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Which Test Data Management Method Is Best?

Replicating Data From Production

The first approach we’re going to cover in this post is perhaps the most popular one, at least for beginners. And that makes perfect sense if you think about it. When you first encounter the challenge of coming up with data to feed your testing processes, it isn’t too far-fetched to think you should just copy data from production and be done with it. It’s the easiest way to obtain data that is as realistic as possible. You just can’t get more real than production.

Not everything is a bed of roses when it comes to production data replication. Quite the opposite, actually. The easy access to data is pretty much the only advantage this method has. And what about the disadvantages? These, sadly, abound.

Here Be Dragons: Some Downsides of the Approach

Here’s the first problem: replicating data from production continues to be mostly a manual process. Sure, you can come up with scripts and automated jobs to do most of the heavy lifting for you. But keep in mind that generating the data isn’t the whole job of a TDM management solution. “Availability” is an integral part of the package. That means that the TDM tool is responsible for making sure the data is available where it’s needed, at the right time. A naive approach based on scripts might not be sufficient to manage the demands of a complex testing process, forcing you to rely on a manual process to do so.

Secondly, production replication doesn’t lend itself well to negative test cases. It’d be out of the scope of this post to give a lengthy explanation of negative testing. In a nutshell, negative test cases are tests that validate the system against invalid data. Basically, you throw faulty data at your application to check how well it can handle it. Since production data would (hopefully) be in good shape, this approach isn’t well suited to this type of testing.

Production data replication also doesn’t work…if there is not data replication for you to replicate in the first place! What should you do when you need to test an application that is still in the alpha stage of development or even a prototype? Since no one is actually using the application, there would be no production data for you to copy. That’s a severe downside of this approach since every new application will face this problem.

Here Be Dragons (For Real): Legal Implications

Finally, we have the most serious downside of this approach—data sensitivity. Data compliance is a crucial part of the modern IT landscape since companies are responsible for the data they store and manipulate. It’s up to them to protect their client’s data, ensuring it’s not abused. When replicating data from production, software organizations run the risk of failing to comply with privacy acts, such as GDPR. And that can bring catastrophic consequences, legal, financial, and reputation-wise.

Data Masking

In order to solve the downsides of production data replication (a.k.a the naive approach), test data management tools have come up with more sophisticated methods. One of the
most popular of these approaches is test data masking. As its name implies, tools that adopt this approach enable its users to apply masks to production data. Such masks will remove personally identifiable information (PII) from the data.

Data masking is an improvement over naive production data replication, for sure. But the approach is not without its downsides.

First, consider the “time” variable. Data masking doesn’t reduce the time spent generating (or rather, copying) the data for testing. On the contrary, it increases it because now you have a new added in the process. You could argue—and I’d gladly agree—that it’s time well spent, but it’s more time nonetheless.

Then, you also have to keep in mind that data masking isn’t a standalone approach on its own. Instead, it complements the previous approach by solving one of its more serious issues. The problem is data masking can’t fix every problem that the production replication approach has. For instance, if you intend to test an application still in development, for which there is no production data at all, data masking is powerless to help you.

Synthetic Data Generation

Synthetic data generation is yet another method of test data management. As its name suggests, this approach consists of generating “fake”—or synthetic—data from a data model. Tools that implement this approach are able to preserve the format of the data. The values themselves, though, are completely disconnected from any original data. What does that imply?

The implication of this is that synthetic data generation’s greatest asset is simultaneously its most significant downside. By populating the database with entirely “made-up” values, the approach dramatically reduces (virtually eliminates) the risk of exposing sensitive data. On the other hand, depending on the tool’s sophistication—or lack of—you might end up with data that feels “fake-y.” One of the goals of an excellent TDM strategy is to provide data that is as production-like as possible.

To wrap-up, let’s talk about the biggest advantage of synthetic data generation, namely: speed. Once you have a model in place, you can quickly generate data from it, effectively eliminating the time delays that plague other approaches.

Test Data Management Is More Than Test Data Generation

In this post, we’ve covered some of the most used approaches to generate test data. The list is definitely not exhaustive; there are many more methods that we didn’t cover. However, many of them are variations or combinations of the approaches we did talk about.

Another thing to keep in mind is that test data management is much more than just generating test data. TDM is responsible for ensuring the quality of the test data, its availability, and also its security. In other words: the data must be good, and it must be available at the right place, at the right time. And bad actors shouldn’t be allowed to expose it or misuse it in any way. That’s why, depending on the needs of your organization, you should consider adopting a full-fledged data compliance solution, which can not only supply your data generation needs but also make sure your data adhere to the compliance requirements you must follow.

