Finding Savings in Your Lower Environments – ROI of Test Environments & Test Data


The Unseen Cost of Software Development Did you know that organizations typically spend over 50% of their IT environment budget on testing? While the spotlight often shines on development and production, lower environments—like testing and staging—are essential yet often overlooked areas for cost-saving. This article aims to shed light on two crucial aspects: Test Environment Management (TEM) and Test Data Management (TDM), which are critical for both enhancing organizational IT delivery and controlling IT costs.

Why Lower Environments Matter

The Backbone of Quality Software Lower environments are crucial for software testing, data validation, and quality assurance. However, these environments are complex to manage and can become cost centers if not handled efficiently. From hardware and software licensing to personnel and service costs, these areas offer tremendous potential for optimization.

ROI of Test Environment Management (ROI of TEM)

Unlock Savings Through Efficient Test Environments

  • Unlock Savings Through Efficient Test Environments
    • Reduction in Infrastructure Costs: TEM enables you to make better use of existing resources. Virtualization technologies let you run multiple test environments on a single server, reducing hardware costs.
    • Reduction in License Costs: By optimizing software licenses across test environments, you can cut down the number of required licenses, leading to substantial savings.
    • Reduction in Service Costs: Automated setup and configuration processes can significantly cut down on service costs related to environment management.
    • Reduction in Headcount: Automation also reduces the need for manual labor, thus allowing your employees to focus on value-added tasks and leading to staffing efficiencies.

Useful Tool: For a thorough evaluation, consider using ROI calculators like the one offered by Enov8. It can provide you with tailored insights into potential cost savings.

ROI of Test Data Management (ROI of TDM)

Optimize Your Test Data for Maximum Efficiency

  • Reduction in Infrastructure Costs: TDM allows you to minimize the need to replicate entire production environments, reducing hardware and storage costs.
  • Enhancement in Tester Productivity: Quick provisioning of accurate and compliant test data can lead to faster testing cycles.
  • Boost in Developer Productivity: With streamlined access to quality data, developers can focus on coding rather than data management, resulting in quicker development cycles.
  • Minimization of Support Costs: Better quality of test data can lead to more reliable testing outcomes, reducing the cost of post-launch support and rework.
  • Averting Data Breach Costs: By using de-identified data for testing, the risks of data breaches are minimized, thereby potentially saving significant costs related to data security incidents.

Synergies Between TEM and TDM

Better Together for Greater Savings Combining TEM and TDM offers synergistic benefits. For example, TEM’s efficient hardware utilization can be maximized when paired with TDM’s efficient data management. By synchronizing these two functions, organizations can achieve cumulative ROI that is greater than the sum of their parts.

Action Steps for Organizations

Your Roadmap to Implementation

  1. Conduct a Pilot Project: Start small to understand the benefits and challenges.
  2. Engage Stakeholders: Get buy-in from relevant departments.
  3. Choose the Right Tools: Look for platforms that align with your organization’s specific needs and risk tolerance.


By focusing on the ROI of both TEM and TDM, organizations can unlock significant savings while maintaining, or even enhancing, the quality of software delivery. In a world where every dollar counts, these lower environments offer a fertile ground for impactful cost optimization.

OKR Explained

What is an OKR?

  • OKR stands for Objectives and Key Results.

It is a popular goal-setting framework used by teams and individuals to set ambitious goals with measurable results. OKRs are typically set quarterly, but they can also be set annually or monthly.

How do OKRs work?

The first step in setting OKRs is to define your objectives. Objectives are qualitative statements that describe what you want to achieve. They should be ambitious but achievable.

Once you have defined your objectives, you need to identify the key results that will measure your progress towards your objectives. Key results are quantitative statements that track your progress towards your objectives. They should be specific, measurable, achievable, relevant, and time-bound.

