Latest Blog
What Hardware and Software Factors Enable Fast Immich Recovery?
Fast Immich recovery combines complete originals and database state with compatible software, adequate I/O, and a timed restore sequence.
Immich Caching: How Warm Data Changes Repeated Requests
Warm Immich requests reuse model, database, media, and client state; pair cold and repeated measurements to avoid overstating real capacity.
Immich in a Multi-App Home Server: How Shared Resources Change Results
See why Immich behaves differently on a multi-app host and use a controlled pause test to identify the shared resource changing the result.
Why Is Immich Moving Toward More Local Processing?
Immich local processing keeps photo analysis near private data and reduces cloud dependence, while shifting performance and recovery duties to the operator.
How to Test Whether Immich Is CPU-, Memory-, Network-, or Storage-Bound
Diagnose an Immich bottleneck by fixing the workload, correlating latency with resource waits, and verifying one suspected limit at a time.
How Many Concurrent Tasks Can Immich Handle Before Search Responsiveness Degrades?
Find a defensible Immich concurrency limit by measuring search latency and queue progress while background photo jobs compete for shared resources.
Open Models Are Catching Frontier AIโIs 2026 the Year Local AI Becomes Good Enough?
Open models are getting good enough for more local AI workloads, while frontier cloud models remain useful for the hardest reasoning and agent tasks.
NVIDIA PAIR Turns Your Home Network Into a Local AI ClusterโDo You Still Need One Big GPU Server?
NVIDIA PAIR spreads local AI requests across multiple PCs, making compute more elastic while one home server can keep data and state persistent.
