Keep your eye on this page for known issues and troubleshooting tips.

You can run bin/enterprise-search --help for more information.

Reset passwordedit

If you’ve lost access to Enterprise Search, you can recover specific users or reset all access to Enterprise Search.

Refer to the following sections in the Enterprise Search documentation:

Log indicesedit

Enterprise Search creates several log indices. You can create dashboards for these indices within Kibana, or you can query these indices using Elasticsearch.

For a list of these indices, see Log retention in the Enterprise Search documentation.

Capturing Diagnosticsedit

Running the binary with the --diagnostic-report flag to capture a diagnostic bundle:

bin/enterprise-search --diagnostic-report

The bundle generates a zipped folder, with the following structure:

- app_info.json
- config.json
- elasticsearch_info.json
- logs
  - stats.log
  - system.log
- recent_jobs_info.json
- system_info.json
  • app_info.json: Version information, build date, and background queue statuses.
  • config.json: Sanitized enterprise-search.yml with defaults.
  • elasticsearch-info.json: Elasticsearch cluster, node, index, and configuration settings.
  • logs/stats.log: Periodic metrics: response codes, timings. Each line is snapshot data for a sliding window of time. Generates one line per process per minute.
  • logs/system.log: Sanitized log of key system events such as web requests, response codes, API methods, background job processing, and more.
  • recent_jobs_info.json: Information about most recent finished jobs for every content source.
  • system_info.json: Operating System and Java Virtual Machine details.

When you submit feedback or issue a support request, attach this bundle to provide our team with:

  • Enterprise Search & Elasticsearch configuration details
  • Partial logs from Enterprise Search and Elasticsearch
  • System information

The richness of the bundle will change depending on what you have set for log_level in your config/enterprise-search.yml.

You can select one of: debug, info, warn, error, fatal, or unknown.

If you are sending the bundle into support, the debug setting will render the most thorough information:

log_level: debug

Look through the logs before sending to ensure that you are comfortable sharing the information.

Java Erroredit

You will need to use the correct Java version if you receive an error such as:

Found java executable in PATH
Java version: 1.7.0_80
Elastic Enterprise Search requires Java version 1.8 or higher, current version is 1.7.0_80

On Linux or MacOS, you can manage your Java environment using something like jEnv.

Ensure you have 1.8 or higher installed; just installing a new Java version often is not enough, ensure it is in your PATH.

Response Alerts & Warningsedit

Successful search API responses return a 200 response but may contain either alerts or warnings.

This page will help you identify and troubleshoot alerts.

For warnings, consult the search API Reference for instructions on how better format your query based on warning contents.

Response Objectedit

The response object is rich.

Errors will appear within the alerts or warnings array of the meta object.

  "meta": {
    "alerts": [], // Indicates issues with the Enterprise Search service.
    "warnings": [], // Indicates issues with query formation.
    "page": {
      "current": integer,
      "total_pages": integer,
      "total_results": integer,
      "size": integer
    "request_id": "9c4c527ba0f57e6bafb1f318167eaa04"
  "results": [

  # ... Documents.


5001: Degraded search resultsedit

It is helpful to know whether a query has timed out, or whether the query returned no results.

A 5001 error indicates that the query could not be completed in full.

Use the 5001 error to initiate a retry of the query, perhaps after assessing whether the given parameters are bloating the query.

If the issue persists, please contact support.

Debugging your search queriesedit

You can debug Enterprise Search queries by simply adding a header to your Search API requests. This allows you to analyze the queries Enterprise Search is sending to Elasticsearch and the responses returned. A common use case is to find the root cause of slow queries.

This is a fast and lightweight alternative to enabling monitoring and logging for your entire deployment.

The X-Enterprise-Search-Debug headeredit

If the X-Enterprise-Search-Debug header is present and set to true in your Search API request, this enables request-level debug logging. The response body now returns all the raw Elasticsearch queries associated with your Enterprise Search request, along with detailed timing data.

Here’s how the request looks using curl:

curl -X POST '<ENTERPRISE_SEARCH_BASE_URL>/api/as/v1/engines/test/search' \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer search-REDACTED' \
  -H 'X-Enterprise-Search-Debug: true' \

Add a unique request IDedit

You can add another header to make the queries easy to track. The Search API automatically generates a unique ID for requests. However, if you add the X-Request-ID header, you can set this ID to an arbitrary unique value of your choice. This helps you find the request and all its associated Elasticsearch requests in Enterprise Search application logs. The following example sets the Request ID to pancakes.

Here is an example curl request with the header X-Enterprise-Search-Debug: true and the X-Request-ID header set to pancakes:

curl -X POST '<ENTERPRISE_SEARCH_BASE_URL>/api/as/v1/engines/test/search' \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer search-REDACTED' \
  -H 'X-Enterprise-Search-Debug: true' \
  -H 'X-Request-ID: pancakes' \
  -d '{"query": "great"}'

Parsing the response bodyedit

A simple way to see how the response has changed is to run the same search API request with and without the X-Enterprise-Search-Debug: true header and the X-Request-ID header. When you add the headers, the request response body will now have additional fields:

  • request_id: The X-Request-ID passed in the header

Under elasticsearch you will find:

  • query: The raw Elasticsearch query appears in this object
  • took: The amount of time Elasticsearch spent processing the raw query, in milliseconds

You can search for pancakes in the Enterprise Search application logs to find all activity associated with this request. An example of a response body with this additional information looks like this:

  "meta": {
    "alerts": [],
    "warnings": [],
    "precision": 2,
    "page": { ...
    "engine": {
      "name": "longevity",
      "type": "default"
    "elasticsearch": {
      "request_header": {
        "index": "enterprise-search-engine-test",
        "preference": "de2f15d014d40b93578d255e6221fd60"
      "request_body": {
        "query": { ...

