In the context of public cloud infrastructure, a sandbox environment is a development and testing environment that allows users to experiment with resources and services without affecting production systems.
Sandbox environments offer the benefits of learning, experimentation, and prototyping new features in a safe and isolated way. However, maintaining segregation while ensuring that the environments resemble production environments closely enough to keep any prototyping relevant introduces management complexity.
This article discusses the best practices for maintaining sandbox environments to ensure that you get the most value from your cloud infrastructure while minimizing complexity.
Before looking further into the best practices associated with sandbox environments, it’s worth clarifying a common cause of confusion: the difference between sandbox and development environments. While sandbox and development environments are both used to build and test software, they serve different purposes and have distinct characteristics.
Developers use development environments to write, debug, and experiment with code. Active development and initial testing occur in these environments, including integration and unit testing.
Sandbox environments, however, provide a more controlled and isolated space for testing how code interacts with systems, APIs, or third-party services without impacting the live production environment. Sandboxes are used for testing configurations and interactions, especially in regulated industries or when third-party access is required.
Development environments typically contain mock data or subsets of real data for testing purposes but not production-level data. Developers can modify this data to test different scenarios. Meanwhile, sandbox environments utilize data masking, replacing sensitive information with anonymized or placeholder data to simulate real-world conditions more accurately while protecting privacy. They do not typically contain actual production data for security and compliance reasons. If actual data is necessary, it should be segmented and securely stored to prevent misuse.
Development environments are used throughout coding and early testing phases, including debugging, unit testing, and integration testing. They are optimized for code changes and quick testing iterations. At the same time, sandbox environments are used for controlled, pre-production testing to validate features, configurations, and integrations in conditions that closely resemble production. They are commonly used to test third-party integrations, simulate user interactions, or evaluate security and compliance.
In short, development environments prioritize flexibility and ease of development for internal use. In contrast, sandbox environments prioritize control, security, and simulation of production-like scenarios for more rigorous testing, particularly with external interactions.
Sandbox environments can provide a broad range of access to various functionalities or systems while keeping security risks minimal. By creating an isolated environment, sandboxes enable developers, testers, and users to interact with systems or applications without affecting production environments or exposing sensitive data.
Sandboxes create a controlled, separate environment where code or applications can run independently from your production infrastructure, which prevents unwanted changes or security risks from spreading to other parts of your wider environment.
You should log and monitor all actions within each sandbox environment using tools such as AWS CloudTrail, AWS CloudWatch, and AWS Config, enabling administrators to track and review activities. This can help you identify and address malicious behavior or performance issues quickly. Monitoring also provides a safe space to test potential vulnerabilities or new features, where risks can be observed and controlled.
By balancing wide-ranging access across a sandbox with restrictions on what the sandbox can connect to, sandbox environments support safe experimentation, innovation, and testing without compromising security or production stability.
Although sandboxes are ideally completely isolated from production environments, if it is necessary to connect the two, security tooling such as AWS IAM, VPC security groups, and Amazon GuardDuty should be implemented to ensure only essential connectivity between environments.
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Despite sandboxes typically being highly controlled, a sandbox usage policy should still exist to establish clear guidelines for using the environment. Although segregated from production resources and data, it is still pertinent to clarify acceptable and unacceptable behaviors, set expectations, and hold users accountable for their actions within the sandbox environment.
By defining and limiting what can be done in the sandbox, the policy should help prevent malicious code or malware from affecting production environments, keeping potentially risky testing contained.
The policy should also restrict access to sensitive data and ensure that experimental changes don’t impact live data. It should be clear that users can only access data that is safe to use within the sandbox.
Sandboxes consume resources (e.g., processing power, storage, etc.), so the policy should limit excessive use that could impact overall system performance and generate unexpected costs.
By using a sandbox environment with well-established guidelines, organizations reduce the risk of unintended disruptions to live systems or other sandbox users and ensure a safer testing ground for innovation and development. A good usage policy should promote a secure, efficient, and organized environment for development and testing.
As with any other cloud resource, tracking and maintaining the cost of a sandbox environment is essential to ensure cost efficiency.
Sandboxes can be resource-intensive, especially when running large-scale tests or simulations. Tracking costs can help pinpoint where resources are used inefficiently, enabling optimization.
When operating with a fixed IT or R&D budget, monitoring sandbox costs helps you stay within those budgets and reduces the likelihood of unexpected overspending. Tracking expenses also provides insight into trends, allowing teams to plan for future projects better.
Knowing which project or team uses specific resources allows for better cost allocation and accountability. This helps distribute costs accurately and hold users responsible for their consumption. When teams know they are being monitored, they are more likely to be conscious about their usage, which reduces waste and helps manage costs.
Cloud financial management tools such as AWS Cost Explorer, AWS Budgets, and AWS Cost Anomaly Detection should all be configured against your sandboxes for optimal financial reporting and control. This will support the organization’s broader innovation, growth, and budget-conscious operation goals.
Guardrails are policies and configurations that help maintain a safe and controlled sandbox environment. They balance flexibility and security, allowing users to experiment, develop, and test without risking the security or stability of production systems. They also ensure that the sandbox usage policy is followed by enforcing restrictions rather than acting on trust.
Examples of guardrails include, but are not limited to, the following:
Implementing guardrails ensures a safe, reliable, and efficient sandbox environment for testing and development. Although a usage policy goes some way toward achieving this by clearly defining what is acceptable and holding users accountable for their actions, preventing users from performing unacceptable actions reduces risks while still allowing users the freedom to innovate and experiment within these enforced boundaries.
