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Livebook
4 posts about Livebook. Every summary links to the original.
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AI GPU Clusters, From Your Laptop, With Livebook
Livebook, FLAME, and the Nx stack combine Elixir notebooks, elastic execution, and GPU-backed machine learning into a workflow that can move from a laptop to remote infrastructure. Livebook can start runtimes on Fly Machines, connect to existing Erlang/Elixir applications, and synchronize notebook dependencies and modules across nodes while preserving access to private resources within a Fly organization. FLAME wraps arbitrary code in Flame.call, manages executor pools, controls node limits and concurrency, streams results, and shuts down idle nodes or the cluster after disconnection. In the demonstrated AI workflow, video stills are processed on GPU Fly Machines with Llama, then Mistral summarizes the returned descriptions. The same setup also drives a 64-GPU hyperparameter run for BERT, with each L40s node preparing dependencies, loading data, fine-tuning, and streaming chart results to Livebook.
Better Business Intelligence in Elixir with Livebook
The post argues that Elixir developers already perform business intelligence when they use iex or a Rails console to query application data, calculate figures, and produce CSV rows for managers. It presents Livebook as a more capable alternative for young projects that need analysis without adopting a large, continuously running BI application such as Metabase. Because notebooks execute Elixir code and can communicate with running applications through BEAM/OTP clustering, they can reuse business logic, Ecto schemas, associations, and external integrations such as Stripe while avoiding direct database access. Livebook also supplies charts, graphs, tables, Markdown-based sharing, and reproducible reruns, with WireGuard enabling secure connections to apps on Fly.io. The resulting notebooks can answer onboarding, sales, and integration questions while preserving work that may later support an admin dashboard.
FYI: Livebook 0.2 with Kino
Livebook 0.2 was released with Kino, a client-side-focused feature for animating data changes, alongside new input support and the data_table feature. Elixir cells can read input values with IO.gets("input name: "), although those values arrive as strings and may require parsing or other processing. data_table presents data in a table with pagination and sorting, while Livebook is positioned for teaching Elixir, documenting libraries, experimenting with Nerves and embedded hardware, and connecting to a live production system. The post also notes that ElixirConfEU and ElixirConf US 2021 were announced as hybrid or mixed-format events, with ElixirConfEU scheduled for September 9–10 and ElixirConf US for October 12–15 across physical and online sessions.
Livebook is a secret weapon for documentation
The post presents Livebook as an interactive way to document the central logic of an Elixir or Phoenix application, helping new developers understand and explore code alongside existing documentation and tests. Using a TicTac example, it documents and executes the GameState module and struct, then describes and demonstrates a Horde-managed GenServer that runs the game state. Livebook connects to an existing project through a Mix standalone runtime, providing Elixir code completion, Markdown explanations, execution, and access to operations such as Ecto queries, context calls, and starting GenServers. The resulting notebooks are plain Markdown files, can be stored in source control, and support experimentation, reviewable diffs, and collaborative editing. The setup described requires Elixir 1.12: install Livebook with mix escript.install hex livebook, start livebook server, and connect through the locally generated token URL.
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