Chaos Engineering For Elasticsearch

Last Updated: November 2, 2018

Introduction

Gremlin is a simple, safe and secure service for performing Chaos Engineering experiments through a SaaS-based platform. Elasticsearch is a search engine based on Apache Lucene. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. Datadog is a monitoring service for cloud-scale applications, providing monitoring of servers, databases, tools, and services, through a SaaS-based data analytics platform. Datadog provides an integration to monitor Elasticsearch.

Chaos Engineering Hypothesis

For the purposes of this tutorial we will run Chaos Engineering experiments on the Elasticsearch nodes to reproduce an issue referred to as “split brain”. We will then explain how to avoid “split brain” and run an additional Chaos Engineering experiment to ensure it does not occur. The Chaos Engineering experiment we will perform is a Gremlin Shutdown attack on one Elasticsearch node.

Split brain indicates data inconsistencies originating from separate data sets with overlap in scope, either because of servers in a network design, or a failure condition based on servers not communicating and synchronizing their data to each other. This last case is also commonly referred to as a network partition.

split brain

avoiding split brain

Source: Elasticsearch architecture best practices - by Eric Westberg, Elastic

Prerequisites

To complete this tutorial you will need the following:

3 cloud infrastructure hosts running Ubuntu 16.04
A Gremlin account (sign up here)
A Datadog account

You will also need to install the following on each of your 3 cloud infrastructure hosts. This will enable you to run your Chaos Engineering experiments.

Java
Elasticsearch
Docker
Gremlin
Datadog

Overview

This tutorial will walk you through the required steps to run the Elasticsearch Split Brain Chaos Engineering experiment.

Step 1 - Setting up a VPN for your Elasticsearch hosts using Ansible
Step 2 - Installing Java
Step 3 - Install Elasticsearch on each host
Step 4 - Installing Docker on each host
Step 5 - Installing Gremlin in a Docker container on each host
Step 6 - Installing Datadog in a Docker container on each host
Step 7 - Running the Elasticsearch Split Brain Chaos Engineering experiment
Step 8 - Preventing Elasticsearch Split Brain
Step 9 - Additional Chaos Engineering experiments you can run with Gremlin

Step 1 - Setting up a VPN for your Elasticsearch hosts using Ansible

We will use an Ansible Playbook to automatically create /etc/hosts entries on each host that resolves each VPN server's inventory hostname to its VPN IP address.

First you will need to install Ansible on your local machine, you can use homebrew to do this:

bash

1brew install ansible

On your local machine, use git clone to download a copy of the Playbook. We'll clone it to our home directory:

bash

1cd ~

bash

1git clone https://github.com/thisismitch/ansible-tinc

Now change to the newly-downloaded ansible-tinc directory:

bash

1cd ansible-tinc

Before running the Playbook, you must create a hosts file that contains information about the hosts you want to include in your Tinc VPN.

bash

1vim ~/ansible-tinc/hosts

Enter your own vpn configuration in the~/ansible-tinc/hosts file, an example is provided below:

bash

1[vpn]node01 vpn_ip=10.0.0.1 ansible_host=165.227.185.205node02 vpn_ip=10.0.0.2 ansible_host=104.248.1.194node03 vpn_ip=10.0.0.3 ansible_host=104.248.1.100[vpn:vars]ansible_python_interpreter=/usr/bin/python3[removevpn]

Once your hosts file contains all of the servers you want to include in your VPN, save your changes.

At this point, you should test that Ansible can connect to all of the hosts in your inventory file:

bash

1ansible all -m ping

You should see a "SUCCESS" message similar to below:

bash

1node01 | SUCCESS => {\    "changed": false,\    "ping": "pong"}node03 | SUCCESS => {\    "changed": false,\    "ping": "pong"}node02 | SUCCESS => {\    "changed": false,\    "ping": "pong"=}

Before running the Playbook, you may want to review the contents of the /group_vars/all file:

bash

1cat /group_vars/all

You will see the following:

bash

1netname: nyc3physical_ip: "{{ ansible_eth1.ipv4.address }}"vpn_interface: tun0vpn_netmask: 255.255.255.0vpn_subnet_cidr_netmask: 32

Next we will set up the VPN across your hosts by running the Playbook.

