---
id: 10822c63-5508-4a0d-9f23-4fe3c27c9dc5
---

# High CPU usage on MongoDB host
---

This incident type involves the detection of high CPU usage on a MongoDB host, often triggered by an alert monitor. The incident may be indicated by anomalous CPU usage values that are more than two standard deviations above predicted values during a specific time period, such as the last 15 minutes. The incident can cause performance issues and may require investigation to identify the root cause and resolve the problem.

### Parameters
```shell
# Environment Variables

export HOSTNAME="PLACEHOLDER"

export MONGODB_PORT="PLACEHOLDER"

export PASSWORD="PLACEHOLDER"

export USERNAME="PLACEHOLDER"

export DATABASE_NAME="PLACEHOLDER"

```

## Debug

### Check CPU usage on the MongoDB host
```shell
top
```

### Check MongoDB logs for any errors
```shell
tail -n 100 /var/log/mongodb/mongod.log
```

### Check MongoDB processes and memory usage
```shell
ps aux | grep mongod
```

### Check network connections to MongoDB
```shell
netstat -an | grep ${MONGODB_PORT}
```

### Check MongoDB disk usage and available space
```shell
df -h /var/lib/mongodb
```

### Check MongoDB configuration file for any issues
```shell
cat /etc/mongod.conf
```

### Check MongoDB version and compatibility with other components
```shell
mongod --version
```

### Check MongoDB performance metrics
```shell
mongostat --ssl --host ${HOSTNAME} --port ${PORT} --username ${USERNAME} --password ${PASSWORD}
```

### Check MongoDB database status and status of all databases
```shell
mongo --eval "db.runCommand({serverStatus: 1})" && mongo --eval "db.runCommand({listDatabases: 1})"
```

## Repair
### Optimize database queries and indexes to reduce the load on the database and improve CPU usage.
```shell
#!/bin/bash

# Set database connection parameters

DB_HOST=${HOSTNAME}

DB_PORT=${MONGODB_PORT}

DB_NAME=${DATABASE_NAME}

DB_USER=${USERNAME}

DB_PASS=${PASSWORD}

# Connect to the database

mongo --host $DB_HOST --port $DB_PORT -u $DB_USER -p $DB_PASS $DB_NAME

# Enable profiling to identify slow queries

db.setProfilingLevel(2, {slowms: 100});

# Analyze query performance

db.system.profile.find({millis: {$gt: 100}}).sort({ts: -1}).limit(10);

# Create indexes for frequently queried fields

db.collection.createIndex({field1: 1, field2: 1});

# Monitor index usage to identify any issues

db.collection.find().explain("executionStats");

# Optimize queries by removing unnecessary queries and improving existing queries

db.collection.aggregate([

  {$match: {field1: "value1"}},

  {$group: {_id: "$field2", count: {$sum: 1}}},

  {$sort: {count: -1}},

  {$limit: 10}

]);

# Verify improved query performance

db.collection.find({field1: "value1", field2: "value2"}).explain("executionStats");

# Disable profiling

db.setProfilingLevel(0);

```

This incident type involves the detection of high CPU usage on a MongoDB host, often triggered by an alert monitor. The incident may be indicated by anomalous CPU usage values that are more than two standard deviations above predicted values during a specific time period, such as the last 15 minutes. The incident can cause performance issues and may require investigation to identify the root cause and resolve the problem.


This incident type refers to a situation where the Tomcat server's JDBC connection pool usage surpasses its configured limits. This can lead to a shortage of available connections for incoming requests, resulting in slow response times or even server crashes. It is important to monitor and manage the JDBC connection pool usage to prevent such incidents from occurring.


Tomcat High JDBC Connection Pool Usage Incident.

This incident type refers to an increase in the number of errors per second on a Tomcat server, which could indicate an issue with the server itself, the host, a deployed application, or an application servlet. This could include errors generated when the Tomcat server runs out of memory, can't find a requested file or servlet, or is unable to serve a JSP due to syntax errors in the servlet codebase. This incident type requires immediate attention to diagnose and address the underlying issue.


Increase of the errors/second rate for Tomcat server

This incident type indicates that there is a high latency issue in the execution of a Spark job. Spark is a distributed computing framework that is used for processing large datasets. High latency in this context means that the time taken to execute the Spark job is significantly longer than expected or normal. This can result in delays in processing data and can impact the performance of the application or system that is utilizing Spark.