Until now, it has been implied that a sandbox environment would be a single entity used by all users and teams. However, all of the best practices above can be implemented more granularly if sandbox environments are provided on a per-user or per-team basis.
Providing each user or team with their own sandbox isolates different users’ or teams' activities, reducing the risk of accidental or malicious behavior between environments. Minimal permissions should be granted to production environments and environments dedicated to other users or teams. As previously discussed, if cross-team or cross-user connectivity is required, it should be enabled in a controlled and managed manner via AWS security tools.
Per-user or per-team sandboxes can also enable a tighter budget and resource allocation per user or team, providing a clear view of cloud usage. Allocating resources based on a user's or team's needs ensures that they receive all the resources they need but no more. This prevents waste and improves efficiency.
Tracking use at a granular level encourages accountability for cloud spend and helps prevent overspending. Using guardrails to enforce tagging resources inside each user’s or team’s sandbox provides an even more granular approach to cost tracking and allocating within a team.
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Using temporary resources and environments allows teams to create, test, and deploy resources only when needed and tear them down afterward. This provides cost savings, flexibility, and risk reduction in various development and operational scenarios.
Temporary resources eliminate the cost of running unused or idle resources. Instead of paying for always-on infrastructure, teams can launch resources for a specific task or test as needed.
Ideally, even an AWS account should be considered a temporary resource. This is the best way to ensure that nothing persists between each development or testing session. However, creating a new AWS account and configuring all the best practices described above before each session will soon become time-consuming, especially if done via the AWS web GUI.
AWS organizational units (OUs) are part of AWS Organizations, a service that allows you to centrally manage multiple AWS accounts. They provide a way to organize and manage AWS accounts in a multi-account environment. Organizing accounts into a hierarchical structure helps simplify governance, policy enforcement, and account management across your infrastructure.
AWS OUs allow you to group AWS accounts in a tree-like structure, making it easier to apply management policies at a higher level for all accounts within the OU. If configured to do so, all accounts within the OU automatically inherit those policies.
You can create OUs for different environments like sandbox, development, testing, and production, or logically group accounts based on specific needs, such as business units, teams, or projects. You can also combine organizational approaches for more complex environments, creating different AWS accounts for each environment within each business unit, team, or project. This simplifies management tasks like billing, security, and resource access control, as policies can be applied at the OU level instead of to each account.
Service control policies allow you to control which AWS services and actions are allowed or denied within the accounts under that OU. This helps enforce security and compliance policies across all accounts. However, managing service control policies and the OU organization can introduce complexity.
These features can simplify provisioning multiple AWS accounts, but this is still a relatively time-consuming process and far from self-service for development teams. If the practice of implementing guardrails and controlled permissions has been followed, they are unlikely to have direct access to AWS to provision new accounts for themselves.
As discussed earlier, manually managing temporary resources and environments can be time-consuming. The ability to manage the lifecycle of a temporary sandbox environment is limited, even when using AWS OUs to simplify some of the processes.
Infrastructure as code (IaC) tools like Terraform or AWS CloudFormation define resources as code. This allows for consistent, repeatable provisioning and easy scaling. Creating reusable templates that match everyday sandbox needs (e.g., for development, testing, or training environments) so users can quickly spin up resources based on standardized configurations improves usability, ensuring that code behaves consistently across all deployment stages. IaC removes some of the time-consuming and repetitive tasks associated with creating new AWS accounts and configuring all best practices but introduces other complexities, especially if your team is new to the concept of IaC.
Utilizing IaC to automate resource creation, usage, and termination can ensure cost-effective resource management in your sandbox environments. By leveraging automation, you can dynamically allocate resources when needed, monitor usage in real time, and quickly free up resources once they’re no longer required. Integrating with cloud APIs to provision resources based on triggers or scheduled tasks helps ensure that resources are only created when needed. As this is done automatically, it moves some of the complexity away from those who are unfamiliar with IaC itself.
Automating resource management in a sandbox environment helps balance resource availability and cost control and moves some complexity away from users who are unfamiliar with deployment techniques for infrastructure as code. That said, creating IaC and the required automation is not always straightforward, especially if dynamic and variable environments are needed for many use cases.
Using a developer platform like Coherence based on the CNC platform engineering framework can simplify matters, giving your team a world-class developer experience that will scale as you grow. It allows you to easily create new environments via UI, CLI, or integrations, including production, staging, dev, and ephemeral sandbox environments. This enables you to collaborate with your team securely using environment variables, cloud secrets, RBAC, and automated CI/CD.
Built-in reference architectures assist in rapid deployment while allowing you to retain the freedom to customize or even write your own architecture. It can significantly simplify the process of creating dynamic IaC that can be provisioned automatically or on a self-serve basis by those less familiar with IaC concepts. It allows you to implement the best practices of sandbox environments without the time consumption or complexity associated with them.
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Although sandbox environments offer significant benefits by providing a controlled and isolated space for testing during the development lifecycle, they also add managerial complexity to your infrastructure. Resource sprawl, security, compliance, and cost overruns must all be considered and tightly controlled to ensure the effective use of sandboxes.
Conducting regular audits and cleanups, implementing strict security policies, and configuring continuous monitoring and optimization all help avoid some of the potential pitfalls of sandbox environments, but configuring this is a complexity of its own. Developer platforms like Coherence attempt to remove some of this complexity, allowing you to implement the best practices of sandbox environments with relative ease. This improves the platform experience for your developers, allowing them to develop, test, and ultimately deploy software quickly and securely.
