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Modal

Made Crystal Clear

A practical, visual guide to running Python, GPUs and AI workloads in the cloud, paying only while your code runs

Every GPU tutorial ends the same way: a machine you forgot to turn off. Modal sells the other unit, functions and seconds. This guide takes you from pip install modal to a deployed vLLM endpoint your OpenAI client code already speaks, through environments written as Python, cron jobs and web APIs that cost pennies a month, GPUs picked by arithmetic instead of spreadsheet, and Sandboxes for code an LLM wrote. It treats the catches as content: cold starts measured before the levers, and the break-even worksheet that says when per-second billing stops winning. Every price is dated and every vendor claim is attributed.

Pages
198
Level
Beginner to advanced
Status
Available
Kindle · $12.99 ↗Paperback · $39.99 ↗Give feedback

Inside the book

  1. 01The End of Paying for Idle
  2. 02The Big Picture: How Modal Thinks
  3. 03Zero to Cloud in Ten Minutes
  4. 04Images: Your Environment as Python Code
  5. 05Python in the Cloud 24/7: Cron Jobs and Web Endpoints
  6. 06GPUs on Demand: Picking Hardware Without a Spreadsheet
  7. 07Volumes: Where Model Weights Live
  8. 08Ship an LLM Endpoint: vLLM in Production Shape
  9. 09Cold Starts, Solved Honestly
  10. 10Scaling Out: Map, Spawn, and Training Runs
  11. 11Sandboxes: A Safe Room for Untrusted Code
  12. 12The Money Chapter: What Modal Really Costs
  13. 13Production: Secrets, Regions, Budgets, and Sleep
  14. 14Your 90-Day Path and the One-Page Cheat Sheet
  15. 15Resources: The Short List Worth Your Time

You'll leave with

  • Understand what happens between your decorator and a billed second, and why idle costs zero
  • Write your environment as Python, with model weights baked in at build time
  • Ship a cron job and a locked web endpoint for pennies a month, no GPU required

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Sources

Every source cited in Modal Made Crystal Clear. Each number matches the [n] marker next to that link in the book's "Go deeper" lists, so you can trace any claim back to its origin.

  1. [1]Modal homepage
  2. [2]Modal customer stories
  3. [3]Latent Space: "Truly Serverless Infra for AI Engineers"
  4. [4]Erik Bernhardsson: "What I have been working on: Modal"
  5. [5]Coiled: a GPU-accelerated serverless alternative to AWS Lambda
  6. [6]Hacker News: practitioners on Modal
  7. [7]Modal pricing
  8. [8]Functions guide
  9. [9]Images guide
  10. [10]Autoscaling guide
  11. [11]Hello world example
  12. [12]Web endpoints guide
  13. [13]Modal changelog
  14. [14]Edlitera's Modal tutorial
  15. [15]modal.com/docs/guide/images
  16. [16]modal.com/docs/guide/existing-images
  17. [17]modal.com/docs/examples/hello_world
  18. [18]Scheduling remote cron jobs
  19. [19]The Server primitive
  20. [20]GPU acceleration guide
  21. [21]Billing guide
  22. [22]GPU cold starts and VRAM math
  23. [23]Volumes guide
  24. [24]Cloud bucket mounts
  25. [25]Dicts
  26. [26]Queues
  27. [27]Deploying a vLLM server on Modal
  28. [28]Modal docs: Functions
  29. [29]Modal docs: Web endpoints
  30. [30]Modal docs: Volumes
  31. [31]Modal docs: GPU acceleration
  32. [32]Modal: Cold start performance
  33. [33]Modal: Memory snapshots
  34. [34]Modal: GPU memory snapshots
  35. [35]Modal: GPU snapshot example
  36. [36]Modal: engineering talk on the container stack
  37. [37]Scaling out (Modal docs)
  38. [38]Substack case study (Modal)
  39. [39]Sandboxes guide
  40. [40]Sandboxes product page
  41. [41]The safe_code_execution example
  42. [42]JavaScript and Go SDKs
  43. [43]Security guide
  44. [44]Budgets
  45. [45]Introl: serverless GPU platforms compared
  46. [46]GPU Tracker: serverless GPU comparison
  47. [47]Secrets guide
  48. [48]Region selection
  49. [49]Developing and debugging
  50. [50]OpenTelemetry integration
  51. [51]Managing deployments
  52. [52]Web Function URLs
  53. [53]modal.com

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