From the ansible-tinc directory, run this command to run the Playbook:

bash

1ansible-playbook site.yml

While the Playbook runs, it should provide the output of each task that is executed. If successful, it will appear as below:

bash

1PLAY RECAP ********************************************************************************node01                     : ok=18   changed=15   unreachable=0    failed=0node02                     : ok=18   changed=15   unreachable=0    failed=0node03                     : ok=18   changed=15   unreachable=0    failed=0

All of the hosts in the inventory file should now be able to communicate with each other over the VPN network.

Step 2 - Installing Java

Install Java 8 on all 3 of your Elasticsearch hosts.

Add the Oracle Java PPA to apt:

bash

1sudo add-apt-repository -y ppa:webupd8team/java

Update your apt package database:

bash

1sudo apt-get update

Install the latest stable version of Oracle Java 8 with this command (and accept the license agreement that pops up):

bash

1sudo apt-get -y install oracle-java8-installer

Be sure to repeat this step on all of your Elasticsearch servers.

Now that Java 8 is installed, let's install ElasticSearch.

Step 3 - Install Elasticsearch on the host

Elasticsearch can be installed with a package manager by adding Elastic's package source list. Complete this step on all of your Elasticsearch servers.

Run the following command to import the Elasticsearch public GPG key into apt:

bash

1wget -qO - https://packages.elastic.co/GPG-KEY-elasticsearch | sudo apt-key add -

Create the Elasticsearch source list:

bash

1echo "deb http://packages.elastic.co/elasticsearch/2.x/debian stable main" | sudo tee -a /etc/apt/sources.list.d/elasticsearch-2.x.list

Update your apt package database:

bash

1sudo apt-get update

Install Elasticsearch:

bash

1sudo apt-get -y install elasticsearch

Elasticsearch is now installed but it needs to be configured before you can use it.

Open the Elasticsearch configuration file for editing:

bash

1vim /etc/elasticsearch/elasticsearch.yml

Because our VPN interface is named "tun0" on all of our servers, we will configure all of our servers with the same line:

bash

1network.host: [_tun0_, _local_]

Note the addition of "_local_", this will allow you to use the Elasticsearch HTTP API locally by sending requests to localhost.

Next, set the name of your cluster

bash

1cluster.name: production

Next, we will set the name of each node.

bash

1node.name: ${HOSTNAME}

Next, you will need to configure an initial list of nodes that will be contacted to discover and create a cluster.

bash

1discovery.zen.ping.unicast.hosts: ["10.0.0.1", "10.0.0.2", "10.0.0.3"]

Your servers are now configured to form a basic Elasticsearch cluster.

Save and exit elasticsearch.yml.

Now start Elasticsearch:

bash

1sudo service elasticsearch restart

Then run this command to start Elasticsearch on boot up:

bash

1sudo update-rc.d elasticsearch defaults 95 10

Repeat these steps on all of your Elasticsearch hosts.

To check state from each of your Elasticsearch hosts, run the following command on each host:

bash

1curl -X GET 'http://localhost:9200'

You should see the following:

bash

1{  "name" : "elasticsearch-03",  "cluster_name" : "production",  "cluster_uuid" : "q84ze4j2TDSrYDOfw-EF8g",  "version" : {\    "number" : "2.4.6",\    "build_hash" : "5376dca9f70f3abef96a77f4bb22720ace8240fd",\    "build_timestamp" : "2017-07-18T12:17:44Z",\    "build_snapshot" : false,\    "lucene_version" : "5.5.4"  },  "tagline" : "You Know, for Search"}

To check cluster state from your Elasticsearch hosts, run the following command:

bash

1curl -XGET 'http://localhost:9200/_cluster/state?pretty'

