Start with a question
A homelab is most useful when it gives a practical question somewhere to go. Can a compact ARM cluster run a useful MongoDB workload? What changes when the database working set exceeds its cache? How can a local model answer from documents with traceable evidence?
The public projects on this site explore those questions through code and measurements. Each project is a starting point for another experiment.
Make the build reproducible
The MongoDB ARM project uses Ansible to turn configuration and operating procedures into repeatable steps. Deployment, monitoring, updates, and platform start and stop procedures belong to the same engineering story.
Automation helps separate an intentional setup from a machine that only works because of forgotten manual changes. It also makes the repository useful to someone building their own version.
Observe before concluding
Running a workload is only the beginning. Throughput needs context: operation mix, acknowledgement settings, dataset size, client concurrency, and measurement duration all affect what a result means.
The MongoDB memory experiments distinguish host-kernel huge pages, user-space allocator state, and WiredTiger cache behavior. These layers interact, but seeing activity in one is not proof of an application-level improvement.
The RAG project raises a related problem. Retrieving an expected source, citing it correctly, and producing a correct answer are separate outcomes. Evaluation should preserve that distinction.
Connect applications to infrastructure
The lab provides a way to follow a system through several layers:
- Applications: ingestion, retrieval, prompt assembly, and generation.
- Data: indexing, cache behavior, replication, and storage.
- Operations: automation, observability, and lifecycle management.
This is a conceptual view of the experiments. It describes areas of learning without presenting a network inventory or a live service map.
Share useful evidence
Public notes should help a reader understand the method and reproduce an experiment in their own environment. Generic node roles, reference diagrams, documented workload settings, and selected results are useful for that purpose.
Internal addresses, hostnames, service access paths, private document names, credentials, and administrative dashboards do not belong in these articles. Public diagrams use abstract roles and do not describe the current private deployment.
Follow the experiments
The MongoDB build article introduces the compact platform. The memory deep dive follows it into controlled measurement. The RAG Gateway article explores the application layer, including its local and cloud data boundaries.