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Growth is painful. The transition from a small project with a tight-knit team and straightforward processes needs to be strategic and fast. Because your customers won't wait around for you to figure out your next steps. You need to learn to handle more people, more tasks, and the rising user expectations quickly. Under that pressure, prioritizing speed over quality is common. And so you enter the danger zone. The QA process is rushed. Coverage is unbalanced or lacking. Testing steps are overlooked. And while you're chasing speedier releases, developers waste time on hotfixes and false issues, product quality dwindles down, and clients quietly churn. How to resolve and prevent this? By working with a specialist who brings structure, quality ownership, and visibility. Today, we discuss QA Lead responsibilities and the value of this expert for your business. Why QA Team Lead Roles and Responsibilities Matter? QA Lead is somewhat of an exception. They are both the jack and the master of ...

We like to marvel at how technology keeps changing. Yet, some things stay the same. Some teams struggle with an avalanche of regression tests. Some with the complexities of scaling. Some with how difficult hiring talent has become. And the lucky ones grapple with all of them and more. The progress of tech creates new challenges. It's like the great filter: to survive and thrive, you must overcome the barriers in front of you. Today, we discuss a solution that can help you with that — automated test case generation. What Is Automated Test Case Generation? Automated test case generation (ATCG) is the use of tools and algorithms to create test cases. With the traditional approach, specialists go through specs, user stories, requirements, etc. Then, they identify relevant test scenarios. And finally, QA engineers create test cases themselves, writing them by hand. When done manually, this process can take around ten minutes. But per one test. So, this adds up significantly. And given t...

The cost of poor QA is high. Critical bugs in production, negative client feedback, hotfixes that eat away at dev time... That's just scratching the surface. If you've ever dealt with that, you know the value of root cause analysis in refining your team, product, and business. But you must also know how demanding it is. Luckily for everyone, AI found its way into this discipline as well. And it made it simpler, faster, and more precise, saving your resources. Today, we break down what AI-powered root cause analysis is, how it works, and why it matters for your business. What Is AI Root Cause Analysis? AI-based root cause analysis is the use of artificial intelligence to handle data work during RCA. You may have expected a definition that made it sound like a silver bullet. Well, don't be disappointed. Most of RCA is gathering, cleaning, organizing, and analyzing data. And AI is perfect for handling that. AI can quickly sift through massive log files or monitoring data. It can pinpo...

A critical bug in production isn't your greatest nemesis. Events that created it are. If you don't want to waste money, resources, and your team's precious time on treating just the symptoms, you should develop expertise in root cause analysis techniques. Because they transform mistakes into lessons that make your product better. What Is Root Cause Analysis? Root cause analysis (RCA) is a problem-solving method that aims to identify the reason for an issue. Its defining characteristic is that it doesn't treat the bug itself as an error. Only as a symptom of something bigger. For example, a software bug doesn't necessarily mean that someone failed. It can be due to poor code coverage, incorrect prioritization, faulty testing processes, or everything combined. An important aspect of techniques for root cause analysis is that they avoid assigning blame. They also view errors as growth opportunities. For instance, if a junior QA engineer missed a test, you should upskill them. If a devel...

Automating business workflows is a key competitive advantage. To establish a fine-working automated system, a CRM solution is not just a choice, but a necessity. Growth exposes process gaps; the next necessary step is to standardize them in a CRM. However, the "stumbling block" for making the right decision is data migration. This step has stopped many businesses on their path to automation because the data was messy, inconsistent, or incomplete. According to Forbes, only 36 % of data migration projects succeed, meaning 64 % fail in meeting objectives or staying within budget and schedule. But we are here to help you! Today, our team, together with CRMiUM experts, wants to share practical advice on migrating data into a new CRM system. This post will highlight how good planning ensures that no records are lost and your company can start using the CRM with confidence. Common Pitfalls in CRM Data Migration Moving to a new CRM promises clarity and automation of workflows, yet data migra...

To get to the treasure room where cost reduction, refined flexibility, and greater innovation reside, you first have to pass the boss fight: cloud migration. This beast guards an important entrance. Behind it, you'll find endless business opportunities. And to get through it, you'll need a confident cloud migration testing strategy---one that prevents disrupted operations, compromised data, and product delivery slowdown. Today, we discuss why cloud migration testing is much more complex than one might think and how to do it to set yourself up for success. The Risks of "Improvised" Cloud Testing Migration Imagine taking your entire house and throwing it into the sea. That's how going cloud feels without proper software testing services. There are no modifications to the structure, so it can sit atop liquid. No waterproofing. And gas pipes that don't link to the mainland... Your house is where you wanted it to be. But it doesn't function as it should. Common Issues of Inadequate Cloud M...

There can be no good without the bad. Microservices architecture makes development easier by breaking down apps into smaller pieces. But it also greatly complicates unifying them into a functioning one. Such tradeoffs are common in IT. But there should never be compromises regarding quality. Because it's the only aspect that has no mentioned duality—a subpar product is just a subpar product. That's why today, we'll learn how to do integration testing in microservices without overexerting your team and budget while securing profit and happy customers. What Is Microservices Integration Testing? Integration testing in microservices is the process of checking how different services work together. You're ensuring that they operate properly when combined: exchanging data, following expected workflows, handling errors, etc. Let's take a look at a brief integration testing microservices example to understand this better. In an e-commerce system, integration testing would check how the orde...

Much like ogres and onions, IoT devices have layers. So working with them isn't for the weak. Because they combine physical components, embedded software, network connectivity, cloud services, and apps. And skipping or overlooking just one layer can cause everything to spiral. Thus, high-functioning IoT testing involves device testing across all these layers to ensure a stable, secure, and user-ready product. Today, we'll learn how to do it. Understanding IoT Device Testing Scope The scope of IoT device testing goes far beyond checking the physical hardware. Each device is part of a layered system that includes firmware, companion mobile apps, APIs, and cloud services. These layers don't just coexist. They constantly exchange data and commands, which means a flaw in one area can compromise the entire experience. Firmware underpins the device's core functions. If it isn't tested thoroughly, crashes or faulty readings are a given. They can result in high return rates, warranty claims...

Teams trying to create a memorable product are more likely to face development issues. Increased workload that's getting uncomfortable. Gaps in business continuity that overwhelm. Difficulties in finding the right experts that make you question the future. These are rare for crews that don't really bother. They can just ignore the strain and be fine with settling for less. That's why, however odd it may sound, we love when clients come to us with such troubles. It means they care. They care about their team members, product quality, and continuous progress. Today, we discuss API integration testing best practices that help you prevent and confidently deal with SDLC hurdles. What Is API Integration Testing? API integration testing is the process of checking how different APIs work together and interact with other parts of a system. The focus is on making sure that components collaborate as intended when combined. Allow us to get a tad more technical. APIs define how your syste...