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PRIVATE PROJECT / ARCHITECTURE WALKTHROUGH

Local LLM inference workstation

A Linux workstation for local model inference using Ollama and isolated service environments.

Engineering notes by Ubaid Bin Waris

HP Z84096GB RAMLinuxOllamaDocker
SYSTEM BLUEPRINTFIG. 05
  1. 01Application build
  2. 02Container runtime
  3. 03Proxy & network
  4. 04Monitor & recover
DESIGNED AROUND YOUR WORKFLOWINPUT → OUTCOME

The repository is private or client-owned. This is a high-level architecture walkthrough; source code and confidential project details are not published.

01 / THE PROBLEM

What the system needs to solve

Running models on owned hardware introduces memory, model-size and concurrency constraints that managed APIs usually hide.

02 / THE APPROACH

How the pieces fit together

  1. Select model sizes and quantization settings to fit the available memory.
  2. Isolate supporting services and expose inference through an application boundary.
  3. Document configuration, restart procedures and resource constraints.

03 / THE TRADEOFFS

Engineering is a set of choices

Local hosting offers control over deployment and data handling, but hardware limits affect throughput, model choice and operating effort.

04 / VALIDATION CONSIDERATIONS

What to test before relying on it

Evaluate representative prompts, sustained memory use and concurrent requests. Record model and quantization settings alongside any benchmark results.

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