Discover the key benefits of using a sandbox environment and how to create one in Keboola.
Ever had your live app crash after a new update, forcing you to spend your weekends fixing it? Let us guess, an enthusiastic developer introduced a change without testing it thoroughly.
But it’s not just app development that can go rogue. Whether it's last-minute changes to client reports, tweaks to your marketing campaign, or any other update in a live setting, unexpected problems can crop up.
Even your cousin with minimal tech experience will advise you: Always test in a sandbox environment before releasing your data product.
In this article, you'll learn:
A sandbox environment is a controlled and isolated environment designed for testing, experimentation, and development purposes.
It acts as a replica or twin of the production environment, offering a safe and separate environment for data teams in marketing and various other industries.
Think of a sandbox as a playground for grown-ups. Here you can test, play, and experiment without messing up the real stuff. This setup gives you a free pass to try and break things without affecting the end users.
For example, in this testing environment, you can run quality assurance checks on your marketing dashboards before sharing them with your clients. And, as a development environment, it enables you to test new features (e.g. optimize customer churn prediction with a new machine learning algorithm) - without breaking the production features.
Sandboxes are nifty tools that data teams in marketing (and other departments) can use to work their magic over multiple use cases.
Imagine you're developing a new customer loyalty app. Before rolling it out to your clients, you want to ensure it works flawlessly and doesn't cause any unexpected issues.
In a sandbox environment, you can extensively test the platform, send loyalty emails, subscribe and unsubscribe customers from loyalty campaigns, and generally verify that all features function as expected. This way, you can avoid any potential mishaps and deliver a polished marketing solution to your clients.
As a data scientist, you've come up with a brilliant idea for a machine-learning model that can predict customer behavior accurately. Before implementing it in your live marketing campaigns, you can test the model in a sandbox environment.
You experiment with different algorithms, fine-tune the model's parameters, and assess its performance on sample datasets. This way, you can ensure your model is optimized and delivers accurate predictions when deployed in the production environment.
You're a part of a consultancy agency, and your client is a retail company interested in understanding their customer demographics better.
In a sandbox environment, you can share a secure, anonymized dataset containing customer information. This allows your client to explore this data, conduct analysis, and provide feedback without accessing sensitive customer details.
This collaboration ensures data privacy and enables your client to make data-driven decisions for their marketing strategies. And since this data is in a sandbox and isolated from your complete datasets, you don’t have to worry the clients will accidentally have permission to view sensitive data.
The best part? You can automate this workflow and share data with multiple clients using the same sandboxing technology in real time. All while guaranteeing data governance, security, and privacy.
Your team has developed a new landing page to handle customer sign-ups and logins. Before making it publicly available, you want to assess its security against potential cyber threats.
Within a sandbox environment, you can simulate common cybersecurity attacks, such as SQL injection or cross-site scripting, to identify any vulnerabilities. This way, you can patch up any weaknesses and ensure your application remains secure when deployed in the real world.
Sandboxing is not used just in marketing. Cybersecurity researchers consistently use sandboxes as an additional layer of security when testing malicious code, new antivirus software, firewalls, malware-detection algorithms, or exploring other security threats.
Your marketing team is launching a revamped website with a new user interface and interactive features.
To ensure a smooth user experience, you conduct quality assurance testing to see how it works in a sandbox environment.
Your team checks the functionality of buttons, navigational elements, and data displays. By detecting and fixing any issues in the sandbox, you guarantee a seamless user experience when the website goes live.
Testing in sandboxes before deploying is a common best practice in software development.
You've introduced a new marketing automation tool to streamline your team's workflow. To get everyone up to speed, you provide access to a sandbox environment containing sample data.
In this risk-free space, team members can practice creating automated marketing campaigns, setting up workflows, and analyzing performance metrics. This hands-on learning experience helps them become proficient with the new tool before using it in real marketing campaigns.
Impatient to try a sandbox use case yourself? Wait no longer. We’ll show you two approaches: the classic, more challenging way, and the new, simplified approach.
Traditionally, there have been three primary methods for creating sandbox environments:
But traditional technologies posed several challenges for data engineers:
Luckily, there’s a more straightforward and easier way to create a sandbox.
Keboola is the data stack as a service that automates all your data operations — including creating a new sandbox environment.
Creating a new sandbox environment in Keboola is as simple as a three-click process:
Prerequisite: Ensure you have data in Keboola Storage. No data in Storage yet? Follow this easy tutorial to see how simple it is to load data into Keboola.
4. Load data into the new sandbox environment and start experimenting.
Curious about the fine details and possible customizations? Check Keboola’s docs for details.
Choosing Keboola for your sandbox environment has many benefits:
And those are just on top of the benefits you unlock by using sandboxes.
A sandbox environment brings many benefits to data teams:
Keboola helps you unlock all the benefits of sandbox environments, including safety, quality assurance, experimentation, template ability, and time savings.
Moreover, unlike other sandboxing technologies, in Keboola you can set up a new sandbox environment in a couple of clicks — without worrying about the DataOps.
The best part? Keboola offers an always-free tier for every user, so you can play with data without breaking the piggy bank.