Honeycomb

A Honeycomb chart shows the status of many entities as color-coded hexagons. Use it for at-a-glance fleet or cluster health.

A Honeycomb chart displays the status of multiple entities using color-coded hexagons. Each hexagon represents one instance (node, server, pod, service, device). It’s built for fast “what’s up/down?” scanning.

It’s ideal for:

• Cluster health

• Node availability

• Service status

• Pod or container health

• IoT device monitoring

What a Honeycomb chart represents

Each hexagon = one instance. Hexagon color shows its current state.

Common states:

• Green = Up / OK

• Yellow = Warning / Degraded

• Red = Down / Critical

Example Honeycomb status chart

Configure a Honeycomb chart

Set Chart type to Honeycomb. Pick the Label column and Value column. Enable Custom config to define status rules.

Honeycomb configuration options

Option	Purpose
Chart type	Must be Honeycomb.
Label column	The entity name shown for each hexagon.
Value column	Numeric field used to compute status.
Custom config	Enables status rules.
Condition	Operator used in a rule (>, <, >=, <=, =).
Threshold	Comparison value for the rule.
Text	Label applied when the rule matches (for example up).
Color	Hexagon color when the rule matches.

Example rules:

• = 1 → up (green)

• < 1 → down (red)

Key rules:

• Each instance is evaluated independently.

• Rules are evaluated top-to-bottom (in order).

• The first matching rule is applied.

• Keep rules mutually exclusive, or order them carefully.

What the user sees

The user instantly sees:

• How many entities are healthy

• Which entities are down

• Where problems are concentrated

No log digging required.

When to use Honeycomb

Use Honeycomb when you need to:

• Monitor many components at once

• Detect failures quickly

• Show binary or state-based health

Ideal for Kubernetes nodes, microservices, servers, network devices, and IoT fleets.

Why the honeycomb layout works

The hexagon layout:

• Packs many items into a small space

• Makes failures visually obvious

• Works better than tables for live monitoring