High Latency Incident for Spark Job Execution.

This incident type involves an alert triggered when read latency is higher than usual for a MongoDB host. The alert is triggered when at least 100% of the average read latency values have been more than 2 deviations above the predicted values during the last 15 minutes. The incident requires monitoring and investigation to identify the root cause of the increased read latency and take appropriate actions to resolve it.


Read latency higher than average for MongoDB host.

This incident type refers to a situation where the write latency for a MongoDB database is higher than the average. This might cause delays in write operations and can negatively impact the performance of the system. The incident might be triggered by an alert that indicates that the write latency has exceeded a certain threshold, and it requires immediate attention from a software engineer to identify and resolve the underlying issue. The incident can be resolved by identifying and fixing the root cause of the latency issue, and ensuring that the system is functioning within acceptable performance parameters.


MongoDB Write Latency Higher Than Average

```shell
# Environment Variables

export HOSTNAME="PLACEHOLDER"

export MONGODB_PORT="PLACEHOLDER"

export PASSWORD="PLACEHOLDER"

export USERNAME="PLACEHOLDER"

export DATABASE_NAME="PLACEHOLDER"

```


### Check CPU usage on the MongoDB host

```shell
top
```

### Check MongoDB logs for any errors

```shell
tail -n 100 /var/log/mongodb/mongod.log
```

### Check MongoDB processes and memory usage

```shell
ps aux | grep mongod
```

### Check network connections to MongoDB

```shell
netstat -an | grep ${MONGODB_PORT}
```

### Check MongoDB disk usage and available space

```shell
df -h /var/lib/mongodb
```

### Check MongoDB configuration file for any issues

```shell
cat /etc/mongod.conf
```

### Check MongoDB version and compatibility with other components

```shell
mongod --version
```

### Check MongoDB performance metrics

```shell
mongostat --ssl --host ${HOSTNAME} --port ${PORT} --username ${USERNAME} --password ${PASSWORD}
```

### Check MongoDB database status and status of all databases

```shell
mongo --eval "db.runCommand({serverStatus: 1})" && mongo --eval "db.runCommand({listDatabases: 1})"
```


### Optimize database queries and indexes to reduce the load on the database and improve CPU usage.

```shell
#!/bin/bash

# Set database connection parameters

DB_HOST=${HOSTNAME}

DB_PORT=${MONGODB_PORT}

DB_NAME=${DATABASE_NAME}

DB_USER=${USERNAME}

DB_PASS=${PASSWORD}

# Connect to the database

mongo --host $DB_HOST --port $DB_PORT -u $DB_USER -p $DB_PASS $DB_NAME

# Enable profiling to identify slow queries

db.setProfilingLevel(2, {slowms: 100});

# Analyze query performance

db.system.profile.find({millis: {$gt: 100}}).sort({ts: -1}).limit(10);

# Create indexes for frequently queried fields

db.collection.createIndex({field1: 1, field2: 1});

# Monitor index usage to identify any issues

db.collection.find().explain("executionStats");

# Optimize queries by removing unnecessary queries and improving existing queries

db.collection.aggregate([

  {$match: {field1: "value1"}},

  {$group: {_id: "$field2", count: {$sum: 1}}},

  {$sort: {count: -1}},

  {$limit: 10}

]);

# Verify improved query performance

db.collection.find({field1: "value1", field2: "value2"}).explain("executionStats");

# Disable profiling

db.setProfilingLevel(0);

```


High CPU usage on MongoDB host

Overview

Parameters

Debug

Check CPU usage on the MongoDB host

Check MongoDB logs for any errors

Check MongoDB processes and memory usage

Check network connections to MongoDB

Check MongoDB disk usage and available space

Check MongoDB configuration file for any issues

Check MongoDB version and compatibility with other components

Check MongoDB performance metrics

Check MongoDB database status and status of all databases

Repair

Optimize database queries and indexes to reduce the load on the database and improve CPU usage.

Learn more

Related Runbooks

Tomcat High JDBC Connection Pool Usage Incident.

Increase of the errors/second rate for Tomcat server

High Latency Incident for Spark Job Execution.

Read latency higher than average for MongoDB host.

Support