You will see the following:

bash

1{  "cluster_name" : "production",  "version" : 11,  "state_uuid" : "If64YGVST_2AvoxvK_vC8Q",  "master_node" : "6wQnJ1DfQL2T8ePNrXIUsQ",  "blocks" : { },  "nodes" : {\    "6wQnJ1DfQL2T8ePNrXIUsQ" : {\    "name" : "elasticsearch-01",\    "transport_address" : "10.0.0.1:9300",\    "attributes" : { }\    },\    "sBGUifwKTCOK6DtFRAP2bA" : {\    "name" : "elasticsearch-03",\    "transport_address" : "10.0.0.3:9300",\    "attributes" : { }\    },\    "x3WfO4aFSN6da6O7A18ljQ" : {\    "name" : "elasticsearch-02",\    "transport_address" : "10.0.0.2:9300",\    "attributes" : { }\    }  },  "metadata" : {\    "cluster_uuid" : "q84ze4j2TDSrYDOfw-EF8g",\    "templates" : { },\    "indices" : { }  },  "routing_table" : {\    "indices" : { }  },  "routing_nodes" : {\    "unassigned" : [ ],\    "nodes" : {\    "x3WfO4aFSN6da6O7A18ljQ" : [ ],\    "6wQnJ1DfQL2T8ePNrXIUsQ" : [ ],\    "sBGUifwKTCOK6DtFRAP2bA" : [ ]\    }  }}

If you see output that is similar to this, your Elasticsearch cluster is running.

Step 4 - Installing Docker On Each Host

In this step, you’ll install Docker.

Add Docker’s official GPG key:

bash

1curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -

Use the following command to set up the stable repository.

bash

1sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"

Update the apt package index:

bash

1sudo apt-get update

Make sure you are about to install from the Docker repo instead of the default Ubuntu 16.04 repo:

bash

1apt-cache policy docker-ce

Install the latest version of Docker CE:

bash

1sudo apt-get install docker-ce

Docker should now be installed, the daemon started, and the process enabled to start on boot. Check that it is running:

bash

1sudo systemctl status docker

Type q to return to the prompt.

Make sure you are in the Docker usergroup, replace tammy with your username:

bash

1sudo usermod -aG docker tammy

Next we will create an Elasticsearch container.

Step 5 - Installing Gremlin On Each Host

After you have created your Gremlin account (sign up here) you will need to find your Gremlin Daemon credentials. Login to the Gremlin App using your Company name and sign-on credentials. These were emailed to you when you signed up to start using Gremlin.

Navigate to Team Settings and click on your Team.

Store your Gremlin agent credentials as environment variables, for example:

bash

1export GREMLIN_TEAM_ID=3f242793-018a-5ad5-9211-fb958f8dc084

bash

1export GREMLIN_TEAM_SECRET=eac3a31b-4a6f-6778-1bdb813a6fdc

Next run the Gremlin Daemon in a Container.

Use docker run to pull the official Gremlin Docker image and run the Gremlin daemon:

bash

1sudo docker run -d \
2  --net=host \
3  --pid=host \
4  --cap-add=NET_ADMIN \
5  --cap-add=SYS_BOOT \
6  --cap-add=SYS_TIME \
7  --cap-add=KILL \
8  -e GREMLIN_TEAM_ID="${GREMLIN_TEAM_ID}" \
9  -e GREMLIN_TEAM_CERTIFICATE_OR_FILE="${GREMLIN_TEAM_CERTIFICATE_OR_FILE}" \
10  -e GREMLIN_TEAM_PRIVATE_KEY_OR_FILE="${GREMLIN_TEAM_PRIVATE_KEY_OR_FILE}" \
11  -v /var/run/docker.sock:/var/run/docker.sock \
12  -v /var/log/gremlin:/var/log/gremlin \
13  -v /var/lib/gremlin:/var/lib/gremlin \
14  -v /proc/sysrq-trigger:/sysrq \
15  gremlin/gremlin daemon

Use docker ps to see all running Docker containers:

bash

1sudo docker ps

bash

1CONTAINER ID        IMAGE                COMMAND                  CREATED             STATUS              PORTS                    NAMES
2b281e749ac33        gremlin/gremlin      "/entrypoint.sh daem…"   5 seconds ago       Up 4 seconds                                 relaxed_heisenberg