        // The raw Elasticsearch query appears in this object...

        "sort": [ ...
        "highlight": { ...
        "size": 10,
        "from": 0,
        "timeout": "30000ms",
        "_source": [
      "response": {

        // The amount of time Elasticsearch spent processing the raw query, in milliseconds:
        "took": 17,

        "timed_out": false,
        "_shards": {
          "total": 2,
          "successful": 2,
          "skipped": 0,
          "failed": 0
        "hits": {
          "total": {
            "value": 4,
            "relation": "eq"
          "max_score": null,
          "hits": [
        "status": 200

    // The original X-Request-ID
    "request_id": "pancakes"

Debugging the raw Elasticsearch queriesedit

You can run the raw Elasticsearch query directly against your Elasticsearch instance using the Elasticsearch search API. The Kibana dev console provides a UI where you can make search API requests against Elasticsearch.

You can also use the Elasticsearch search profile API parameter, profile: true, when querying Elasticsearch directly, to see more Elasticsearch performance profiling metrics. Paste the profiled Elasticsearch response into the Kibana Search Profiler UI to visualize it. Add the 'X-Enterprise-Search-Profile:true' header to your request to return detailed profiling information.

The debug information is also written into the Enterprise Search logs. The logs will include all Elasticsearch queries Enterprise Search performed up to and including the final raw search. For example, for App Search, the logs will show all queries to Elasticsearch to retrieve the engine’s saved synonyms and curations.

You will need to be comfortable analyzing raw Elasticsearch queries to debug using these tools. For difficult to diagnose issues, contact Elastic support for assistance.

Profiling your search queriesedit

If you need to dig deeper into your search query performance, you can enable request-level Elasticsearch profiling. Adding the X-Enterprise-Search-Profile:true header lets you profile Enterprise Search search queries for specific requests.

This returns detailed timing information about the execution of individual components in a search request, by leveraging the Elasticsearch Profile API:

"The Profile API gives the user insight into how search requests are executed at a low level so that the user can understand why certain requests are slow, and take steps to improve them."

The profiling information is returned directly in the response body and is also written into the Enterprise Search logs. This is an advanced tool and the output of the response is verbose. You will need to pretty-print the response and be comfortable analyzing Elasticsearch queries.

Enterprise Search profiling is available for search APIs only.

Using the X-Enterprise-Search-Profile headeredit

Use the X-Enterprise-Search-Profile: true header together with the X-Enterprise-Search-Debug: true header to view profiling data and the underlying Elasticsearch request.

Optionally, add the X-Request-ID header to make it easier to find profiling information for the request in application log files.

Here is an example curl request with the header X-Enterprise-Search-Debug: true, the header X-Enterprise-Search-Profile:true, and the X-Request-ID header set to pancakes:

curl -X POST '<ENTERPRISE_SEARCH_BASE_URL>/api/as/v1/engines/test/search' \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer search-REDACTED' \
  -H 'X-Enterprise-Search-Debug: true' \
  -H 'X-Enterprise-Search-Profile: true' \
  -H 'X-Request-ID: pancakes' \
  -d '{"query": "great"}'

Here is what the response might look like. Note this is a truncated example of the meta.profile portion of the response body:

  "meta": {
    "alerts": [],
    "warnings": [],
    "precision": 2,
    "page": {
    "current": 1,
    "total_pages": 1,
    "total_results": 9,
    "size": 10
  "engine": {
    "name": "test",
    "type": "default"
  "profile": {
    "shards": [
        "id": "[pancakes][.enterprise-search-engine-test-1][0]",
        "searches": [
            "query": [
                "type": "MatchAllDocsQuery",
                "description": "*:*",
                "time_in_nanos": 4228,
                "breakdown": {
                  "set_min_competitive_score_count": 0,
                  "match_count": 0,
                  "shallow_advance_count": 0,
                  "set_min_competitive_score": 0,
                  "next_doc": 270,
                  "match": 0,
                  "next_doc_count": 1,
                  "score_count": 1,
                  "compute_max_score_count": 0,
                  "compute_max_score": 0,
                  "advance": 663,
                  "advance_count": 1,
                  "score": 620,
                  "build_scorer_count": 2,
                  "create_weight": 512,
                  "shallow_advance": 0,
                  "create_weight_count": 1,
                  "build_scorer": 2163
           "rewrite_time": 1596,
           "collector": [
              "name": "SimpleFieldCollector",
              "reason": "search_top_hits",
              "time_in_nanos": 15307
          "aggregations": []

Visualize the responseedit

You can visualize the profiling information using the Kibana Search Profiler UI. Search Profiler is automatically enabled in Kibana. Open the main menu, click Dev Tools, and then click Search Profiler to get started. Paste in the full JSON object surrounding the profile section, e.g.:

   "profile": {

Profiling introduces significant overhead to search execution. This is a diagnostic header. It should not be used in production requests by default.

For difficult to diagnose issues, contact Elastic support for assistance.