Graph Visualization

The Graph Visualization provides a visual interface for analyzing your organizational knowledge graph. It allows you to view entities as nodes, understand how they relate to each other through relationships, inspect node-level details, and focus on specific parts of the graph through filtering and dynamic layout controls. This view is ideal for analyzing structure, understanding topology, or visually investigating how resources, identities, policies, and other objects are connected across your systems. When you need to see the “shape” of your infrastructure or analyze clusters of related resources, the Graph Visualization is the right tool.

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Prerequisites

To work effectively with the Graph Explorer:

• At least one integration or data source must supply entities and relationships
• The Context Graph must contain a meaningful number of nodes for exploration
• Data types and labels must be ingested before filter options become available

Without connected data, the graph will load but contain few or no visualized nodes.

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Page Layout and Components

The Graph Explorer consists of three primary areas:

1. Filters Panel (left): controls what subset of the graph is shown
2. Toolbar (top): actions such as reload, re-arrange, node limit selection, and search
3. Graph Canvas (center): the interactive visualization
4. Node Details Panel (right, when a node is selected): properties, labels, metadata, navigation to full details

These components work together to provide both a high-level overview and deep inspection of any entity.

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Filters Panel

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Data Sources

This section displays all data sources present in the graph, such as:

• AWS
• CSV
• Custom
• Unknown

Each data source tag shows a count of nodes originating from that source. Selecting a data source filter limits the graph to only entities created by that ingestion path.

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Entity Types

The Entity Types section lists all node labels available in the graph, each with a count of how many nodes of that type exist. Examples include:

• AWSUser
• AWSRole
• AWSPolicy
• AWSManagedPolicy
• AWSAccount
• AWSPrincipal, AWSRootPrincipal
• IntegrationAws, IntegrationCsv, IntegrationCustom
• and many others depending on the dataset

Selecting one or more labels filters the visualization to nodes of those types only.

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Active Filters

When filters are applied, they appear in a dedicated Active Filters section, allowing users to:

• See which filters are currently affecting the visualization
• Remove individual filters directly
• Clear all filters at once

This helps maintain visibility into how the graph view is being constrained.

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Toolbar Actions

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Reload

Refreshes the visual graph by re-fetching nodes and relationships according to the current filters. Useful after data source updates or when switching between environments.

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Re-arrange

Recalculates the graph layout and redistributes nodes. This is especially helpful when:

• Switching filters
• Zooming in/out
• The layout becomes visually cluttered
• You want a cleaner, more readable layout

The graph engine repositions nodes for optimal clarity while preserving the structure of relationships.

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Node Limit Selector

A dropdown lets users choose how many nodes to load into the canvas at once:

• 50 nodes - Quick exploration, fastest loading
• 100 nodes - Default view, good balance
• 250 nodes - More comprehensive view
• 500 nodes - Recommended for thorough analysis
• 1000 nodes - Maximum view for complete graph exploration

Smaller views load faster and are easier to interpret, while larger views provide a more complete picture of complex systems. The current node/edge count is always shown in the header (e.g., 500 nodes, 612 edges).

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Search (Filter Nodes…)

Provides text-based filtering across node names and key properties. Typing in this field dynamically reduces the graph to only nodes matching the query. This is useful for locating:

• Specific resource names
• IAM identities
• Policies
• Custom integration records
• Any node identifiable by ingested metadata

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Graph Canvas

The main visualization shows nodes and edges with:

• Entity type labels
• Relationship names (e.g., POLICY)
• Clusters where resources are heavily interconnected
• A miniature map in the bottom-right for navigation

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Interaction Capabilities

Users can:

• Pan across the graph
• Zoom in or out
• Drag nodes to manually reposition them
• Click a node to open its details
• Hover for quick type/label confirmation

The canvas dynamically updates with every filter or limit change.

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Node Details Panel

Clicking any node opens a detailed information panel on the right. This panel includes:

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Labels

All labels assigned to the node, such as:

• AWSPolicy
• AWSManagedPolicy
• IntegrationAws

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Properties

Structured properties ingested from the data source, such as:

• Name
• Type
• ARNs (for AWS resources)
• Identifiers
• Any relevant metadata included by the integration

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Metadata

Graph-level metadata:

• Node ID
• First Seen timestamp
• Last Updated timestamp

These values help trace ingestion history and verify data freshness.

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Relationships

Shows connected nodes, including number of inbound/outbound links. This helps understand how a node fits into the greater graph topology.

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View Full Details

A link that takes the user to a dedicated page for the selected entity in the Entities section. That page includes:

• Full raw JSON
• All relationships
• Property expansion
• Full metadata
• Structured navigation between entities

This is the primary way to jump deeper into an entity after discovering it in the graph.

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Graph Loading and Update Behavior

When the Graph Explorer fetches updated data due to filter changes or reload actions, users see:

• A progress indicator (e.g., Updating relationships 100/100)
• A loading animation
• Gradual completion of relationship fetches

The graph is rendered only after loading is fully complete to avoid partial or inaccurate layouts.

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When to Use Graph Visualization

Graph Visualization excels at:

• Tracing AWS IAM permission relationships visually
• Inspecting associations between policies, users, roles, and managed policies
• Viewing network-level relationships between subnets, ACLs, and routes
• Identifying dependency clusters between resources
• Visually debugging unexpected resource or identity relationships
• Detecting missing, misconfigured, or overly-permissive links
• Understanding how custom ingestion data connects to cloud or identity systems

It is the most intuitive way to see your environment as a connected system rather than as isolated objects.

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What’s Next

The Graph Visualization gives you a visual understanding of your data. Continue exploring through:

• Meta Agent Explore infrastructure interactively through natural language conversation. Ask questions, get insights, and discover relationships without writing queries.
• Entities Inspect every node in a structured table, open detailed views, and explore properties and metadata.
• Queries Write and execute Cypher queries for advanced programmatic analysis and SDK/API integration.
• Data Ingestion Review the ingestion sources feeding the graph, verify sync status, and add new sources.