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OpenNebula: History, Description & Overview
OpenNebula is an open source cloud computing platform for managing heterogeneous data center, public cloud and edge computing infrastructure resources. OpenNebula manages on-premises and remote virtual infrastructure to build private, public, or hybrid implementations of infrastructure as a service (IaaS) and multi-tenant Kubernetes deployments. The two…
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OpenNebula topic overview
The analysis highlights History, Description and Overview as prominent areas in the source structure around OpenNebula.
Related topics
28
Source areas
5
Connected nodes
33
Extracted relationships
221
Concept neighborhoods
12
Bridge connections
33
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Overview · 14 topics
Description · 8 topics
Internal architecture · 3 topics
History · 2 topics
Development · 1 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Hypervisors (VMware vCenter, KVM, LXD/LXC, and AWS Firecracker)
Release
July 24, 2008; 18 years ago (2008-07-24)
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How OpenNebula connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around OpenNebula shows recurring relationship patterns in the source. For example, OpenNebula → ACLs, Additional, AI, AI-powered, AI-ready, API, APIs, App, Archeon, ARM, As, AWS, AWS Firecracker, Axelera AI, Blue Flash, Boomerang, Bubble, C12G Labs, CBT, Ceph Another extracted example is OpenNebula → Cluster, Context, DHCP, DNS, Host, Image, Instantiated Template, IP, IPv4, IPv6, It, Physical, Pool, Template, The, They, Underlying, Virtual, Virtual Machine, Virtual Machines. Use these groups to spot repeated connection types before inspecting the individual relationships.
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 221 structured relationships around OpenNebula. Examples in this analysis include OpenNebula → Available in → English, Czech, French, Slovak, Spanish, Chinese, Thai, Turkish, Portuguese, Turkish, Russian, Dutch, Estonian, Japanese and OpenNebula → Developers → OpenNebula Systems, OpenNebula Community. The table shows each extracted connection, where it came from and its confidence.
Hypervisors (VMware vCenter, KVM, LXD/LXC, and AWS Firecracker)
1.00
infobox
OpenNebula
Release
July 24, 2008; 18 years ago (2008-07-24)
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infobox
OpenNebula
Repository
github.com/OpenNebula/one
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infobox
OpenNebula
Stable release
7.4 / 27 July 2026; 28 days ago (2026-07-27)
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infobox
OpenNebula
Type
Cloud computing
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infobox
OpenNebula
Website
opennebula.io
1.00
infobox
OpenNebula
Written in
C++, Ruby, Shell script, lex, yacc, JavaScript
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infobox
OpenNebula
is a
open source cloud computing platform for managing heterogeneous data center
0.90
text
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around OpenNebula bring nearby vocabulary together. In this analysis, examples include Services, Community and Virtualization. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
OpenNebula
Services
Community
Virtualization
Data
Platform
Hypervisor
Physical
Machine
Network
Virtual
Center
Version
opennebula
Services
Community
Virtualization
Data
Platform
Hypervisor
Physical
Machine
Network
Virtual
Center
Version
cloud computing
Platform
Center
Opennebula
Also
Data
Vmware
Version
Support
New
Virtualization
Kvm
Vcenter
data center
Center
Data
Kvm
Platform
Virtualization
Cloud
Opennebula
Subsystem
Storage
Vmware
Network
Based
public cloud
Platform
Center
Opennebula
Also
Data
Vmware
Version
Support
New
Virtualization
Kvm
Vcenter
virtual infrastructure
Hybrid
Platform
Datastores
Vmware
Integration
Network
Added
Management
Hosts
Version
Based
Support
vmware
Vcenter
Kvm
Also
Cloud
Integration
Community
Platform
Enhanced
Hypervisor
Improvements
Infrastructure
Networks
open cloud computing interface
Platform
Center
Opennebula
Also
Data
Vmware
Version
Support
New
Virtualization
Kvm
Vcenter
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For OpenNebula, one of the stronger structural bridges in this analysis connects OpenNebula with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
OpenNebula
Nodes34
Edges33
Triples221
Avg. degree1.94
Density0.058824
Components1
Source & methodology
TTTA analyzes the structure around OpenNebula to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Description & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
