Skip to content
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions CHANGES.rst
Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@ Changes
Unreleased
==========

- Document dedicated master nodes on the Services page
- Consolidate ``cloud-reference``, ``cloud-howtos``, and ``cloud-tutorials``
- Adjust links to accompany renaming to ``cloud-docs``
- Adjust intersphinx references to accompany consolidation into single repository
Expand Down
43 changes: 42 additions & 1 deletion docs/reference/services.md
Original file line number Diff line number Diff line change
Expand Up @@ -50,7 +50,7 @@ _large production workloads_

- Any cluster size
- Custom compute options
- Dedicated master nodes
- {ref}`Dedicated master nodes <dedicated-master-nodes>`
- Unlimited Storage
- Custom Backups
- Premium Support
Expand Down Expand Up @@ -154,6 +154,47 @@ three (e.g., 3, 6, 9, 12, etc.) provides optimal distribution across zones, it
is not strictly required for high availability.


(dedicated-master-nodes)=
## Dedicated master nodes

By default, every node in a cluster is master-eligible: on top of storing and
querying data, any node can be elected to manage the cluster state—keeping
track of which nodes are members, where shards live, and coordinating changes
to that metadata. On smaller clusters this shared arrangement works fine. On
large or busy clusters it can work against you, because the elected master
competes for CPU and memory with the same query and ingest traffic it is meant
to coordinate—the data node under the most load is also the one holding the
cluster together.

Dedicated master nodes split those two jobs apart. The cluster runs a small,
separate pool of nodes that only manage the cluster state; they hold no data
and answer no queries, so coordination stays responsive no matter how hard the
data nodes are working. In practice this means steadier cluster management and
cleaner failover on larger deployments.

**When to use them**<br>
Consider dedicated master nodes once a cluster grows past a handful of data
nodes, sustains heavy ingest or query load, or has strict availability
requirements. Smaller clusters don't need them—the data nodes take on the
master role without any trouble.

**How they work**<br>
- You opt into dedicated master nodes when deploying a cluster. They are
available on the larger dedicated sizes (CR3 and up).
- The pool always runs an odd number of nodes—three by default, optionally
five—so a master can always be elected by a majority (quorum). An even number
adds cost without improving fault tolerance, so it isn't offered.
- Master nodes are distributed across availability zones like data nodes, and
each is deployed with its own storage. Their size and count are set when the
cluster is created and stay fixed when you scale the data nodes up or down.

**Billing**<br>
Dedicated masters are billed as additional nodes: compute for each master while
the cluster is running, plus their storage. Suspending a cluster pauses master
compute along with the data nodes; master storage keeps being billed, the same
way data storage does. See {ref}`billing <organization-billing>` for details.


## Custom

For organizations with specialized requirements that go beyond the Shared and
Expand Down
Loading