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Elasticsearchquery~5 mins

Application performance monitoring in Elasticsearch

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Introduction

Application performance monitoring helps you see how well your app works. It shows if parts are slow or have errors.

You want to find why your website is slow for users.
You need to check if a new update caused errors.
You want to watch your app's health during busy times.
You want to get alerts when something breaks.
You want to understand user experience by tracking app speed.
Syntax
Elasticsearch
PUT /apm-7.17.0
{
  "settings": {
    "index": {
      "number_of_shards": 1
    }
  },
  "mappings": {
    "properties": {
      "transaction.duration.us": { "type": "long" },
      "transaction.name": { "type": "keyword" },
      "service.name": { "type": "keyword" },
      "timestamp": { "type": "date" }
    }
  }
}

This example creates an index for storing APM data in Elasticsearch.

Fields like transaction.duration.us measure how long a request takes in microseconds.

Examples
Searches the APM index for data from the service named "my-app".
Elasticsearch
GET /apm-7.17.0/_search
{
  "query": {
    "match": { "service.name": "my-app" }
  }
}
Calculates the average transaction duration in microseconds.
Elasticsearch
GET /apm-7.17.0/_search
{
  "aggs": {
    "avg_duration": {
      "avg": { "field": "transaction.duration.us" }
    }
  }
}
Adds a new transaction record to the APM index.
Elasticsearch
POST /apm-7.17.0/_doc
{
  "service.name": "my-app",
  "transaction.name": "GET /home",
  "transaction.duration.us": 150000,
  "timestamp": "2024-06-01T12:00:00Z"
}
Sample Program

This query finds the average response time for the service named "my-app" from the APM data.

Elasticsearch
POST /apm-7.17.0/_search
{
  "size": 0,
  "aggs": {
    "avg_response_time": {
      "avg": {
        "field": "transaction.duration.us"
      }
    }
  },
  "query": {
    "term": {
      "service.name": "my-app"
    }
  }
}
OutputSuccess
Important Notes

APM data is often stored in Elasticsearch indexes with specific mappings for performance metrics.

Use Kibana or other tools to visualize APM data easily.

Keep your APM data size manageable by setting retention policies.

Summary

Application performance monitoring helps track app speed and errors.

Elasticsearch stores and queries APM data using indexes and aggregations.

Average response time is a key metric to watch for app health.

Practice

(1/5)
1. What is the main purpose of Application Performance Monitoring (APM) in Elasticsearch?
easy
A. To track application speed and detect errors
B. To store user login credentials securely
C. To manage Elasticsearch cluster nodes
D. To backup Elasticsearch indexes automatically

Solution

  1. Step 1: Understand APM's role

    APM is designed to monitor how fast an application runs and to find any errors it produces.
  2. Step 2: Match purpose with options

    Only To track application speed and detect errors describes tracking speed and errors, which fits APM's main goal.
  3. Final Answer:

    To track application speed and detect errors -> Option A
  4. Quick Check:

    APM purpose = Track speed and errors [OK]
Hint: APM = watch app speed and errors [OK]
Common Mistakes:
  • Confusing APM with security or backup tools
  • Thinking APM manages cluster nodes
  • Assuming APM stores user credentials
2. Which Elasticsearch query syntax correctly calculates the average response time from APM data?
easy
A. POST /apm-*/_update_by_query {"script": {"source": "ctx._source.duration = 0"}}
B. GET /apm-*/_search {"query": {"match_all": {}}, "size":10}
C. GET /apm-*/_search {"size":0, "aggs": {"avg_response_time": {"avg": {"field": "transaction.duration.us"}}}}
D. GET /apm-*/_search {"aggs": {"max_response_time": {"max": {"field": "transaction.duration.us"}}}}

Solution

  1. Step 1: Identify aggregation for average

    The query uses "avg" aggregation on the field "transaction.duration.us" which stores response times in microseconds.
  2. Step 2: Confirm query structure

    Size is 0 to avoid returning documents, focusing only on aggregation results, which is correct for average calculation.
  3. Final Answer:

    GET /apm-*/_search {"size":0, "aggs": {"avg_response_time": {"avg": {"field": "transaction.duration.us"}}}} -> Option C
  4. Quick Check:

