Systems | Development | Analytics | API | Testing

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Building Reliable Systems in an Unpredictable World

Can engineers ever guarantee that nothing will break? @Saurabh Shanbhag explains why unexpected failures are always possible in today’s interconnected tech world. The key is to control what you can and collaborate to build resilient systems. Here’s how to approach it: Watch this episode of Test Case Scenario to learn more about building reliable systems.

Perforce's Approach to Open-Source Communities

Perforce has been contributing and working in open source for decades now. We understand that open source is the linchpin for technology that supports businesses today. Our approach to open source is not unique to the industry at large or a company of our size (we have around 1,700 employees and 800 are on my team), but questions of our approach to open source became much more visible when we acquired Puppet – which has a really dedicated open-source community and a long history with open source.

The Future of Financial Services Testing is Automated

In the fast-paced, highly regulated world of financial services, delivering exceptional service isn’t just about speed – it’s about managing immense complexity. As financial institutions face increasing pressure to innovate, they also carry the weight of maintaining strict security and compliance standards. Test automation is more than just a tool; it empowers teams to modernize with confidence, knowing they can meet both quality expectations and regulatory demands.

Subdomain takeover: ignore this vulnerability at your peril

The Domain Name System (DNS) is often described as the address book of the Internet. A and AAAA records map a human-friendly hostname like honeybadger.io to some machine-friendly IP address like 104.198.14.52. Other types of DNS records also exist; in particular, CNAME records are records that map a hostname to some other hostname, thereby delegating IP resolution to the latter.

Ways to Use Mock Services in Software Development

Mocking APIs is a popular practice in software development. An increasing number of developers are reaping the benefits and no longer using their valuable time to spin up duplicate resources. Many mock services do not require account creation, making them easy to use and privacy-friendly. In the rest of this article, we explain what mock APIs are, when you should think about using them, and what solutions are available within the open-source and proprietary markets.
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Simplifying AWS Testing: A Guide to AWS SDK Mock

Testing AWS services is an essential step in creating robust cloud applications. However, directly interacting with AWS during testing can be complicated, time-consuming, and expensive. The AWS SDK Mock is a JavaScript library designed to simplify this process by allowing developers to mock AWS SDK methods, making it easier to simulate AWS service interactions in a controlled environment. Primarily used with AWS SDK v2, AWS SDK Mock integrates with Sinon.js to mock AWS services like S3, SNS, and DynamoDB.

Kubernetes Load Testing: How JMeter and Speedscale Compare

At some point, your development team may be considering implementing load testing (also known as stress testing) as part of your software testing process. Load testing validates that your web app is able to withstand a large number of simultaneous users, decreasing the chance that any traffic spikes will bring down your services once deployed. These stress tests can be highly granular, giving you the opportunity to test run virtually unlimited strategies before they are set into the wild.

Episode 11: The future of data lakes: Open table formats, metadata and AI | AWS

Paul Meighan, Director of Product Management at AWS, shares how enterprises are increasingly looking for ways to integrate more data sources in their environment — especially with data lakes. From turning S3 buckets into databases to establishing better metadata layers, Meighan explores the rapid evolution of data lakes alongside data warehouses. He also explains the pivotal role AI, ML and GenAI workloads and applications will play in large metadata environments, driving innovative analytics and business insights.