Performance: Adding multiple indexes in term query in a search request

Elastic Stack Elasticsearch
1

I intend to use query_string and term queries (across multiple indexes) on _search.
My combined query is this,

"query": {
"bool": {
"must": [
{
"query_string": {
"fields": [
"*"
],
"query": "tes"
}
}
],
"should": [
{
"bool": {
"must": [
{
"terms": {
"_index": ["people", "organization"]
}
}
],
"should": [
{
"terms": {
"zoneId": [1, 51]
}
},
{
"term": {
"ownerId": 1
}
}
],
"minimum_should_match": 1
}
},
{
"bool": {
"must": [
{
"terms": {
"_index": ["event", "meeting"]
}
},
{
"term": {
"ownerId": 1
}
}
]
}
},
{
"bool": {
"must": [
{
"term": {
"_index": "activity"
}
}
]
}
},
{
"bool": {
"must": [
{
"terms": {
"_index": ["note", "attachment"]
}
}
],
"should": [
{
"bool": {
"must": [
{
"terms": {
"source": ["event", "meeting"]
}
}
],
"should": [
{
"terms": {
"territoryId": [1,51]
}
},
{
"term": {
"ownerId": 1
}
}
],
"minimum_should_match": 1
}
},
{
"bool": {
"must": [
{
"term": {
"source": "activity"
}
},
{
"term": {
"ownerId": 1
}
}
]
}
}
],
"minimum_should_match": 1
}
}
],
"minimum_should_match": 1
}
}
}

How would the performance be if I performed a query on 100k records? Or should I use _msearch by breaking the query down based on index? If multiple users are sending requests how would the network overhead would be? Would there be latency? Thank you for any clarifications