Have some downtime on your hands? Need a distraction? Check out what our authors have been covering this week in our digest below.

QA Metrics: An Introduction and 7 Examples to Help You

The technology industry is becoming more and more competitive with each passing year. Organizations around the world struggle to remain afloat. They employ strategies to improve the quality of their products and services. They adopt test automation to obtain shorter release cycles. However, many companies don’t actively track their progress (or lack thereof) when it comes to quality improvements, which threatens to make the whole effort futile. If we accept that we can’t improve what we don’t measure, then QA metrics become crucial to improving quality in our organizations. Find out more from Carlos Schults on Testim’s blog.

Supporting Privacy Regulations In Non-Production

Every aspect of our daily lives involves the usage of data. Be it our social media, banking account, or even while using an e-commerce site, we use data everywhere. This data may range from our names and contact information to our banking and credit card details. The personal data of a user is quite sensitive. In general, all users expect a company to protect their sensitive data. But there is always a slight chance that the app or service you are using might face a data breach. In that case, the question that comes to mind is how the company or app will keep your data safe. The answer is data privacy regulations. Learn more from Arnab Roy Chowdhury on DataOps’ blog.

Lead Time vs. Cycle Time: What’s the Difference?

A key part of effective agile software team leadership is focusing on the right metrics. There are lots of behaviors that you can measure, but knowing that you’re measuring something doesn’t mean you know what that measurement tells you. It also doesn’t tell you how or when to push to improve your team’s measurements. Two commonly measured metrics are lead time and cycle time. In this post, we’re going to spend some time talking about both of them and how they’re different, how they work together, and what you should learn from measuring them. Eric Boersma can fill you in on Plutora’s blog. 

Top 7 Security Best Practices for APIs

As cybersecurity attacks become more and more common, it’s extremely important to secure your APIs. However, some developers neglect securing their APIs if they believe their APIs are only communicating with the frontend of their programs. There is this misleading perception that a well-secured front end excuses you from paying too much attention to related API security. The truth is that you need to pay equal attention to securing your APIs regardless of whether they communicate with the frontend or the backend of your application. In this post, you’ll learn the top 7 security best practices for APIs. Find out more from Dawid Ziolkowski on Sqreen’s blog.

Organizations today face an uphill battle against cybercrime. Attacks are rising in frequency and sophistication each year, with hackers increasingly targeting vulnerabilities in cloud systems and home networks. As such, executives across the board are abandoning outdated and ineffective cybersecurity policies and embracing new tactics. According to PwC, 96% of executives are shifting their cybersecurity strategy due to COVID-19. This new era of cybersecurity is all about speed and efficiency. In fact, survival depends heavily on real-time threat detection and remediation. Companies can no longer wait several weeks or months to discover vulnerabilities and intruders. As a result, there is an urgent demand for big data cybersecurity. Companies need to use advanced analytics to discover trends and keep pace with cybercriminals. With all this in mind, let’s take a closer look at big data and the critical role it’s playing in cybersecurity. Learn more from Justin Reynolds on Scalyr’s blog. 

Test Data Is Critical: How to Best Generate, Manage, and Use It

We also recently updated a post. When it comes to testing, data is king! In an increasingly digitized world, data is becoming more important for many businesses. However, many people aren’t aware that data plays an important role in testing. Why? Because the best way to test your application is with real data. Of course, you should avoid using production data directly. Instead, use test data. This term refers to the generation of data that comes as close as possible to your production data without revealing any sensitive information. Why does the accuracy and structure of test data matter? Well, it doesn’t make sense to test your software with completely meaningless data. Check out more on Testim’s blog.