Comparison
awesome-open-mlops vs keras
Verdict
Pick awesome-open-mlops when tags unique to awesome-open-mlops: machinelearning, datascience, mlops, infrastructure; pick keras when tags unique to keras: data-science, neural-networks, deep-learning, python.
Markdown twin · awesome-open-mlops alternatives · keras alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | awesome-open-mlops | keras |
|---|---|---|
| Maintenance | Dormant (418d since push) As of today · github_public_v1 | Very active (4d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No criticals As of today · osv@v1 |
Tagline
- awesome-open-mlops
- The Fuzzy Labs guide to the universe of open source MLOps
- keras
- Deep Learning for humans
Stars
- awesome-open-mlops
- 482
- keras
- 64k
Forks
- awesome-open-mlops
- 54
- keras
- 20k
Open issues
- awesome-open-mlops
- 6
- keras
- 228
Language
- awesome-open-mlops
- -
- keras
- Python
Adopt for
- awesome-open-mlops
- -
- keras
- -
Persona
- awesome-open-mlops
- -
- keras
- -
Runtime
- awesome-open-mlops
- -
- keras
- -
License
- awesome-open-mlops
- Apache-2.0
- keras
- Apache-2.0
Last pushed
- awesome-open-mlops
- May 19, 2025
- keras
- Jul 7, 2026
Categories
- awesome-open-mlops
- AI Agents, Model Training, Inference & Serving
- keras
- Model Training, Inference & Serving
Trust and health
Maintenance
- awesome-open-mlops
- Dormant (18%)
- keras
- Very active (96%)
Days since push
- awesome-open-mlops
- 418d
- keras
- 4d
Open issues (now)
- awesome-open-mlops
- 6
- keras
- 228
Security scan
- awesome-open-mlops
- No lockfile
- keras
- No criticals
Full report
- awesome-open-mlops
- Trust report
- keras
- Trust report
Choose awesome-open-mlops if…
- Tags unique to awesome-open-mlops: machinelearning, datascience, mlops, infrastructure.
- Also covers AI Agents.
- Leaner open-issue backlog (6).
When NOT to use awesome-open-mlops
- Last GitHub push was 418 days ago (dormant maintenance, May 19, 2025). Validate activity before betting a new project on awesome-open-mlops.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Choose keras if…
- Tags unique to keras: data-science, neural-networks, deep-learning, python.
- More GitHub stars (64k vs 482) - visibility, not fit.
When NOT to use keras
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (fuzzylabs/awesome-open-mlops) · observed Jul 11, 2026
- GitHub forks (fuzzylabs/awesome-open-mlops) · observed Jul 11, 2026
- Last push (fuzzylabs/awesome-open-mlops) · observed May 19, 2025
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (keras-team/keras) · observed Jul 11, 2026
- GitHub forks (keras-team/keras) · observed Jul 11, 2026
- Last push (keras-team/keras) · observed Jul 7, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-open-mlops 482 · keras 64k (synced Jul 11, 2026).
Common questions
- What is the difference between awesome-open-mlops and keras?
- awesome-open-mlops: The Fuzzy Labs guide to the universe of open source MLOps. keras: Deep Learning for humans. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-open-mlops over keras?
- Choose awesome-open-mlops over keras when Tags unique to awesome-open-mlops: machinelearning, datascience, mlops, infrastructure; Also covers AI Agents; Leaner open-issue backlog (6).
- When should I choose keras over awesome-open-mlops?
- Choose keras over awesome-open-mlops when Tags unique to keras: data-science, neural-networks, deep-learning, python; More GitHub stars (64k vs 482) - visibility, not fit.
- When should I avoid awesome-open-mlops?
- Last GitHub push was 418 days ago (dormant maintenance, May 19, 2025). Validate activity before betting a new project on awesome-open-mlops. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- When should I avoid keras?
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- Is awesome-open-mlops or keras more popular on GitHub?
- keras has more GitHub stars (64,191 vs 482). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-open-mlops and keras open source?
- Yes - both are open-source projects on GitHub (awesome-open-mlops: Apache-2.0, keras: Apache-2.0).
- Where can I find alternatives to awesome-open-mlops or keras?
- GraphCanon lists graph-backed alternatives at awesome-open-mlops alternatives and keras alternatives (awesome-open-mlops markdown twin, keras markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, awesome-open-mlops or keras?
- awesome-open-mlops: Dormant. keras: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for awesome-open-mlops and keras?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-open-mlops trust report; keras trust report.