Systems | Development | Analytics | API | Testing

LLM Testing in 2025: Methods and Strategies

Large Language Models, or LLMs, have become a near-ubiquitous technology in recent years. Promising the ability to generate human-like content with simple and direct prompts, LLMs have been integrated across a diverse array of systems, purposes, and functions, including content generation, image identification and curation, and even heuristics-based performance testing for APIs and other software components.

Using gRPC with Python

Microservices are now the architecture of choice for many developers when crafting cloud-native applications. A microservices application is a collection of loosely coupled services that communicate with each other, enhancing collaboration, maintainability, scalability, and deployment. There are several options for enabling this communication between microservices. When it comes to Python, gRPC and REST are two extremely popular directions to go.

What is a Memory Leak?

Memory leaks happen when a program fails to release memory it no longer needs, and can be a big issue for developers and system administrators alike, as the gradual depletion of available memory often makes for complex troubleshooting and debugging. Given how the consequences of a memory leak can range from decreased system performance to outright crashes, it’s crucial to isolate the root cause of the leak quickly and efficiently.

EP14: Platform Engineering for Architects

In this episode, hosts Sanjiva and Asanka are joined by special guest Daniel Bryant to explore the evolving practice of platform engineering through the lens of software architecture. They discuss why platform engineering should have a product mindset with developers as its primary customers, how platform and software architectures are symbiotic, and why good APIs, abstractions, and automation are essential for success. The conversation also highlights the role of internal developer platforms (IDPs) in enabling efficient and scalable software delivery.

Traffic-Driven Testing: Shift Right With The Ultimate Guide

In the process of developing software, designing and performing testing is a critical aspect of ensuring high software reliability, improving software quality, and deploying strong fit and function. The shift-right testing approach moves testing to later in your production cycle as a way of doing this with more accurate user data and post-production testing practices. Also known as “testing in production,” with shift-right, you test software after it has been deployed.

Traffic-Driven Testing: Shift Right Testing

In the process of developing software, designing and performing testing is a critical aspect of ensuring high software reliability, improving software quality, and deploying strong fit and function. The shift-right testing approach moves testing to later in your production cycle as a way of doing this with more accurate user data and post-production testing practices. Also known as “testing in production,” with shift-right, you test software after it has been deployed.

Kubernetes vs Docker: 7 Key Differences

It’s impossible to learn about containerization without hearing about Docker and Kubernetes. These two tools together dominate the world of containers, both being the de facto standard in what they each do. When you’re first getting started learning about containers, it can be quite a challenge to figure out the differences between these two tools.

DevOps as a Service (DaaS): Transforming Enterprise IT Operations

A software update failure led to one of the most infamous outages of the year: the Crowdstrike Outage. The incident is estimated to have cost Fortune 500 companies more than USD 5 billion. Per the congressional testimony by Crowdstrike’s officials, the downtime wasn’t attributed to a malicious attack but a configuration and software update failure. Incidents like these make us question how we deal with our digital ecosystems - the configurations, the monitoring, the testing, etc.

What is Resilience Testing: The Ultimate Guide

Today’s complex, dynamic applications demand rigorous resilience testing. A common hurdle is accurately mimicking real user behavior. This post discusses a possible solution: production traffic replication (PTR), a technique that captures actual user interactions to enhance chaos testing, and the principle of intentionally introducing failures to evaluate application recovery.