Jump into your Gremlin container with an interactive shell (replace b281e749ac33 with the real ID of your Gremlin container):

bash

1sudo docker exec -it b281e749ac33 /bin/bash

From within the container, check out the available attack types:

bash

1gremlin help attack-container

bash

1attack-container: CONTAINER and TYPE must be specified
2
3Usage: gremlin attack-container CONTAINER TYPE [type-specific-options]
4
5Type "gremlin help attack-container TYPE" for more details:
6
7  blackhole     # An attack which drops all matching network traffic
8  cpu           # An attack which consumes CPU resources
9  io            # An attack which consumes IO resources
10  latency       # An attack which adds latency to all matching network traffic
11  memory        # An attack which consumes memory
12  packet_loss   # An attack which introduces packet loss to all matching network traffic
13  shutdown      # An attack which forces the target to shutdown
14  dns           # An attack which blocks access to DNS servers
15  time_travel   # An attack which changes the system time.
16  disk          # An attack which consumes disk resources
17  process_killer        # An attack which kills the specified process

Step 6 - Installing the Datadog agent in a Docker container

To install Datadog in a Docker container you can use the Datadog Docker easy one-step install.

Run the following command, replacing the item in red with your own API key:

bash

1docker run -d --name dd-agent -v /var/run/docker.sock:/var/run/docker.sock:ro -v /proc/:/host/proc/:ro -v /sys/fs/cgroup/:/host/sys/fs/cgroup:ro -e DD_API_KEY=7cfe87ac24e0ce166be9c96aea1f3f88 datadog/agent:latest

It will take a few minutes for Datadog to spin up the Datadog container, collect metrics on your existing containers and display them in the Datadog App.

View your Docker Containers in Datadog, you should see the following on the host Dashboard:

Step 7 - Running the Elasticsearch Split Brain Chaos Engineering Experiment

We will use the Gremlin CLI attack command to create a shutdown attack.

Now use the Gremlin CLI (gremlin) to run a shutdown attack against the host from a Gremlin container:

bash

1docker run -i \
2  --net=host \
3  --pid=host \
4  --cap-add=NET_ADMIN \
5  --cap-add=SYS_BOOT \
6  --cap-add=SYS_TIME \
7  --cap-add=KILL \
8  -e GREMLIN_TEAM_ID="${GREMLIN_TEAM_ID}" \
9  -e GREMLIN_TEAM_CERTIFICATE_OR_FILE="${GREMLIN_TEAM_CERTIFICATE_OR_FILE}" \
10  -e GREMLIN_TEAM_PRIVATE_KEY_OR_FILE="${GREMLIN_TEAM_PRIVATE_KEY_OR_FILE}" \
11  -v /var/run/docker.sock:/var/run/docker.sock \
12  -v /var/log/gremlin:/var/log/gremlin \
13  -v /var/lib/gremlin:/var/lib/gremlin \
14  -v /proc/sysrq-trigger:/sysrq \
15  gremlin/gremlin attack shutdown

This attack will shutdown the Elasticsearch host where you ran the attack.

This triggers an issue referred to as Elasticsearch Split Brain which is documented below:

To check which Elasticsearch node is currently the master node in your cluster run the following:

bash

1curl -X GET "localhost:9200/_cat/master?v

You should see something similar to the following:

bash

1id                     host     ip       nodeEpkU82qVQ0CoIOHzZjaqBg 10.0.0.1 10.0.0.1 elasticsearch-01

