---
id: a5af4f3b-5c01-427a-829e-2dca0f7abb82
---

# High memory consumption in Redis
---

This incident type relates to Redis, a popular in-memory data structure store that is widely used in software development. The incident occurs when there is high memory consumption in Redis, which can lead to performance issues and potentially cause the system to crash. This incident type is critical as it can impact the functionality of the system and requires immediate attention to resolve.

### Parameters
```shell
# Environment Variables

export MAXIMUM_MEMORY_IN_GB="PLACEHOLDER"

export PATH_TO_REDIS_CONFIG_FILE="PLACEHOLDER"

export MAXIMUM_MEMORY_SIZE_IN_BYTES="PLACEHOLDER"
```

## Debug

### Check if Redis is running
```shell
systemctl status redis
```

### Check Redis version
```shell
redis-cli --version
```

### Check Redis configuration file
```shell
cat /etc/redis/redis.conf
```

### Check Redis memory usage
```shell
redis-cli info memory | grep used_memory_human
```

### Check Redis memory limit
```shell
redis-cli info memory | grep maxmemory_human
```

### Check Redis memory usage by database
```shell
redis-cli info memory | grep db
```

### Check Redis keyspace statistics
```shell
redis-cli info keyspace
```

### Check Redis slow log
```shell
redis-cli slowlog get
```

### Check system memory usage
```shell
free -m
```

### Check system swap usage
```shell
swapon -s
```

### Check system disk usage
```shell
df -h
```

### Check system logs for any related errors
```shell
journalctl -u redis
```

## Repair

### Increase the memory available to Redis by modifying the Redis configuration file.
```shell


#!/bin/bash



# Set the path to the Redis configuration file

REDIS_CONFIG_FILE=${PATH_TO_REDIS_CONFIG_FILE}



# Set the maximum memory available for Redis (in gigabytes)

REDIS_MAX_MEMORY=${MAXIMUM_MEMORY_IN_GB}



# Update the maxmemory setting in the Redis configuration file

sed -i "s/$maxmemory\s*$[0-9]*[mMgG]\?/\1${REDIS_MAX_MEMORY}g/" $REDIS_CONFIG_FILE



# Restart the Redis service

systemctl restart redis.service


```

### Use Redis' built-in eviction policies to automatically remove least recently used keys when memory consumption gets too high.
```shell


#!/bin/bash



# Define Redis eviction policy settings

MAX_MEMORY=${MAXIMUM_MEMORY_SIZE_IN_BYTES}

MAX_MEMORY_POLICY=allkeys-lru



# Update Redis configuration file with new settings

echo "maxmemory $MAX_MEMORY" >> /etc/redis/redis.conf

echo "maxmemory-policy $MAX_MEMORY_POLICY" >> /etc/redis/redis.conf



# Restart Redis service to apply changes

systemctl restart redis.service


```


This incident type relates to Redis, a popular in-memory data structure store that is widely used in software development. The incident occurs when there is high memory consumption in Redis, which can lead to performance issues and potentially cause the system to crash. This incident type is critical as it can impact the functionality of the system and requires immediate attention to resolve.


Tomcat JVM OutOfMemory incident occurs when the Java Virtual Machine (JVM) running the Apache Tomcat server runs out of memory, which causes the server to crash or become unresponsive. This type of incident can happen due to a variety of reasons such as incorrect configuration settings, memory leaks, or insufficient memory allocation. When this incident occurs, it can impact the availability and performance of the web application running on the Tomcat server.


Tomcat JVM OutOfMemory Incident

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 the situation where the Tomcat server is utilizing more memory than it should, causing system instability and performance issues. This can happen due to a variety of factors such as memory leaks, improper configuration, or application code issues. It is important to address this incident promptly to prevent system failures and ensure optimal application performance.


Excessive memory usage by Tomcat.

Apache Spark Out of Memory Error is a type of incident that occurs when the Apache Spark application running on a system is unable to allocate enough memory to perform its tasks. This can happen when the system's memory is insufficient or when there is a memory leak in the application's code. When this incident occurs, the application may crash, become unresponsive, or produce incorrect results. It is important to diagnose and resolve this issue as soon as possible to ensure the smooth functioning of the application.


Apache Spark Out of Memory Error incident.

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.

### Check if Redis is running

```shell
systemctl status redis
```

### Check Redis version

```shell
redis-cli --version
```

### Check Redis configuration file

```shell
cat /etc/redis/redis.conf
```

### Check Redis memory usage

```shell
redis-cli info memory | grep used_memory_human
```

### Check Redis memory limit

```shell
redis-cli info memory | grep maxmemory_human
```

### Check Redis memory usage by database

```shell
redis-cli info memory | grep db
```

### Check Redis keyspace statistics

```shell
redis-cli info keyspace
```

### Check Redis slow log

```shell
redis-cli slowlog get
```

### Check system memory usage

```shell
free -m
```

### Check system swap usage

```shell
swapon -s
```

### Check system disk usage

```shell
df -h
```

### Check system logs for any related errors

```shell
journalctl -u redis
```


### Increase the memory available to Redis by modifying the Redis configuration file.

```shell


#!/bin/bash



# Set the path to the Redis configuration file

REDIS_CONFIG_FILE=${PATH_TO_REDIS_CONFIG_FILE}



# Set the maximum memory available for Redis (in gigabytes)

REDIS_MAX_MEMORY=${MAXIMUM_MEMORY_IN_GB}



# Update the maxmemory setting in the Redis configuration file

sed -i "s/$maxmemory\s*$[0-9]*[mMgG]\?/\1${REDIS_MAX_MEMORY}g/" $REDIS_CONFIG_FILE



# Restart the Redis service

systemctl restart redis.service


```

### Use Redis' built-in eviction policies to automatically remove least recently used keys when memory consumption gets too high.

```shell


#!/bin/bash



# Define Redis eviction policy settings

MAX_MEMORY=${MAXIMUM_MEMORY_SIZE_IN_BYTES}

MAX_MEMORY_POLICY=allkeys-lru



# Update Redis configuration file with new settings

echo "maxmemory $MAX_MEMORY" >> /etc/redis/redis.conf

echo "maxmemory-policy $MAX_MEMORY_POLICY" >> /etc/redis/redis.conf



# Restart Redis service to apply changes

systemctl restart redis.service


```


```shell
# Environment Variables

export MAXIMUM_MEMORY_IN_GB="PLACEHOLDER"

export PATH_TO_REDIS_CONFIG_FILE="PLACEHOLDER"

export MAXIMUM_MEMORY_SIZE_IN_BYTES="PLACEHOLDER"
```


High memory consumption in Redis

Overview

Debug

Check if Redis is running

Check Redis version

Check Redis configuration file

Check Redis memory usage

Check Redis memory limit

Check Redis memory usage by database

Check Redis keyspace statistics

Check Redis slow log

Check system memory usage

Check system swap usage

Check system disk usage

Repair

Increase the memory available to Redis by modifying the Redis configuration file.

Use Redis' built-in eviction policies to automatically remove least recently used keys when memory consumption gets too high.

Parameters

Learn more

Related Runbooks

Tomcat JVM OutOfMemory Incident

Tomcat High JDBC Connection Pool Usage Incident.

Excessive memory usage by Tomcat.

Apache Spark Out of Memory Error incident.

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