCI compliant workloads run on appropriate servers.
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# Getting in Depth
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This has been a brief high-level overview of the architecture of Nomad. There
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are more details available for each of the sub-systems. The [consensus protocol](/docs/internals/consensus.html) is
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documented in detail as is the [gossip protocol](/docs/internals/gossip.html).
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are more details available for each of the sub-systems. The [scheduler design](/docs/internals/scheduling.html),
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[consensus protocol](/docs/internals/consensus.html), and [gossip protocol](/docs/internals/gossip.html)
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are all documented in more detail.
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For other details, either consult the code, ask in IRC or reach out to the mailing list.
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@ -10,10 +10,11 @@ description: |-
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Scheduling is a core function of Nomad. It is the process of assigning tasks
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from jobs to client machines. This process must respect the constraints as declared
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in the job, and optimize for resource utilization by bin packing. This page documents
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the details of how scheduling works in Nomad to help both users and developers
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build a mental model of how it works. The design is heavily inspired by Google's
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work on [Omega: flexible, scalable schedulers for large compute clusters](http://research.google.com/pubs/pub41684.html)
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in the job, and optimize for resource utilization. This page documents the details
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of how scheduling works in Nomad to help both users and developers
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build a mental model. The design is heavily inspired by Google's
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work on both [Omega: flexible, scalable schedulers for large compute clusters](http://research.google.com/pubs/pub41684.html)
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and [Large-scale cluster management at Google with Borg](http://research.google.com/pubs/pub43438.html).
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~> **Advanced Topic!** This page covers technical details
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of Nomad. You don't need to understand these details to
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