Benefits of using OKRs

There are many benefits to using OKRs, including:

  • Increased focus and alignment: OKRs help teams stay focused on the most important goals. They also help to align teams around a common vision.
  • Improved transparency and accountability: OKRs are transparent and visible to everyone in the organization. This helps to improve accountability and ensure that everyone is working towards the same goals.
  • Greater motivation and engagement: OKRs are motivating because they are ambitious and challenging. They also help to engage employees by giving them a sense of ownership over their work.
  • Improved decision-making: OKRs provide a framework for making decisions. By understanding the organization’s goals and key results, teams can make decisions that are aligned with the organization’s priorities.

How to implement OKRs

Here are some tips for implementing OKRs:

  • Start small: Don’t try to implement OKRs across the entire organization all at once. Start with a small team or department and gradually expand the program as you gain experience.
  • Get buy-in from leadership: OKRs are more likely to be successful if they have the support of leadership. Make sure that your CEO and other senior leaders are on board with the program before you launch it.
  • Train your team: OKRs can be a complex concept, so it’s important to train your team on how to use them effectively. Provide your team with resources and training so that they understand the framework and how to set and track OKRs.
  • Be flexible: OKRs are a living document, so don’t be afraid to make changes as needed. If an objective or key result isn’t working, don’t be afraid to adjust it.

Examples of OKRs

Here are some examples of OKRs:

  • Objective: Increase website traffic by 10% in the next quarter.
  • Key Results:
    • Increase organic search traffic by 5%.
    • Increase social media traffic by 3%.
    • Increase referral traffic by 2%.
  • Objective: Launch a new product by the end of the year.
  • Key Results:
    • Complete the product design by the end of the quarter.
    • Develop the product by the end of the second quarter.
    • Test the product with users by the end of the third quarter.
    • Launch the product by the end of the year.


Here are some specific examples of how OKRs can be used to support test environment management improvements:

  • Objective: Improve the reliability of test environments.
  • Key Results
    • Reduce the number of outages in test environments by 50%.
    •  Increase the uptime of test environments to 99%.
  • Objective: Improve the efficiency of test environment provisioning.
  • Key Result
    • Reduce the time it takes to provision a new test environment by 50%.
    • Increase the number of test environments that can be provisioned simultaneously by 25%.
  • Objective: Improve the security of test environments.
  • Key Result
    • Implement security controls in all test environments.
    • Conduct security assessments of all test environments on a quarterly basis.

By using OKRs to focus on specific goals and track progress over time, teams can improve the effectiveness of their test environment management efforts


OKRs are a powerful goal-setting framework that can help teams and individuals achieve their goals. If you’re looking for a way to improve your focus, alignment, and motivation, consider implementing OKRs in your organization.

database cloning

Understanding Data Cloning: A Guide for Beginners

Data Cloning, alternatively referred to as Database Virtualization, is a sophisticated technique that encompasses the process of capturing snapshots of authentic data, subsequently resulting in the creation of miniature, albeit fully functional and operational, replicas. These compact and efficient duplicates are subsequently and expeditiously provisioned into the designated Development and Test Environments, streamlining the process of testing and ensuring the integrity of the original dataset remains uncompromised.

The Cloning Process

There are four main steps:

  1. Ingest the Source Data
  2. Snapshot the Data
  3. Replicate the Data
  4. Provision the Data to new Environments

Behind the Scenes Cloning usually employs ZFS or HyperV technologies, which allow you to transition from traditional backup and restore methods that can take hours.

Utilizing ZFS or HyperV enables database provisioning to be 100 times faster and ten times smaller.

What is ZFS?

ZFS, short for Zettabyte File System, is a revolutionary file system that places a strong emphasis on data integrity, reliability, and ease of management. It was initially developed by Sun Microsystems and is now maintained as an open-source project. As a file system, ZFS not only guarantees data integrity by using advanced error detection and correction mechanisms but also supports snapshotting, a feature that allows for the efficient creation of point-in-time representations of the data stored within the system.

ZFS is unique in that it combines the roles of a traditional file system and a volume manager, which simplifies storage management tasks and reduces complexity. This integrated approach allows for advanced features such as data compression, deduplication, and the ability to create and manage storage pools. Furthermore, ZFS’s inherent copy-on-write functionality ensures that data is never overwritten, safeguarding against data corruption and enabling easy recovery in the event of an issue.

