Category Archives: TEM

Conflict

Avoiding Test Environment Conflict

I. Introduction

Test environment conflict is a common challenge faced by organizations during software development. It occurs when multiple release trains or testing teams are trying to access a shared test environment simultaneously, leading to conflicting actions and potential issues such as broken test cases, incorrect data, and delays in testing.

The importance of test environments in the software development process cannot be overstated, as they provide a crucial step in ensuring the functionality and reliability of applications before they are released to production.

In this post, we will discuss the causes of test environment conflict, its consequences, and strategies for avoiding it to ensure a smooth and efficient software development process.

II. Causes of Test Environment Conflict

A. Multiple teams accessing a shared test environment – Shared test environments are often used by multiple teams within the same organization or across different organizations, allowing for a centralized management of resources and reducing the cost of setting up separate environments for each team. However, this can lead to conflicting actions when multiple teams are trying to access the same environment simultaneously.

B. Lack of proper planning and management processes – Proper planning and management processes are crucial in avoiding test environment conflict. Without these processes in place, there is a risk of conflicting actions and potential issues such as incorrect data and broken test cases.

C. Inconsistent communication between teams – Communication is key in avoiding test environment conflict. When teams are not communicating effectively, there is a risk of conflicting actions, duplicated work, and other issues that can slow down the software development process. Inconsistent communication between teams can lead to misunderstandings and miscommunications, causing test environment conflict to occur.

III. Consequences of Test Environment Conflict

A. Delays in testing – When test environment conflict occurs, it can cause delays in testing as teams try to resolve the issues caused by conflicting actions. This can slow down the entire software development process and impact the release schedule.

B. Loss of data – Conflicting actions in a shared test environment can result in the loss of data, making it difficult to accurately test applications. This can have a negative impact on the quality of the applications being developed.

C. Issues with reproducibility – Conflicting actions in the test environment can make it difficult to reproduce test results, which is crucial for debugging and fixing issues. This can further delay the software development process and impact the quality of the final product.

D. Incorrect test results – When test environment conflict occurs, it can lead to incorrect test results, which can result in incorrect conclusions about the functionality of the applications being tested. This can have a negative impact on the overall quality of the applications and the credibility of the testing process.

IV. Strategies for Avoiding Test Environment Conflict

A. Implement proper planning and management processes as part of your Product Lifecycle Management (PLM)

  1. Reserve the environment for each team – Designating separate test environments for each team can prevent conflicting actions and ensure that each team has the resources they need to test their applications effectively.
  2. Set up proper change control procedures – Establishing change control procedures helps ensure that changes to the test environment are well managed, preventing conflicting actions and ensuring the accuracy of test results.
  3. Create a clear communication plan between teams – Establishing clear communication channels between teams can help prevent misunderstandings and conflicting actions in the test environment.

B. Use test environment management tools

  1. Automate and simplify management of shared test environments – Utilizing test environment management tools can automate many manual tasks and simplify the management of shared test environments, reducing the risk of conflicting actions. One such tool is Enov8 Environment Manager.
  2. Streamline communication and collaboration between teams – These tools can also provide a centralized platform for communication and collaboration between teams, reducing the risk of miscommunications and conflicting actions.
  3. Ensure consistent access to the test environment – Test environment management tools can also help ensure consistent access to the test environment for all teams, reducing the risk of conflicting actions and ensuring that each team has the resources they need to test effectively.

C. Ensure Environments are Readily Available

  1. Establish Dedicated Test Environments – To prevent conflicts, assign dedicated test environments to significant projects and phases of the Software Lifecycle. For continuous delivery, projects should always have dedicated development and test environments.
  2. Enable On-demand Test Environments – Additionally, ensure the ability to quickly spin up and down environments, using automation, based on necessary demand.

V. In Conclusion

In conclusion, test environment conflict can have a negative impact on the software development process, resulting in delays, loss of data, incorrect test results, and other issues. To avoid these issues, teams should implement proper planning and management processes and make use of test environment management tools. With effective communication and collaboration between teams as well as automated process management, teams can ensure a smoother testing process and better quality applications.

