# Understanding time\_in\_millis for ingest pipeline running embeddings

**URL:** <https://discuss.elastic.co/t/understanding-time-in-millis-for-ingest-pipeline-running-embeddings/382249>\
**Category:** Elasticsearch\
**Tags:** elastic-stack-machine-learning\
**Created:** [September 26, 2025, 11:15am UTC](https://discuss.elastic.co/t/understanding-time-in-millis-for-ingest-pipeline-running-embeddings/382249 "2025-09-26T11:15:36Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![gueri](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/gueri/32/103243_2.png) [@gueri](https://discuss.elastic.co/u/gueri)\
**Post date:** [September 26, 2025, 11:15am UTC](https://discuss.elastic.co/t/understanding-time-in-millis-for-ingest-pipeline-running-embeddings/382249/1 "2025-09-26T11:15:36Z")

</div>

Hi,

I try to figured out the meaning of time\_in\_millis field about my ingest pipelines running embeddings.

time\_in\_millis  
(integer) Total time, in milliseconds, spent preprocessing documents in the ingest pipeline.

In my case, I have a deployment for the bge-large-en-v1.5 model with 1 pipeline named embedding\_pipeline for embeddings.

> "trained\_model\_stats": [  
> {  
> "model\_id": "bge-large-en-v1.5",  
> "model\_size\_stats": {  
> "model\_size\_bytes": 1336505252,  
> "required\_native\_memory\_bytes": 6012339732  
> },  
> "pipeline\_count": 1,  
> "ingest": {  
> "total": {  
> "count": 24823,  
> "time\_in\_millis": 70866438,  
> "current": 0,  
> "failed": 0  
> },  
> "pipelines": {  
> "embedding\_pipeline": {  
> "count": 24823,  
> "time\_in\_millis": 70866438,  
> "current": 0,  
> "failed": 0,  
> "ingested\_as\_first\_pipeline\_in\_bytes": 100573518,  
> "produced\_as\_first\_pipeline\_in\_bytes": 638648261,  
> "processors": [ ...

I run a watcher every minute to collect statistics.

For example, this is results for the pipeline time\_in\_millis  
22:58:00 65,352,075  
22:59:00 65,671,555  
The difference is 319,480 ms so this is equal to 5 minutes approx.

I don't understand this time regarding the definition. Can someone explain me this result in a interval of 1 minute ???

Regards,

Eric

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<div class="post-metadata">

**Author:** ![Keith\_Massey](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/keith_massey/32/83666_2.png) [@Keith\_Massey](https://discuss.elastic.co/u/Keith_Massey)\
**Post date:** [September 26, 2025, 1:47pm UTC](https://discuss.elastic.co/t/understanding-time-in-millis-for-ingest-pipeline-running-embeddings/382249/2 "2025-09-26T13:47:22Z")

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`time_in_millis` is the [cumulative wall clock time](https://github.com/elastic/elasticsearch/blob/main/server/src/main/java/org/elasticsearch/ingest/IngestService.java#L1039) spent running the pipeline across all nodes. Is it possible you’re running ingest in multiple concurrent requests over that minute? It could be that one node is running 5 or more requests at once, or you have multiple ingest nodes?

---

<div class="post-metadata">

**Author:** ![gueri](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/gueri/32/103243_2.png) [@gueri](https://discuss.elastic.co/u/gueri)\
**Post date:** [September 30, 2025, 1:32pm UTC](https://discuss.elastic.co/t/understanding-time-in-millis-for-ingest-pipeline-running-embeddings/382249/3 "2025-09-30T13:32:32Z")

</div>

Hello,

Yes we run this configuration with 2 ML nodes :

```auto
  "deployment_stats": {
    "deployment_id": "bge-large-en-v1.5",
    "model_id": "bge-large-en-v1.5",
    "threads_per_allocation": 4,
    "number_of_allocations": 2,
    "queue_capacity": 1024,
    "state": "started",
    "allocation_status": {
      "allocation_count": 2,
      "target_allocation_count": 2,
      "state": "fully_allocated"
    },...

```

The Ingest is used for embeddings performed by a python script using helpers.bulk() calls to push the text chunks in Elastic.

In my case, I am looking the best practices for monitoring and troubleshooting the ingest behavior.

It’s why I try to understand the value of time\_in\_millis between 2 api \_stats collect.

Regards, Eric