Adventures in Aerospike

Screenshot2023-06-21at1104AM 1687369654810
Theodore -
Aerospike Student
June 9, 2023|6 min read
Art Anderson
Developer Advocate
June 9, 2023|6 min read

Aerospike had the pleasure of hosting Theodore in a short internship for a school project exploring how companies work. He spent some time tinkering with the Aerospike database and documented his journey, which he shared with us. We in turn would like to share the work of this promising student, with his permission of course, with you. As this was Theodore's first time working with this technology stack, we've added a few [Editors notes] to help with some of the commands. So, without further ado, here's Theodore's report:

How to create an Aerospike Database

This document was written during my 1 week internship at Aerospike and has all the steps I went through during that to create a functional database and a data visualization program in python. This project took 3 days in total. All the official documentation for Aerolab can be found here and the resources for API programming here.


  1. Go to

  2. Needs Windows 10 (build 19041 or higher)or Windows 11

  3. Open PowerShell as administrator (right click and “run as administrator”)

  4. Run:

wsl --install

5. Restart your PC

6. Wait for Ubuntu to install

7. Enter a new username

8. Enter a new password

Install Docker

1. To update to the latest version:

sudo apt update && sudo apt upgrade

2. Install the necessary packages to allow apt to use repositories over HTTPS:

sudo apt install apt-transport-https ca-certificates
curl software-properties-common

3. Add the official Docker GPG key using the following command:

curl -fsSL | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg 

4. Add the Docker repository to the apt sources list:

echo "deb [arch=amd64 signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null 

5. Update the package index again to include the Docker repository:

sudo apt update

6. Install Docker by running the following command:

sudo apt install docker-ce docker-ce-cli

7. Verify docker is running:

docker --version

Install Aerolab

[Editors note: use cd ~ instead of steps 1 and 2]

  1. In Ubuntu run: cd .. #until you are at the furthest out directory

  2. Access the bin: cd usr/local/bin/

  3. Install the Aerolab package: For AMD: sudo wget For ARM: sudo wget

  4. Then, depending on the file you downloaded run: [Editors note: this step is not technically required] sudo chmod +x [FILE NAME]

  5. Unpack the file: sudo dpkg -i [FILE NAME]

  6. The Aerolab command is now available so run: aerolab

  7. Follow the given instructions.

Install VSCode

  1. Run on Ubuntu: aerolab client create vscode -n vscode -e 8080:8080

  2. Open in your browser: http://localhost:8080

  3. VSCode should now be accessible.

Creating Clusters and adding AMS

  1. Clusters contain nodes which store your data. If you have an enterprise version by default you will be limited to 1 node. For my internship I was able to get a feature file which allowed for 5 nodes for 2 weeks.

  2. Create a 5 node cluster by running: aerolab cluster create -n myCluster -c 5

  3. Add the prometheus exporter by running: aerolab cluster add exporter -n myCluster

  4. Create the AMS client: aerolab client create ams -n ams -s myCluster -e 3000:3000

  5. Open in your browser: http://localhost:3000

  6. The User and Password for Grafana is: admin, admin

  7. The AMS now works!

Get AS Bench Working

  1. ASBench allows you to test your nodes and clusters by putting them under strain.

  2. To get started, create 5 tools clients: aerolab client create tools -n myClient -c 5

  3. Add Promtail to clients to push asbenchmark logs to AMS stack: aerolab client configure tools -l all -n myClient --ams ams

  4. To test ASBench on your cluster just run: [Editors note: this command should be aerolab attach client -n myClient -l all --parallel --asbench] aerolab attach shell -n myCluster -l all asbench

  5. There are additional parameters you can tinker with.

Code Example

I wanted to be able to actually use this database for something so I decided to use it to visualize statistics. It's important to note this isn't necessarily the best way to use this database as it's much better suited for 24/7 use where you need to be able to quickly view data.

  1. To do this, first download the Air Traffic Passenger Statistics from

  2. Then insert the file into VSCode by dragging it into the python folder.

  3. Add the following two scripts to the folder:

import aerospike
config = {
    'hosts': [
        ( '', 3000 ), 
        ( '', 3000 ), 
        ( '', 3000 ), 
        ( '', 3000 ), 
        ( '', 3000 ) 
    'policies': { 
        'timeout': 10000 # milliseconds 
client = aerospike.client(config) 
write_policy = {'key': aerospike.POLICY_KEY_SEND} 
f = open("/opt/code/python/Air_Traffic_Passenger_Statistics.csv", "r") 
for line in f: 
    line = line[0:len(line)-1] #remove last "\n" from the end 
    line = line.split(",") #turn line into list 
    if i==1: 
        headers = line #get headers from first line 
        key = ('test', 'ATPStatistics', 5000+i) #key for each record, increases by 1 for each
        reportMap = {} #actual data 
    for header in headers: 
    bins = { 
        'occurred': 20220531, 
        'reported': 20220601, 
        'posted': 20220601, 
        'report': reportMap, 
    # Write the record to Aerospike 
    client.put(key, bins, policy=write_policy) 
import aerospike 
import plotly.graph_objects as go
config = { 
    'hosts': [ 
        ('', 3000), 
        ('', 3000), 
        ('', 3000), 
        ('', 3000), 
        ('', 3000) 
    'policies': { 
        'timeout': 10000 # milliseconds 
client = aerospike.client(config) 
namespace = 'test' # Replace with your namespace 
set_name = 'ATPStatistics' # Replace with your set name 
airline_passengers = {} 
policy = {'socket_timeout': 300} 
scan = client.scan(namespace, set_name) # Create a scan operation 
# Iterate over all records using scan.foreach() 
def process_record(record): 
    key = record[0] 
    bins = record[2] 
    airline = str(bins['report']['Published Airline']) 
        passengers = int(bins['report']['Passenger Count']) 
    if airline in airline_passengers: 
        airline_passengers[airline] += passengers 
        airline_passengers[airline] = passengers 
scan.foreach(process_record, policy=policy) # Perform the scan operation and process each record 
airlines = list(airline_passengers.keys()) 
passengers = list(airline_passengers.values()) 
fig = go.Figure(data=[go.Bar(x=airlines, y=passengers)]) 
    title='Passengers per Airline', 
    yaxis_title='Passenger Count' 

4. In the VSCode terminal install plotly by running:

pip install plotly  

5. Replace the IPs in config with your nodes’ IPs, which you can find by running:

aerolab cluster list

6. Run and then, the output should look like this:

image1 1686170843802

Image of the output

Everything now works! You can interface with the client using your API of choice from here The simplest way to interface is using atomic transactions. You can also clear your cluster by stopping it:

aerolab cluster stop -n myCluster

and then start it again:

aerolab cluster start -n myCluster

You can get all the IPs of your nodes for the config by running:

aerolab cluster list

and the clients by running:

aerolab client list

You will need to restart the client and clusters when you shut down your computer and you can reconfigure the ams to connect to the nodes by running:

aerolab client configure ams -n ams -s myCluster

[Editors note: Amazing job Theodore!]