    Average aggregation query = GET /apm-*/_search {"size":0, "aggs": {"avg_response_time": {"avg": {"field": "transaction.duration.us"}}}} [OK]
Hint: Average uses "avg" aggregation with size 0 [OK]
Common Mistakes:
  • Using match_all without aggregation
  • Using update_by_query instead of search
  • Using max aggregation instead of avg
3. Given this Elasticsearch aggregation query on APM data, what is the expected output?
GET /apm-*/_search
{
  "size": 0,
  "aggs": {
    "avg_response_time": {
      "avg": { "field": "transaction.duration.us" }
    }
  }
}
medium
A. {"aggregations":{"max_response_time":{"value":500000}}}
B. {"hits":{"total":100}}
C. {"error":"Field not found"}
D. {"aggregations":{"avg_response_time":{"value":250000}}}

Solution

  1. Step 1: Understand aggregation type

    The query requests the average of the field "transaction.duration.us" which holds response times in microseconds.
  2. Step 2: Match output to aggregation

    The output shows an aggregation named "avg_response_time" with a numeric value representing the average, matching {"aggregations":{"avg_response_time":{"value":250000}}}.
  3. Final Answer:

    {"aggregations":{"avg_response_time":{"value":250000}}} -> Option D
  4. Quick Check:

    Average aggregation output = {"aggregations":{"avg_response_time":{"value":250000}}} [OK]
Hint: Aggregation output shows "aggregations" with average value [OK]
Common Mistakes:
  • Confusing hits total with aggregation result
  • Expecting max instead of avg
  • Assuming error without checking field existence
4. You run this Elasticsearch query to get average response time but get an error: Fielddata is disabled on text fields by default. What is the likely cause?
medium
A. Trying to aggregate on a text field instead of a numeric field
B. Using the wrong index pattern in the query
C. Missing authentication credentials
D. Query syntax error in aggregation block

Solution

  1. Step 1: Analyze error message

    The error says fielddata is disabled on text fields, which means aggregation was attempted on a text field.
  2. Step 2: Understand aggregation requirements

    Aggregations like average require numeric fields, so using a text field causes this error.
  3. Final Answer:

    Trying to aggregate on a text field instead of a numeric field -> Option A
  4. Quick Check:

    Fielddata error = Aggregation on text field [OK]
Hint: Average needs numeric field, not text [OK]
Common Mistakes:
  • Blaming index pattern or auth for this error
  • Assuming syntax error without checking field type
  • Ignoring field data type requirements
5. You want to monitor the average response time for your app but only for transactions with errors. Which Elasticsearch query snippet correctly filters and calculates this?
hard
A. { "size": 0, "query": { "term": { "error.id": "" } }, "aggs": { "avg_response_time": { "avg": { "field": "transaction.duration.us" } } } }
B. { "size": 0, "query": { "exists": { "field": "error.id" } }, "aggs": { "avg_response_time": { "avg": { "field": "transaction.duration.us" } } } }
C. { "size": 0, "query": { "match_all": {} }, "aggs": { "avg_response_time": { "avg": { "field": "transaction.duration.us" } } } }
D. { "size": 0, "query": { "term": { "transaction.status": "success" } }, "aggs": { "avg_response_time": { "avg": { "field": "transaction.duration.us" } } } }

Solution

  1. Step 1: Identify filter for transactions with errors

    Transactions with errors have a non-empty "error.id" field, so we use "exists" query on "error.id".
  2. Step 2: Confirm aggregation on filtered data

    The aggregation calculates average response time only on filtered documents, which is correct.
  3. Final Answer:

    { "size": 0, "query": { "exists": { "field": "error.id" } }, "aggs": { "avg_response_time": { "avg": { "field": "transaction.duration.us" } } } } -> Option B
  4. Quick Check:

    Filter errors with exists + avg aggregation = { "size": 0, "query": { "exists": { "field": "error.id" } }, "aggs": { "avg_response_time": { "avg": { "field": "transaction.duration.us" } } } } [OK]
Hint: Use exists query to filter error transactions [OK]
Common Mistakes:
  • Using empty term query instead of exists
  • Calculating average without filtering errors
  • Filtering for success instead of errors