Test Environment Management 10 Essential Practices

Importance of Test Environment Management

As technology evolves, requirements keep changing. For instance, with Angular dominating the UI domain, the demand for single-page applications has increased a lot. Cost, time, and quality are the most important factors to check for every business. Every firm aims for the appropriate budget and ample time before starting a project. But somehow, these two entities face the most shortage. Well, we don’t live in an ideal world, do we? Sometimes, due to time and budget constraints, the quality of the end product declines.

But budget and time shortages don’t mean that you should compromise on the testing phase. Software testing is a tricky process with the involvement of several dependencies.

Testing is a crucial activity of the software development life cycle (SDLC) and can determine a product’s fate. Therefore, the test environment has to be reliable. Do you want to disappoint customers with a product that has many critical bugs because of improper testing? No matter whether you’re a start-up or an established company, never overlook the importance of testing. For getting the highest accuracy in test results, your team needs proper test environment management.

If a team doesn’t give importance to test environment management, it results in poor handling of assets. This includes time and budget. When a company can’t handle these in the right way, quality suffers. Thus, to maintain a high quality of products and services offered, it’s essential to manage the test environment. Before getting on to the best practices, take a look at these metrics, which will help you to measure and improve your test environment.

10 Best Practices for Test Environment Management

Now that we know why managing a test environment is important, let’s get started with the 10 best practices for test environment management.

1. Begin Testing Exercise at an Early Stage in the SDLC

Even though most firms know the importance of testing early, very few successfully implement it. When teams don’t test early, it leads to bugs at a later stage. Fixing them requires more time, effort, and money. As a result, it disrupts the management of the test environment. When the development team has composed even a few lines of code, testing exercises should start. The team should also follow the shift-left approach. This involves performing testing earlier in the product’s life cycle. The process results in fewer bugs to fix in the end. Hence, it saves time and cuts down costs.

2. Demand Awareness and Management of Knowledge

When customers make a demand, a company must develop a product in a way that satisfies that demand. When team members keep client needs in mind during development, the outcomes are close to what the client expects. Thus, it’s important to use a test environment management strategy according to customer needs. Testers writing a test case should develop a knowledge base according to demands. The business analyst also needs to keep updated documents that contain the current as well as changed requirements. In this way, if there is a case of updating the test environment, it keeps other team members in line with what’s going on.

3. Conduct Iterative Tests

Most companies are adopting agile as part of their framework. Agile follows a sprint-based approach. It also involves testing in iterations. That means the entire product is divided into small phases. Each phase has its development and testing cycle. The entire process reveals bugs early, which makes fixing them easier. Iterative tests increase the flexibility of the SDLC. The client can change the scope in case the need arises without it being a burden to the budget. Since the team handles bugs at every sprint, there doesn’t end up being an overload of them at the end of the project. Thus, managing risks becomes easier.

4. Plan and Coordinate

Planning is very important while managing the test environment. Testing and development teams often don’t have separate test assets. So, test environment managers should plan schedules for both teams. They should ensure proper coordination to avoid conflicts. Sometimes, shared usage of resources can give rise to certain conflicts. For instance, if there are few iOS systems in your team to develop and test iOS apps, conflict may arise regarding which team will use the systems and when. Planning and coordination is a must to maintain transparency among teams and team members. Apart from that, proper communication with clients is important to keep them updated on their requirements. Check out this use case, which will help you to effectively plan and use your resources.

5. Reuse the Test Resources and Test Cases

Reusing test resources helps save money for a company. It frees up the firm of the need to tap new resources every time a new project begins. Even though every application is unique, many have some generic areas. That’s where the option of reusing test cases increases. Reusing test cases reduces redundancy. It eliminates the need for writing a different script each time you’re testing new features. For instance, all e-commerce stores have a shopping cart. Thus, testers can use the script for testing the “add to cart” feature of another app. It won’t matter if they’ve already used it before since the feature is the same.

6. Implement Standardization and Automation

It’s important for testers to analyze the validity of tests. But this requires a benchmark. Defining test environment standards makes it possible to set up a benchmark for running the test cases. After setting these standards, it’s time to automate. Some things that can use automation include deployment, build, and shakedown. Automation can save time, resources, and manual efforts that can be put to better use later. Configuration management becomes a lot easier when the dependency on manual testers lessens. Automated TEM tools reduce the number of test environments in a test bed. As a result, it improves test environment provisioning time. Besides this, the costs incurred are lower.

