Determining The Hardware Needed for Scaling Time Series Usage
TLDR A sought advice on the hardware needed to scale up Time Series usage. Kishore Nallan recommended 2.5x disk data size for memory, with CPU dependant on data updates and query concurrency.
Powered by Struct AI
2
3w
Solved
Sep 09, 2023 (3 weeks ago)
A
A
04:15 AMWhat’s a good rule of thumb for knowing how many machines / cpus / ram we need for scaling up TS usage? I know it’s a bit of a vague question and it depends on multiple factors such as length of query, etc, but any kind of wisdom would be appreciated
Kishore Nallan
Kishore Nallan
09:54 AMHi Azib. Roughly 2.5x memory requirement for the size of data on disk. CPU will largely depend on how often you update the data and query concurrency.
Typesense
Lightning-fast, open source search engine for everyone | Knowledge Base powered by Struct.AI
Indexed 2779 threads (79% resolved)
Similar Threads
Evaluating Correct Cluster Size/Configuration
Nathan asked which metrics/graphs to focus on to evaluate cluster size/configuration. Jason suggested CPU usage and RAM usage, ideally below 70%.
4
3mo
Solved
Typesense Memory Issues and Scaling Concerns
David raised concerns about Typesense's memory usage in their project. Jason provided guidelines for calculating RAM requirements.
3
3mo
Solved
Timeseries Data and Typesense for Large Datasets
Josh asks if Typesense is suitable for their use case with timeseries data, high qps, and 40TB+ datasets. Jason suggests considering Elasticsearch for such scale.
27
8mo
Solved