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systems-product-tools.md

Systems, infrastructure and digital product tools and hints

Table of Contents

General

Infrastructure as Code

Logging

Tracing

  • Zipkin
  • Jaeger
  • OpenTelemetry

Alerting, Monitoring & Observability

Networking

PaaS: Platform as a Service

CI/CD

  • act: Run your GitHub Actions locally!

Data visualization and dashboards

Querying

Data analytics

Data Science and Machine Learning

  • Debezium: Change Data Capture (CDC)
  • Streamlit: Streamlit turns data scripts into shareable web apps in minutes. All in pure Python. No front‑end experience required.
  • Hugging Face Spaces: Hugging Face Spaces offer a simple way to host ML demo apps directly on your profile or your organization's profile. [Backend]
  • Gradio): Gradio is the fastest way to demo your machine learning model with a friendly web interface so that anyone can use it, anywhere! [Frontend]
  • MLFlow: MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry.
  • MLOps: end-to-end machine learning development process to design, build and manage reproducible, testable, and evolvable ML-powered software.
  • Kubeflow: Kubeflow is an open-source platform for machine learning and MLOps on Kubernetes.
  • VertexAI (GCP): machine learning (ML) platform that lets you train and deploy ML models and AI applications, and customize large language models (LLMs) for use in your AI-powered applications. Fast, scalable, and easy-to-use AI technologies. Branches of AI, network AI, and artificial intelligence fields in depth on Google Cloud.
  • Model Cards Google Cloud: the README.md for AI models. Model cards aim to provide a concise, holistic picture of a machine learning model. The value of a shared understanding of AI models.
  • Amazon SageMaker: Build, train, and deploy machine learning models for any use case with fully managed infrastructure, tools, and workflows. Amazon SageMaker is a cloud machine-learning platform that enables developers to create, train, and deploy machine-learning models in the cloud. It also enables developers to deploy ML models on embedded systems and edge-devices.

Security

Testing

Chaos engineering

Feature toggles/flags

Development and ephemeral environments

Internal Developer Platform

Serverless

Databases

Backoffice

REST APIs

Database migrations

Marketing and user behavior analytics

  • HotJar: Website Heatmaps & Behavior Analytics Tools
  • Clarity (from Microsoft): free user behavior analytics tool, Free Heatmaps & Session Recordings
  • LogRocket: Session Replay | Product Analytics | Error Tracking | Identify technical and UX issues with our AI, quantify impact with analytics, and then watch session replays to see exactly what went wrong
  • Google Tag Manager: measure your advertising ROI
  • Product updates announcement: https://announcekit.app/

Tools for online events

Social networks

  • GetStream: Build In-App Chat. Video & Audio + Feeds

Hotspots and code analysis

Playgrounds

Books and other resources

LLMs

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