7. Use Testing Techniques According to Needs

I’m going to cite a situation that you must have come across many times. There are times when something seems impossible at first. But if you break it down into chunks, it doesn’t seem overwhelming. Taking it one step at a time makes things simple. In most cases, with this approach, you succeed. Similarly, for test environment management, first, analyze the test structure. Then break down massive loads of tasks into manageable pieces. After that, understand the steps and the needs for performing each. Figure out the test endeavors and take the necessary steps. According to the need, pick out the testing techniques and implement them. For example, you can use containers to improve your system’s security and agility.

8. Mask and Encrypt Test Data

With advancement in technology, cyberthreats have increased. Endpoint devices are usually the starting point of the majority of data breaches. Not only are they a threat to users, but they also pose great hazards to companies as well. So, companies should mask and encrypt user data. Not only that, every company should avoid using real customer data during testing. Firms should ensure data compliance with PII or GDPR standards. Some processes to ensure data compliance are ETL automation, service virtualization, and data fabrication.

9. Implement Processes According to Stakeholder Requirements and the Company’s Culture

Stakeholders are the most important component determining the success of a business. They’re the ones giving the requirements. The entire team has to work according to their needs. But it’s important that their needs are in line with the company’s culture. Sometimes companies don’t have the means to ensure the fulfillment of customer requirements. This results in an unsatisfied client, which can be fatal for a company. The testing team should have pre-configured assets before they start testing. A client doesn’t forgive any unresolved bug in the later stages. For instance, if an e-commerce app in production charges the customer twice for a transaction, it can create chaos. As a result, the reputation of the company can suffer. You can take a look at this blog to analyze and refine your company’s current capabilities.

10. Convey the Right Status of the Task

Legitimate and correct correspondence is a must to ensure a smooth flow of work. If the conveying of information goes wrong, it can cost a firm its reputation. The objective of a project should be clear to all in the beginning. Team members should share the task status with the right group of people. The timing of conveying information is also important for a fruitful task.

Suppose you need a specific set of data for executing a test case. Whenever you’re stuck with that test case, convey the blockage-related information with the concerned person. Don’t just inform your QA lead. Inform the scrum master or your QA manager as well. They’ll take care of the issue so that you can smoothly carry out your task. If you hesitate regarding whom to ask, a delay in testing will occur. Before the project starts, the entire team should have clarity about whom to contact in case of emergencies or sharing daily task statuses

What Drives Appropriate Test Environment Management?

The processes for end-to-end testing should be transparent for managing your test environment. The key factors driving smooth management include the following:

Resource management: Use a resource properly and assign the right task to the right person.
Efficient planning: Plan a successful test cycle at each sprint that results in a bug-free end product.
Process optimization: Adjust the entire test process in a way that the resources give their best output.
Test automation: Automate every repetitive task that seems to waste manual labor.

Software testing is tricky. To achieve high accuracy, setting up a test environment close to a real-life scenario is important. To set up such an environment, proper planning and management are musts. Scenarios change and test environments evolve. Thus, a test environment management strategy is vital for firms. A combination of the above practices increases productivity. At the same time, test environment management practices also reduce costs and accelerate releases

7 Metrics for Configuration Management

Years ago, a company might have released a software suite and then proverbially kicked back in a chair with its feet on a desk basking in celebration.

Suffice it to say that the software world moves much faster today. It seems as though there are some companies that push out new updates every few days. And thanks to microservices architecture and the DevOps Mindset, there are many companies that are constantly updating their software or at least some feature in it.

Pumping out release after release isn’t easy. With so many moving parts and so much riding on each new update, companies need to do everything within their power to ensure that releases are well-received by users.

That starts with getting their development house in order through a process known as configuration management.

What Is Configuration Management?

Configuration management is the process in which organizations and development teams oversee new software updates to ensure they are working as designed when bugs are fixed, new features are introduced and old features are decommissioned.

Thanks to configuration management, organizations can gain full visibility into the development lifecycle and easily identify errors that may need to be fixed.

If you’re thinking about implementing configuration management, or CMDB*, at your organization, that’s great news. But like anything else, you can’t just expect configuration management to solve all of your problems on its own. You need the right approach.

What is a CMDB

A CMDB (Configuration Management Database) is a database that stores information about the IT assets and infrastructure of an organization. It is used to manage and track the configuration items (CIs) in an organization’s IT environment, including hardware, software, network devices, and other components.

A CMDB can include detailed information about the relationships between CIs, such as dependencies, dependencies, and interdependencies. This information can be used to help organizations plan changes to their IT environment, understand the impact of changes on other components, and maintain the integrity and availability of their IT services.

In addition to maintaining information about CIs, a CMDB can also be used to track service requests, incidents, problems, and changes related to the IT environment. It can help organizations improve their IT service management processes and make better decisions about their IT investments.

