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Topology

Key metrics on network structure, geographic peer distribution, client diversity, and connection patterns across the IPFS network. All metrics in this section refer to IPFS Amino DHT Server nodes.

Geographic Distribution

Node IP address to country mapping, based on data sourced from https://ipregistry.co/.

Country Distribution (24h)

Country Distribution (24h)

This world map visualizes the geographic distribution of network nodes based on IP geolocation data. Each country is color-coded according to the number of dialable peers detected in the last 24 hours. This helps assess network decentralization and identifies regions with high node concentration. Note that nodes behind NAT cannot be measured and geographic data may not be fully accurate due to VPNs or proxy usage.

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Geolocation Over Time

DHT Server geolocation per agent version over time

Countries Distribution (24h)

Snapshot of active agents geolocation within the last 24hrs

Agent Version Distributions

Network structure representation through client and agent distribution.

Client Diversity Trend

Client Diversity Trend

Shows the evolution of different user agent types (client software) participating in the network, over time.

Each agent type represents a different implementation and and indicates its relative prevalence within the network for the given reporting period. This chart helps track software diversity, adoption of new client versions, and overall network health, in terms of active nodes in the network.

The Unknown category represents nodes where the agent version could not be retrieved through the libp2p identify protocol. This situation can occur due to various reasons, such as the node terminating the connection before completing the full protocol negotiation.

Client participation over time

Active Agents Distribution (24h)

Snapshot of active agents within the last 24hrs

Agent Versions Trend

Agent version participation over time

Agent Version Distribution (24h)

Snapshot of versions active per agent within the last 24hrs

Availability

We categorize IPFS Amino DHT Server nodes with regard to their availability as follows:

  • “Online”: the node has been found online for 80% of time or more.
  • “Mostly Online”: the node has been found online between 40%-80% of time.
  • “Mostly Offline”: the node has been found online between 10%-40% of time.
  • “Offline”: the node has been found online less than 10% of time.

Availability Over Time

IPFS Amino DHT Server node availability over time

Availability Current Week

IPFS Amino DHT Server node availability - per region - over the current week

IPFS Amino DHT Server Peer Dynamics

Aggregation of server peers entering and leaving the IPFS Amino DHT per day

Protocols & Infrastructure

Key metrics on supported protocols per agent version, as well as intrastructure providers.

Quic Support Over Time

Quic Support Over Time

Tracks the adoption of QUIC protocol support across different client implementations, over time. QUIC provides improved performance, security, and connection reliability compared to traditional TCP. This chart shows which client types support QUIC and how adoption evolves, helping assess the network's transition to more efficient transport protocols.

Count of nodes that support QUIC per agent version

Cloud Provider Dependency Over Time

Count of nodes deployed per cloud provider and per agent

Supported Protocols Over Time

Count of nodes support per protocol

Supported Transports

Network snapshot in terms of supported transports

Supported Transports Over Time

Count of nodes support per transport protocol

Errors

Connection and crawl errors breakdown

Dial Error Causality Distribution

Dial Error Causality Distribution

The plot shows the percentage split of the cause of errors, when errors happen. For example, a 20% error due to, say, connection_refused does not mean that 20% of the time we attempted a connection to a node our attempt was refused. The percentage shown is out of the times that an error did occur, not the total number of attempts.

Percentage split of dial errors per error cause

Crawl Errors Over Time

Crawl Errors Over Time

Monitors the percentage of crawl errors encountered during network topology discovery over time. Crawl errors occur when the monitoring system cannot successfully connect to or retrieve information from discovered peers. This metric helps identify network connectivity issues, configuration problems, or periods of increased network instability. Use the discovery method filter to analyze errors specific to DHT or GossipSub peer discovery.

Percentage split of crawl errors per error cause

Measurement Tools

Our network monitoring employs advanced crawling and probing tools and techniques to gather comprehensive data about network health, topology, and performance

Our Tools

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DAS Guardian

A Data Availability Sampling tool to asses Ethereum Node's real custody
tool-abstract-7

Bitswap Sniffer

A CID sniffer for content in IPFS over Bitswap and DHT requests
Freepik

Tiros

A performance measurement tool for Kubo and IPFS-hosted websites.
AI Freepik

Parsec

A DHT and IPNI lookup performance measurement tool.
GarryKillian / Freepik

Ants

A DHT monitoring tool for NAT'd peers.
From GarryKillian / Freepik

Hermes

A lightweight GossipSub tracer.
Abstract Image 6

Nebula

A network agnostic DHT crawler and monitoring tool