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Error Logs

Error Log: index_not_found_exception – The missing index

By November 19, 2025No Comments

Error Log: This is a very clear and common error, seen in both client logs and API responses.

org.opensearch.index.IndexNotFoundException: no such index [my-missing-index]

Or in a JSON response:
JSON

{
  "error" : {
    "root_cause" : [
      {
        "type" : "index_not_found_exception",
        "reason" : "no such index [my-missing-index]",
        "resource.type" : "index_or_alias",
        "resource.id" : "my-missing-index",
        "index_uuid" : "_na_",
        "index" : "my-missing-index"
      }
    ],
    ...
  },
  "status" : 404
}

Why… is this happening? This error is straightforward: OpenSearch cannot find an index or alias with the name you provided.

The most common reasons are:

  1. A Simple Typo: You misspelled the index name in your query (e.g., my-index instead of my_index).
  2. Incorrect Date: You are searching a time-series index (e.g., logs-2025-11-04) but no data has been indexed for that specific day yet, so the index doesn’t exist.
  3. Alias Problem: You are querying an alias, but the alias either doesn’t exist or it doesn’t point to any indices (e.g., it’s an “empty” alias).
  4. Index Was Deleted: A cleanup script or automated ISM (Index State Management) policy deleted the index you are trying to query.

Best Practice:

  1. Check Your Names: The first step is always to double-check your spelling. Use GET /_cat/indices?v or GET /_cat/aliases?v to list all existing indices and aliases and verify the name.
  2. Enable Auto-Create Index: If you are sending data to time-based indices, you can enable automatic index creation. In opensearch.yml, set action.auto_create_index: "logstash-*,my-pattern-*,...". (Note: Be careful with this; a typo could auto-create many unwanted indices).
  3. Use Index Templates: A better practice for time-series data is to use an index template and an index alias. Have all your clients write to a single alias (e.g., my-logs-write). An ISM policy can then automatically create a new index (my-logs-000001, my-logs-000002) and roll the alias over when needed.
  4. Query Gracefully: If it’s acceptable for an index to sometimes not exist (e.g., searching the last 3 days), add ignore_unavailable=true as a URL parameter to your search request. This tells OpenSearch to simply ignore any specified indices that are missing instead of throwing an error.

What else can I do? Not sure if you should be using aliases, index templates, or ISM policies? This is a core part of managing OpenSearch. Ask the community for examples based on your data. For a deeper dive into data architecture, reach out to the vibrant OpenSearch community for help and support on the OpenSearch Slack Channel. 

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