Dev-Environment

Why Development Environments?

Why Development Environments

A development environment, like a test environment, is a critical component of any software development lifecycle, providing developers with the space and tools they need to implement and test application features.

This type of test environment may include a variety of tools and resources, such as testing frameworks, code repositories,test data, debuggers, and more. It is important for developers to carefully consider their needs when creating a development environment, as this will impact both the quality and efficiency of their work.

Some key considerations to keep in mind when designing a development environment include selecting appropriate tools, setting up robust processes and procedures, and optimizing communication among team members.

Additionally, it is important to ensure that your development environment not only supports your current project needs but can also grow with you over time. By taking these factors into account, you can create a development environment that will help to maximize the success of your software projects.

In this article, we will first explore what a development environment is, its purpose, and some examples. After that, we’ll go more in-depth and discover the best practices for creating a good dev environment.

Development Environment: The Basics

Why do we need a Development Environment?

Development environments let software developers create, run, and test their application code in a way that simulations real-world scenarios adequately. If that’s still too vague for you, here are some specific examples.

There are a number of key benefits to using a development environment, including increased user experience, reduced costs, and improved safety and privacy.

For example, by interacting with simulated dependencies instead of the real services, developers can avoid creating problems in the production app and incurring unnecessary costs. Additionally, working with real services may raise security or privacy concerns that can be avoided by using a development environment. Ultimately, utilizing a development environment helps software developers create better code more efficiently and safely.

How do we Implement a Development Environment?

There are a number of factors to consider when creating a development environment, including the size and complexity of your team, the maturity of your infrastructure, and the dependencies that your code relies on.

At its most basic level, a development environment is simply the developer’s machine itself. However, with advances in technologies like Docker, it has become easier to create self-contained and reproducible environments that can be activated by running a single command.

In some cases, however, this may not be sufficient for meeting all of your needs. In these situations, it might make sense to leverage existing infrastructures or resources in order to create development environments for engineers. For example, you may choose to create mock APIs or databases to avoid accessing real systems, or use sample data that has been anonymized to protect sensitive information.

Ultimately, the key to successfully implementing a development environment is to consider all of your requirements and find the right balance between flexibility and control. By taking these factors into account, you can create an environment that will enable your team to be more effective and efficient in their work.

Development Environment: A Few Best Practices

We’ve just covered the fundamentals of test environments. You’ve learned what they are, why they exist, and how to implement one. Now, let’s walk through some best practices to keep in mind when implementing a dev environment.

Your Development Environment Should Be Fast

One of the key best practices for a successful development environment is to ensure that it is fast and efficient. This involves using high-performance hardware, as well as optimizing your software and coding practices to maximize performance.

Your Development Environment Should Offer Isolation

Additionally, it is important to ensure that your development environment offers adequate isolation from other systems or processes in order to give developers the freedom they need to experiment and explore while minimizing the risk of errors or bugs in production.

Your Development Environment Should Be Realistic, But Not That Much

The phrase “It works on my machine!” is often used in software development, and for good reason. It can be frustating when the code you write doesn’t work when it’s transferred to the production server. This happens because the development environments and production environments are not identical copies of each other.

For example, my front-end code relies on an Apache version, or configuration, that has been activated in my developer test bed, however still needs to be deployed on to the target server. Consequently,the code doesn’t run correctly

By keeping the environments close to each other, for example same versions of the operating system and software stack, we are able to fix this problem. Containers, as referenced before, help us reach that goal.

However we should also appreciate it can’t, and shouldnt normally be an exact copy. For example, unlike production, you dont want customer sensitive data. In short, your dev environment should only be as realistic as it needs to be for developers to run their code safely and predictably.

Your Development Environment Should Be Compliant

Finally, it is important to keep your development environment as realistic as possible while still maintaining compliance with various regulatory requirements around user data protection and security.

Overall, creating an optimal dev environment requires careful planning and attention to detail in order to help developers work efficiently while also ensuring a reliable and secure end product.

