📊 Banner 321/367
⚡ How it works (architecture deep-dive 🔬 for engineers)
This profile is a self-updating MLOps demo — a living portfolio showcasing production-grade automation.
- 🤖 Banner rotation: 367 GIFs · natural sorting · cache-busted CDN URLs
- 🧩 Dynamic insights: Context-aware NLG (time/season/DOW algorithms)
- ⏱️ Next Update badge: Shields.io endpoint · HLS gradient · sub-minute precision
- 📡 Observability: JSONL telemetry · heartbeat pings · state persistence
- ⚙️ Zero-touch ops: 5475+ runs · 133 mutations · idempotent commits
| File | Version | Description |
|---|---|---|
| update_readme.py |  |
Banner engine + NLG + JSONL pipeline |
| build_next_badge.py |  |
HLS gradient renderer + countdown |
| Workflow | Schedule | Status |
|---|---|---|
| Auto Update README | Daily 12:15 UTC |  |
| Next Update Badge | Every 20min |  |
| CI/CD Pipeline | On push/PR |  |
.
├─ update_log.jsonl # CI run timeline (1 JSON per run: ts_utc, run_id, run_number, sha, banner_*, insight_*)
├─ update_log.txt # Grep-friendly mirror of update_log.jsonl (ts UTC, run=…, sha=…; rolling tail)
├─ badges/
│ ├─ next_update.json # Live Shields.io badge state (label, message like '~14h 35m', color bucket)
│ ├─ next_update_log.jsonl # Badge countdown snapshots (ts, next_utc, minutes_left, message, color, jitter params)
│ ├─ next_update_log.txt # Human-readable badge ETA tail ([ts] color=… msg='…' next_utc=… mins_left=…)
│ ├─ github_followers.json # Endpoint payload for the Followers badge (schemaVersion/label/message/color)
│ ├─ github_stars.json # Endpoint payload for the Stars badge
│ └─ total_updates.json # Endpoint payload for the Updates badge
└─ .ci/
├─ heartbeat.log # GitHub Actions heartbeat ledger (Updated on / Triggered by / Commit SHA / Run ID / Run number)
└─ update_count.txt # Monotonic mutation counter (powers the «N mutations shipped» tagline)
📋 Browse logs:
📊 update_log.jsonl ·
📝 update_log.txt ·
💓 heartbeat.log ·
🔢 update_count.txt
⏱️ next_update.json ·
📡 next_update_log.jsonl ·
📋 next_update_log.txt
👥 github_followers.json ·
⭐ github_stars.json ·
📈 total_updates.json
Now
- ☁️ AWS CCP (CLF-C02) — CloudWolf (active learning)
- 🧱 Azure Data Engineering Projects (Udemy):
- Databricks Lakehouse (Formula1 — batch & lakehouse design)
- Data Factory pipelines (Covid19 — ingestion & orchestration)
- Azure Synapse Analytics (NYC Taxi — analytics & SQL warehouse)
Next
- 🧪 More portfolio releases: architecture diagrams, CI/CD, and production-style enhancements
Focus
- Data Engineering | MLOps | SQL | Automation
- Building cloud-native, cost-aware data platforms
🧭 2+ years of continuous, hands-on learning with a strong focus on real-world projects and automation
- 🎓 SuperDataScience — MLOps & AI specialization
- 📘 Udemy — Data Engineering & Cloud projects
- ☁️ CloudWolf — AWS Cloud & Certification preparation
| 🌐 Platform | 🔗 Link |
|---|---|
| 🧠 GitHub | Evgenii Matveev |
| 📁 Portfolio | Data Science Portfolio |
| Evgenii Matveev |
💫 AI Copilot Ecosystem
| Assistant | Role | Usage |
|---|---|---|
| ChatGPT 5.2 | Core copilot for architecture & automation | Rapid execution |
| Claude Sonnet 4.5 | Contextual planner & strategic reasoner | Long-range thinking |
💡 Note: Dual-Copilot Workflow
This ecosystem operates as a dual-copilot workflow — two AI systems working in synergy:
- ChatGPT → architecture, reasoning, documentation
- Claude Sonnet 4.5 → long-context planning & strategic alignment
This dual-copilot system balances speed and depth —
ChatGPT executes and refines · Claude plans and connects.
Together they form my AI-powered engineering loop for continuous innovation.
✨ Optimized for precision, powered by automation, evolving through insight.
🤖 Automation Logs
🪄 Run Meta (click to expand)
- 📆 Updated (UTC): 2026-01-10 13:03 UTC
- 🤖 Run: #5605 — open run
- 🧬 Commit: e4036c2 — open commit
- ♻️ Updates (total): 226
- 🌀 Workflow: Auto Update README · Job: update-readme
- ✨ Event: schedule · 🧑💻 Actor: evgeniimatveev
- 🕒 Schedule: 24h_5m
- 🌈 Banner: 321/367
🗂️Recent updates (last 5)
| Time (UTC) | Run | SHA | Banner | Event/Actor | Insight |
|---|---|---|---|---|---|
| 2026-01-10 13:03:13 | 5605 | e4036c2 |
321/367 (321.gif) | schedule/evgeniimatveev | 📡 PIPELINES, NOT FIRE-DRILLS • RUN #5605 — Deep work: schema design & contracts ❄️ | Weekend automation vibes! 🎉 Measure → iterate →… |
| 2026-01-09 13:09:03 | 5604 | a8f8ced |
320/367 (320.gif) | schedule/evgeniimatveev | 📡 SHIP SMALL, SHIP OFTEN • RUN #5604 — Great time for infra upgrades 🛠️ | Wrap it up like a pro! ⚡ Optimize, deploy, repeat! 🔄 📊 |
| 2026-01-08 13:17:10 | 5603 | 379930e |
319/367 (319.gif) | schedule/evgeniimatveev | 📡 REPRODUCIBILITY FIRST • RUN #5603 — Hibernate And Optimize 🧊 | Test, Iterate, Deploy! 🚀 Optimize, Deploy, Repeat! 🔄 🤖 |
| 2026-01-07 13:09:05 | 5602 | 6f1fd65 |
318/367 (318.gif) | schedule/evgeniimatveev | 📡 EXPERIMENT → INSIGHT → DEPLOY • RUN #5602 — GREAT TIME FOR INFRA UPGRADES 🛠️ | HALFWAY THERE — KEEP AUTOMATING! 🛠️ SHIP A THIN SLI… |
| 2026-01-06 13:07:01 | 5601 | 17c3d34 |
317/367 (317.gif) | schedule/evgeniimatveev | 📡 AUTOMATE EVERYTHING • RUN #5601 — Harden CI, Cache Models, Reduce Cold Starts 🧊 | Keep Up The Momentum! 🔥 Guardrails On, Feature F… |
Night-mode palettes · Daily A–G theme rotation · Fully automated via GitHub Actions
| 🧩 Workflow | ⚙️ Automation | 📊 Insights |
|---|---|---|
| Design → Build → Scale | Deploy CI/CD with intelligence | Measure → Learn → Improve |
- ⚙️ Automate end-to-end ML pipelines (train → eval → deploy)
- 📈 Track experiments with MLflow & W&B; analyze runs via PostgreSQL/SQL
- 📉 Build stakeholder dashboards in Tableau / Power BI
🤖 MLOPS Insight: 📡 PIPELINES, NOT FIRE-DRILLS • RUN #5605 — Deep work: schema design & contracts ❄️ | Weekend automation vibes! 🎉 Measure → iterate → ship 🚀 📦
📈 Auto GitHub Insights (UTC · auto-refresh)
Daily contributions (last 30 days)
