[Discuss] Performance benchmarking improvements for Opensearch #3983
Description
Currently we have a very basic performance test suite(link) where we execute a single workload nyc_taxis
on a single node cluster and capture the metrics. I wanted to open a discussion for process improvements in benchmarking Opensearch(periodically as well as during every release). This would help in a more through benchmarking and ensuring that we don't miss out on any regression.
Listing down few high level improvements that i can think of. Feel free to add more test scenarios.
1. Testing different cluster configurations
We should also cover different cluster configurations(multi-node clusters, with/without replicas(logical/physical), Multi-AZ configurations, Instance types varying compute, memory and storage(EBS/SSD).
2. Testing with different workloads
Existing list of workloads are mentioned here.
We should add different types of workload to simulate different traffic types like:
geonames
for structured data.pmc
for full text search.nested
for nested documents.
Apart from the existing workloads, we need workloads with higher volume of data(highest is nyc_taxis
with 75 GB approx.). Here is an existing issue on Opensearch-benchmark for the same. Workloads like these would definitely help benchmarking larger clusters (like 100 nodes!!) which reflect real workload of biggest consumers of Opensearch.
3. Benchmarking other usecase(core or plugins)
Apart from search and indexing, we also need benchmarks for other features which are present in core or external plugins. Few examples are:
- Snapshots.
- Reindexing.
- Security plugin.
- Cross cluster search/replication.
- Remote reindex.
- Async search.
- SQL.
- Index management.
- Segment Replication.
- Remote store.
- Pluggable Translog.