When it comes to data there are ultimately two solutions: synthetic data generation or production data cloning (plus data masking methods). While both come

Conclusion

Like test environments, development (or dev) environments are an essential part of modern software development. All of these environments working together, and when done properly allow organizations to deliver high-quality software quickly.

Overall, creating an effective dev environment requires careful planning and attention to detail in order to help developers work efficiently while also ensuring a high quality end product.

Whether through containerization, synthetic data generation or production cloning, it is important to carefully consider the various requirements of your development and software testing process in order to create a productive and compliant environment that can support your team’s work. By taking these factors into account, you can ensure that your development efforts are as efficient and successful as possible.

SRE-Warning

What is Site Reliability Engineering?

An Introduction to SRE

SRE or site reliability engineering has become increasingly essential as businesses confront an ever-growing IT infrastructure that manages cloud-native services. One of the reasons is that the way software development and deployment teams operate has altered considerably.

DevOps principles, which include continuous integration and deployment, have fueled the adoption of DevOps concepts and a transition from departmental silos to a new engineering culture in an ever-changing world. This way of thinking endorses and lives the “you build it, you run it” mentality.

Site reliability engineers are hired by businesses to keep their new IT architecture stable and enhance their competitive advantage. SREs use a variety of engineering principles to assist product engineering teams in optimizing their processes. The team’s fundamental objective is to develop highly dependable software systems by analyzing the current infrastructure and finding methods to improve it with software solutions.

In this post, you’ll discover more about the function and advantages of site reliability engineering, the fundamental principles utilized in SRE, as well as the distinction between a site reliability engineer and a platform engineer.

What is Site Reliability Engineering?

Site reliability engineering, also known as SRE, is a software engineering method that aids in the management of large systems via code. It’s the job of a site reliability engineer to develop a stable infrastructure and efficient engineering processes by following SRE standards. This also includes the use of monitoring and improvement tools as well as metrics.

Even though SRE appears to be a relatively new position in the world of cloud-native application engineering and management, it has been around even longer than DevOps – the phenomenon that successfully connected software development and IT operations.

In fact, it was Google that entrusted its software engineers to make large-scale sites more dependable, efficient, and scalable through the use of automated solutions. The procedures that Google’s engineers began experimenting with in 2003 are now part of the full-fledged IT domain.

Site reliability engineering, in a sense, takes on the responsibilities that operations teams previously performed. However, operational difficulties are addressed with an engineering approach rather than a manual one.

With the use of sophisticated software and Site/Environment Management tools, SREs may establish a link between development and operations to create an IT infrastructure that is dependable and allows for easy deployment of new services and features.

Site reliability engineers are especially important when a firm switches from a traditional IT approach to a cloud-native one. Next, discover more about the responsibilities of a site reliability engineer and what sort of talents are required in this line of work.

What does a Site Reliability Engineer (SRE) do?

A site reliability engineer is someone who has a background in software creation as well as significant operations and business intelligence expertise. All are required to deal with technical issues using code. While DevOps focuses on automating IT operations, SRE teams focus more on planning and design.

They track operations in production, and ideally in non-production (shifting SRE Left), and study their performance to find areas for improvement. Their comments also assist them in predicting the cost of outages and preparing for contingencies.

SRE Engineers will divide their time between operations and the development of systems and software. On-call duties include updating run sheets, tools, and documentation to ensure that engineering teams are ready for the next emergency. They generally conduct deep post-incident interviews to figure out what’s working and what isn’t after an incident occurs.

This is how they acquire important “tribal wisdom.” Because they engage in software development, support, and IT development, this information is no longer compartmentalized and can be put to use to build more reliable systems.

A site reliability engineer’s work is also spent developing and enabling services that improve operations for IT and support personnel. This might imply creating a new tool to repair the flaws in current software delivery or incident management.

And last but not least, SREs are in charge of determining whether new features can be added and when, utilizing the aid of service-level agreements (SLAs), service-level indicators (SLIs), and service-level objectives (SLOs).