What is HyperV?

HyperV, also known as Microsoft Hyper-V or simply Hyper-V, is a virtualization technology developed by Microsoft that allows users to create, manage, and run multiple virtual machines (VMs) on a single physical host. This capability enables the efficient utilization of hardware resources, as multiple operating systems and applications can coexist and run concurrently on a single server. Hyper-V is an integral component of Microsoft’s Windows Server product line and is also available as a standalone product, known as Hyper-V Server.

One of the key features of Hyper-V is its support for snapshotting, which allows administrators to capture the state of a virtual machine at a specific point in time. These snapshots can include the VM’s memory, virtual disks, and hardware configuration. The snapshot functionality is particularly useful for tasks such as testing software updates, rolling back to a previous state in case of an error, or creating point-in-time backups for disaster recovery.

Problem Statement

Traditional backup methods often involve manual processes that can be time-consuming, taking hours or even days to complete. While these backups are in progress, the data being backed up is typically inaccessible, which can lead to significant operational challenges when immediate access to the data is necessary for ongoing business activities or critical decision-making.

Moreover, the storage requirements for these traditional backup and restore operations can be substantial. Since the process creates a full, 100% copy of the original source data, the storage demands can quickly escalate. For example, a 5 TB database would necessitate an additional 15 TB of disk space if three separate restore points were required. This considerable storage overhead not only adds to the overall cost of maintaining the backup infrastructure but also has implications for the time and resources needed to manage and maintain the storage environment.

Benefits of Data Cloning

Data Cloning involves generating a snapshot, or copy, of data for backup, analysis, or engineering purposes, either in real-time or as part of a scheduled routine. Data clones facilitate the provisioning of new databases and testing changes to production systems without impacting live data.


  • Clones can be employed for development and testing without affecting production data
  • Clones consume minimal storage, averaging about 40 MB, even for a 1 TB source
  • The Snapshot & Cloning process is completed in seconds rather than hours
  • Clones can be restored to any point in time by bookmarking
  • Simplifies end-to-end data management


  • The technology required for cloning can be complex

However, various user-friendly tools on the market can mitigate this complexity.

Data Cloning Tools

Besides building your own solution, commercial cloning options include:

  • Delphix
  • RedGate SQL Clone
  • Enov8 vME (VirtualizeMe)
  • Windocks

Each tool offers unique features and benefits. It’s crucial to understand your data environment and objectives before making a final decision.

Data Cloning Use Cases

  1. DevOps: Data cloning creates exact copies of datasets for backups or replicating test data in Test Environments for development and testing.
  2. Cloud Migration: Data cloning offers a secure and efficient method for transferring TB-size datasets from on-premises to the cloud, enabling space-efficient data environments for testing and cutover rehearsal.
  3. Platform Upgrades: Data virtualization reduces complexity, lowers total cost of ownership, and accelerates projects by delivering virtual data copies to platform teams more efficiently than traditional processes.
  4. Analytics: Data clones facilitate query and report design and provide on-demand access to integrated data across sources for BI projects without compromising the original dataset.
  5. Production Support: Data cloning helps teams identify and resolve production issues by supplying complete virtual data environments for root cause analysis and change validation.

In Conclusion

Data cloning, as a cutting-edge technique, facilitates the generation of precise duplicates of datasets for a diverse array of applications, including but not limited to, producing backups or replicating crucial data to be utilized in the realms of development and testing. The intrinsic capability of data clones to expedite the provisioning process for new databases, as well as to rigorously test alterations made to production systems without causing any disruptions or adverse effects on live data, underscores the value of this approach in modern data management practices.

By employing data cloning, organizations can achieve increased efficiency, heightened agility, and greater flexibility in managing their data resources, thereby ensuring a more streamlined and effective approach to handling the ever-growing demands of data-driven operations and decision-making processes.