Portfolio concentration
63%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
29 repos
Visible snapshot
15 repositories updated in the last 90 days.
Leading language
Python
Portfolio mix
Python (10), Unknown (5), HTML (5)
Average size
2
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
63%
of the visible star count comes from this organization's top three repositories.
2
stars per repository in this same snapshot.
Python
is the most common language here, with 15 repositories updated in the last 90 days.
Why this rank
This organization stands out because its public portfolio is relatively balanced across 29 repositories.
Organization pages work best when you separate portfolio breadth from flagship concentration. In DigitalOcean's case, the visible top three repositories account for about 63% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.
The dominant language mix here is Python (10), Unknown (5), HTML (5). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
| # | Repository | Language | Stars |
|---|---|---|---|
| 1 | digitalocean/claudo Run Claude Code against DigitalOcean Gradient AI. Spins up a local LiteLLM proxy to bridge Claude Code's Anthropic API format to DO's OpenAI-compatible endpoint | Shell | 15 |
| 2 | digitalocean/gradient-adk-templates Contains example agents for Gradient ADK. | Python | 10 |
| 3 | digitalocean/CodexPlugin | Python | 7 |
| 4 | digitalocean/ghost-writer Agentic Blogging | Python | 7 |
| 5 | digitalocean/sample-rust ⛵ App Platform sample rust application. | Rust | 3 |
| 6 | digitalocean/litellm Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, VLLM, NVIDIA NIM] | Python | 2 |
| 7 | digitalocean/do-obsd DigitalOcean observability supervisor. | Shell | 2 |
| 8 | digitalocean/benchmark-harness OpenRouter TypeScript harness for reproducible LLM benchmarks and evaluations. | Shell | 1 |
| 9 | digitalocean/litellm-os Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, VLLM, NVIDIA NIM] | 1 | |
| 10 | digitalocean/pmm-headless Percona Monitoring and Management: an open source database monitoring, observability and management tool | 1 | |
| 11 | digitalocean/arp-doks-fix | 1 | |
| 12 | digitalocean/sample-dotnet | HTML | 1 |
| 13 | digitalocean/crewai-ohr-e2e-fixture CrewAI Crew fixture for Open Harness Runtime | Python | 0 |
| 14 | digitalocean/tester Convenient tooling for scheduling, running, and reporting on go tests. | Go | 0 |
| 15 | digitalocean/mars-competitor-pulse | Python | 0 |
| 16 | digitalocean/marketplace-agents | Python | 0 |
| 17 | digitalocean/handy-fleet-packaging | Python | 0 |
| 18 | digitalocean/dorate_testing | 0 | |
| 19 | digitalocean/go-diskfs | Go | 0 |
| 20 | digitalocean/New-App-Management-UXNext | HTML | 0 |
| 21 | digitalocean/AI-Assistant-Entry-Point-UXNext | HTML | 0 |
| 22 | digitalocean/AI-Assistant-Intent-Platform-UXNext | HTML | 0 |
| 23 | digitalocean/Onboarding_Q2_2026_Proposal_UXNext | HTML | 0 |
| 24 | digitalocean/spawn Spawn any agent, on any cloud | TypeScript | 0 |
| 25 | digitalocean/ShellPort Ephemeral Coding Interview Workstation | JavaScript | 0 |
| 26 | digitalocean/RevOps | JavaScript | 0 |
| 27 | digitalocean/kaniko Build Container Images In Kubernetes | 0 | |
| 28 | digitalocean/llama-index-retrievers-digitalocean-gradientai LlamaIndex retriever integration for DigitalOcean Gradient Knowledge Base | Python | 0 |
| 29 | digitalocean/llama-index-llms-digitalocean-gradientai | Python | 0 |
Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.
For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.