Learn more about SRE key performance indicators SLA, SLI, and SLO in the following section, as well as how they are used in site reliability engineering.

The difference between SLOs, SLIs, and SLAs

Site reliability engineers employ three metrics to monitor and improve the performance of IT systems: They write service-level agreements (SLAs), service-level indicators (SLIs), and service-level objectives (SLOs). These related service level measurements not only assist firms in building a more dependable system but also increase consumer confidence.

Let us define each of these key SRE metrics in more detail.

SLI Metric

SLI stands for the service-level indicator. An SLI measures the qualities of service, to provide input for a service provider’s objective.

  • Referencing the SRE Handbook, Google defines it as “a carefully defined quantitative measure of some aspect of the level of service that is provided.”

The analysis of behavioral data is a critical part of any successful customer experience optimization program. Four golden signals are the most frequent SLIs: latency, traffic, error rate, and saturation.

When SRE teams build SLIs to assess a service, they usually use two stages.

  1. They determine the SLIs that will directly impact the customers.
  2. They determine which SLIs influence the availability or latency or performance of the service.

SRE SLI Formula

The formula used to calculate ones SLIs is:

  • SLI = (Good Events * 100) / Valid Events

Note: An SLI value of 100 is optimal, whereas a drop to 0 means that a system is broken.

It’s critical to build SLIs that are appropriate for the user’s experience. This implies that a single SLI is not capable of capturing the whole customer experience as a typical user may be concerned with more than one thing while using the service. Simultaneously, creating SLIs for every imaginable statistic is not desirable since you would lose focus on what matters most.

Site reliability engineers generally focus on the most pressing problems as users go through a system. Once the SLIs have been established, an SRE connects them to SLOs, which are important threshold values defining the availability and quality of service.

SLO Metric

The SLO or service level objective is used to assess the quality of a service’s reliability or performance criteria.

  • Referencing the SRE Handbook, Google says that they “specify a target level for the reliability of your service” and “because SLOs are key to making data-driven decisions about reliability, they’re at the core of SRE practices.”

Unlike SLIs which are product-centric, SLOs are customer-centric.

Their relationship can be defined as follows:

  • SLO (Lower bound) <= SLI <= SLO (Upper bound SLO)

However, establishing appropriate SLOs is a difficult process. Targets should generally be established based on historical system performance rather than current conditions. And targets should be realistic, as opposed to too ambitious.

Tip! Absolute values are not required. It is often better to identify a “realistic” range based on historical data.

SLOs should be viewed as a unifying mechanism that fosters a cohesive language and shared objectives across various departments. And you’re considerably more likely to succeed if all key stakeholders are on board.

However, many firms are preoccupied with product innovation and fail to recognize the link between business success and dependability. Siloed data and the mistaken belief that once standards have been established, they don’t need to be re-examined or adjusted are two frequent stumbling blocks.

SLA Metric

A service-level agreement, or SLLA, is a contract that specifies the level of service provided by a platform. Similar to SLOs, service levels are a client-focused measure.

  • Referencing the SRE Handbook, Google says, an SLA is defined as “an explicit or implicit contract with your users that includes consequences of meeting (or missing) the SLOs they contain.”

An SLA is triggered as soon as an SLO is “breached”. In most cases, you should anticipate fines and financial repercussions if you do not fulfill the requirements of the SLA. If your firm breaches a term established in the SLA, it generally has to repay its clients.

Service-level agreements (SLA) provide transparency and trust between the company and its consumers. They’re similar to SLOs, but instead of being used by a business, they apply to external rather than internal activities. SLAs are less conservative than SLOs, implying that the value of reliability is always somewhat lower than the historical average of an availability SLO. This can be seen as a safety precaution if the average is set too high because there were just a few incidents in the past.

In Conclusion

Site reliability engineering is a critical process for ensuring that websites and online services are available and functioning properly. By establishing key metrics and thresholds, SREs can prevent outages and disruptions in service. SLAs, SLOs, and SLIs are three important tools that SREs use to measure and manage system performance. To be successful, SREs must have a deep understanding of these metrics and how they relate to one another.