View the contents of the Elasticsearch Production Log on one of your running Elasticsearch hosts:

bash

1less /var/log/elasticsearch/production.log

You may notice issues such as other nodes in the cluster stopping the Elasticsearch service when you run the Gremlin Shutdown attack, for example:

bash

1[2018-11-02 00:20:47,046][INFO ][cluster.service          ] l[elasticsearch-02] added {{elasticsearch-03}{pPgjIxYETOWMXWwZe3hnSQ}{10.0.0.3}{10.0.0.3:9300},}, reason: zen-disco-receive(from master [{elasticsearch-01}{EpkU82qVQ0CoIOHzZjaqBg}{10.0.0.1}{10.0.0.1:9300}])

bash

1[2018-11-02 00:21:35,041][INFO ][node                     ] [elasticsearch-01] stopping …

bash

1[2018-11-02 00:21:35,048][INFO ][discovery.zen            ] [elasticsearch-02] master_left [{elasticsearch-01}{EpkU82qVQ0CoIOHzZjaqBg}{10.0.0.1}{10.0.0.1:9300}], reason [shut_down]

bash

1[2018-11-02 00:21:35,050][WARN ][discovery.zen            ] [elasticsearch-02] master left (reason = shut_down), current nodes: {{elasticsearch-02}{YvAyPlK4Q9SOZCtvk-aP6Q}{10.0.0.2}{10.0.0.2:9300},{elasticsearch-03}{pPgjIxYETOWMXWwZe3hnSQ}{10.0.0.3}{10.0.0.3:9300},}

bash

1[2018-11-02 00:21:35,052][INFO ][cluster.service          ] [elasticsearch-02] removed {{elasticsearch-01}{EpkU82qVQ0CoIOHzZjaqBg}{10.0.0.1}{10.0.0.1:9300},}, reason: zen-disco-master_failed ({elasticsearch-01}{EpkU82qVQ0CoIOHzZjaqBg}{10.0.0.1}{10.0.0.1:9300})

bash

1[2018-11-02 00:21:36,557][WARN ][transport.netty          ] [elasticsearch-02] exception caught on transport layer [[id: 0xfe487d7b]], closing connection

bash

1java.net.SocketException: Network is unreachable

To prevent Elasticsearch Split Brain from occuring we will need to take additional steps described in Step 8.

Step 8 - Preventing Elasticsearch Split Brain

There are two common types of Elasticsearch nodes: master and data. Master nodes perform cluster-wide actions, such as managing indices and determining which data nodes should store particular data shards. Data nodes hold shards of your indexed documents, and handle CRUD, search, and aggregation operations. As a general rule, data nodes consume a significant amount of CPU, memory, and I/O.

By default, every Elasticsearch node is configured to be a "master-eligible" data node, which means they store data (and perform resource-intensive operations) and have the potential to be elected as a master node. An Elasticsearch cluster should be configured with dedicated master nodes so that the master node's stability can't be compromised by intensive data node work.

Ensure you have a cluster with 3 Elasticsearch nodes

First, restart the Elasticsearch master node that you shutdown in the previous step.

You will need 3 master nodes to run this Chaos Engineering experiment.

How to Configure Dedicated Master Nodes

Before configuring dedicated master nodes, ensure that your cluster will have at least 3 master-eligible nodes. This is important to avoid a split-brain situation, which can cause inconsistencies in your data in the event of a network failure.

To configure a dedicated master node, edit the node's Elasticsearch configuration:

bash

1sudo vi /etc/elasticsearch/elasticsearch.yml

Add the following lines:

bash

1# Set the node's role  node.master: true  node.data: false

The first line, node.master: true, specifies that the node is master-eligible and is actually the default setting. The second line, node.data: false, restricts the node from becoming a data node.

Save and exit.

Now restart the Elasticsearch node to put the change into effect:

bash

1sudo service elasticsearch restart

Be sure to repeat this step on your other dedicated master nodes.

You can query the cluster to see which nodes are configured as dedicated master nodes with this command:

bash

1curl -XGET 'http://localhost:9200/_cluster/state?pretty'.

Configure Minimum Master Nodes

When running an Elasticsearch cluster, it is important to set the minimum number of master-eligible nodes that need to be running for the cluster to function normally, which is often referred to as quorum. This is to ensure data consistency in the event that one or more nodes lose connectivity to the rest of the cluster, preventing what is known as a "split-brain" situation. For example, for a 3-node cluster, the quorum is 2.