With that in mind, let’s take a look at seven different configuration management metrics you can track to increase the chances that your initiatives help you achieve results. Keep track of these metrics and work hard to improve them over time, and you’ll build better applications that are better received by your users.

1. Frequency of Updates

Some companies are perfectly fine with shipping updates once a quarter or even once a year. Other companies pride themselves on pumping out new updates every month, and some might aim to release even more new software packages than that.

Every software company has unique goals. It might not matter how regularly your software is updated, but it might matter how consistently it is. Your users will expect at least some rhyme and reason to the number of updates you pump out.

Keeping track of the frequency of updates metric will help you make sure you are meeting your company’s goals and satisfying customer expectations. If you’re not shipping releases as frequently as you’d like, you might want to drill deeper and find out why.

2. Release Downtime Metrics

We all know how applications should work. When they don’t work as designed, we’re unable to get things done quickly. Depending on how bad the problem gets, it’s easy to get frustrated to the point a user starts thinking about whether they should find a substitute solution.

End users depend on your software. For a business user, that might mean a platform they use to store information and communicate with colleagues. It might mean a place they store code for a developer. And for a regular customer it might be a social network they use every day to meet new people.

Whatever the case may be, the moment you are unable to meet user expectations might be the moment your users begin an exodus.

Worse than that, downtime can be prohibitively expensive. In fact, a recent Gartner report found that downtime can cost as much as $540,000 per hour.

Keeping track of how much downtime you incur (if any) while a new update is released can help you maintain positive and productive user experiences. In the event there is downtime during a new release, you can quickly identify what happened and take steps to reduce the chances it happens again.

Add it all up, and keeping tabs of this metric can help you provide better experiences while increasing profitability.

3. Average Number of Errors

In a perfect world, your developers would write flawless code every day, and each new release would ship with perfect code. But we live in the real world where people do make mistakes.

Of course, it’s in your best interest to work as hard as you can to keep those mistakes down to a minimum. By keeping track of the average number of errors in each new software release, you can identify areas in your workflow that could be improved. This may help you catch mistakes earlier in the process.

For example, you might realize that a new adding a new tool to your DevOps team’s arsenal can help your release smoother updates every time.

At the very least, tracking this metric provides an easy mechanism to determine whether your team is trending in the right direction, i.e., making fewer errors as time goes on.

4. Code Lines Per Update

The point of writing is to convey a point to your readers. Unless the author is getting paid per-word, writers should state their case in as little words as possible. The question is what day is it today? It’s not do you have any idea as to which 24-hour period we are currently in the middle of?

In the world of software development, the same maxim holds true. You don’t need 100 lines of code when a single line will do the same trick.

Keeping track of code lines per update can help you ensure that you are writing software efficiently. Depending on what your team’s workflows are like, you may be able to identify individual developers who are writing too many lines of code and have the more efficient coders give them a few pointers.

5. Rework Metrics

How many files does your team rework each month?

Developers don’t come cheap. The last thing you want to do is pay them to do the same work over and over again—whether that’s because someone did it incorrectly in the first place or because your team is struggling to communicate effectively.

Tracking rework metrics can help you make sure that the percent of rework your team does each month doesn’t increase in perpetuity. On the flipside, you may also be able to identify what you are doing that is decreasing rework. With that information on hand, you may be able to bake additional efficiencies into your development processes.

6. Frequently Changing Files

Track this metric to determine whether certain files are changing too frequently. If you find out that certain files are changing with each update, you may need to look into the issue a bit.

For example, you can determine why certain files are changing so often. Maybe it’s because developers aren’t sure of the requirements. Maybe it’s because there’s an issue with your testing and QA approach.

Whatever the case may be, this metric can help you add additional efficiencies into your development processes by reducing or eliminating duplicative work and rewriting inefficient code blocks as needed.

7. Root Causes for Late Delivery

As you optimize your release management workflows, everything should get more and more predictable.

Yet nobody can predict the future and nobody’s perfect. So things will invariably not go according to plan every now and again.

Configuration management lets you drill down into the root causes for late delivery.

Fingers crossed that you never run into any errors that slow down your releases. But in the event you do miss some deadlines, you may be able to start detecting a pattern as to why you are unable to meet them.

Armed with that information, you can begin working backward to identify what is causing delays and what you need to do to prevent that from happening in the future.

Are You Ready to Start Using Configuration Management?

Is your development team reaching its full potential and doing its best work? If not, it may be time to get started with configuration management. That way, you’ll be able to delight customers by meeting their expectations while avoiding downtime and increasing profitability.

And the best part? With the right tools in place, configuration management can largely be automated.

To learn more about how your DevOps team can integrate configuration management into their workflows to build better software more efficiently, take a look at Enov8.

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