The minimum master nodes setting can be set dynamically, through the Elasticsearch HTTP API. Run this command on any node:

bash

1curl -XPUT localhost:9200/_cluster/settings?pretty -d '{"persistent" : {"discovery.zen.minimum_master_nodes" : 2}}'You should see the following result: {  "acknowledged" : true,  "persistent" : {\    "discovery" : {\    "zen" : {\    "minimum_master_nodes" : "2"\    }\    }  },  "transient" : { }}

This setting can also be set as in /etc/elasticsearch.yml as:

bash

1discovery.zen.minimum_master_nodes: 2

If you want to check this setting later, you can run this command:

bash

1curl -XGET localhost:9200/_cluster/settings?pretty

Running the Elasticsearch Split Brain Chaos Engineering Experiment After Config Changes

We will use the Gremlin CLI attack command to create a CPU attack.

Now use the Gremlin CLI (gremlin) to run a CPU attack from within a Gremlin container:

bash

1sudo docker run -i \
2  --net=host \
3  --pid=host \
4  --cap-add=NET_ADMIN \
5  --cap-add=SYS_BOOT \
6  --cap-add=SYS_TIME \
7  --cap-add=KILL \
8  -e GREMLIN_TEAM_ID="${GREMLIN_TEAM_ID}" \
9  -e GREMLIN_TEAM_CERTIFICATE_OR_FILE="${GREMLIN_TEAM_CERTIFICATE_OR_FILE}" \
10  -e GREMLIN_TEAM_PRIVATE_KEY_OR_FILE="${GREMLIN_TEAM_PRIVATE_KEY_OR_FILE}" \
11  -v /var/run/docker.sock:/var/run/docker.sock \
12  -v /var/log/gremlin:/var/log/gremlin \
13  -v /var/lib/gremlin:/var/lib/gremlin \
14  -v /proc/sysrq-trigger:/sysrq \
15  gremlin/gremlin attack shutdown

This attack will shutdown the Elasticsearch host.

To check which Elasticsearch host is currently the master node in your cluster run the following on any host:

bash

1curl -X GET "localhost:9200/_cat/master?v

You should see something similar to the following:

bash

1id                     host     ip       nodeMHOVfw_VSL2apsJ_LKiNrg 10.0.0.3 10.0.0.3 elasticsearch-03

Now that you have resolved the Split Brain issue, when you shutdown a master you will find a message similar to the following in /var/log/elasticsearch/production.log:

bash

1[elasticsearch-02] not enough master nodes, current nodes: {{elasticsearch-02}{RE_2u5HQR3mMLzSFQuT4oQ}{10.0.0.2}{10.0.0.2:9300}{data=false, master=true},}

Step 9 - Additional Chaos Engineering experiments to run on Elasticsearch

There are many Chaos Engineering experiments you could possibly run on your Elasticsearch infrastructure:

Time Travel Gremlin - will changing the clock time of the host impact how Elasticsearch processes data?
Latency & Packet Loss Gremlins - will they impact the ability to use the Elasticsearch API endpoints?
Disk Gremlin - will filling up the disk crash the host?

We encourage you to run these Chaos Engineering experiments and share your findings! To get access to Gremlin, sign up here.

Conclusion

This tutorial has explored how to install Elasticsearch and Gremlin in Docker containers for your Chaos Engineering experiments. We then ran a shutdown Chaos Engineering experiment on the Elasticsearch container using the Gremlin Shutdown attack.

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Gremlin empowers you to proactively root out failure before it causes downtime. See how you can harness chaos to build resilient systems by requesting a demo of Gremlin.

Get started

Introduction

Chaos Engineering Hypothesis

Prerequisites

Overview

Step 1 - Setting up a VPN for your Elasticsearch hosts using Ansible

Step 2 - Installing Java

Step 3 - Install Elasticsearch on the host

Step 4 - Installing Docker On Each Host

Step 5 - Installing Gremlin On Each Host

Step 6 - Installing the Datadog agent in a Docker container

Step 7 - Running the Elasticsearch Split Brain Chaos Engineering Experiment

Step 8 - Preventing Elasticsearch Split Brain

Step 9 - Additional Chaos Engineering experiments to run on Elasticsearch

Conclusion

Related

Avoid downtime. Use Gremlin to turn failure into resilience.