Operations | Monitoring | ITSM | DevOps | Cloud

Compliant Test Data Used to Be Hard. It Isn't Anymore.

This is a guest post from Saskia Parks. If you're exploring test data management (TDM) solutions, you probably know your current practices aren't ideal, but you're skeptical investing in a solution is worth the budget and effort. We hear the same concerns. The perception is that proper TDM is expensive, complicated, and takes months of painful implementation.

AWS Elastic Beanstalk 101: A Beginner's Guide To App Deployment On AWS

Imagine you want to launch an application without first building and managing the servers that run it. You write the code, pick how it should run, and then let a platform take care of the rest. That’s the core promise of AWS Elastic Beanstalk. In this snackable guide, you’ll understand AWS Elastic Beanstalk well enough to decide if it belongs in your AWS architecture.

Introducing "Explain Flame Graph": Stop Fighting Fires and Start Explaining Them

In a modern observability deployment, it’s simple to get data that helps you understand where your system is failing. However, when we try to understand why, the answer is often buried beneath a mound of stack traces. For many developers, attempting to interpret a flame graph by manually calculating self-time (the resources consumed by the function itself) versus child-frame latency (the time spent waiting on called sub-functions) is both confusing and time-consuming.

16 new integrations - powered by AIready Low Code Plugins

Today marks a big milestone in our mission to bring more data, more context, and more visibility into a single, unified view. We’re excited to announce 16 brand‑new integrations, extending the range of data sources you can connect with just a few clicks. But the integrations themselves are only half the story.

A Technical Guide to Controls Engineering

The modern world runs on mission-critical software. It moves our money, drives our cars, diagnoses our illnesses, and fundamentally improves our lives. But, organizations building this critical software face a paradox: they need to move fast to stay competitive, but they also need rigorous governance to manage risk. This has created a lot of tension in regulated industries.

How to Remove Watermark from AI Generated Images (Midjourney, DALL·E & Canva)

AI image tools have made it ridiculously easy to create artwork, mockups, social media visuals, and even product photography. But many platforms add watermarks - especially on free plans or previews. If you've downloaded an image and realized there's a logo, text overlay, or semi-transparent branding across it, you're not alone. Let's go through what actually works when it comes to removing watermarks from AI-generated images - and what usually makes things worse.

The Operational Case for Stablecoins: Why More Teams Convert Crypto Into "Working Capital"

In operations, volatility is rarely a feature. Finance teams care about predictability: how much cash is available, when it arrives, what it will be worth next week, and whether it can be moved quickly to pay suppliers or contractors. Crypto can be useful for moving value across borders or between platforms, but it also introduces a stubborn problem for business workflows: prices swing, sometimes sharply, and that swing can turn a straightforward payment plan into a risk management exercise.

Ruby vs Rust: Choosing the Right Language for Your Next Project

Ruby is a high-level, interpreted programming language designed for quick, simple coding and development, and is often used by teams for web backends and APIs, as well as for other projects where features need to be deployed quickly. Ruby powers 6.6% of all websites with a known server-side programming language. Rust is a compiled systems programming language focused on speed and memory safety, chosen for services, infrastructure, and software that require stability and efficiency.

Scaling Infrastructure Teams: The Increasing Need for Rust Engineers

The Infrastructure teams have had to continuously improve current systems to make them faster, safer, and more reliable. With the growth of cloud services, the complexity of applications, and the demand for low-latency processing, engineering teams still need the best tools and languages to build these systems. The traditional languages that have been used for decades to power system-level development, i.e., C, C++, and Java, have long been the standard. But as software system complexity becomes unsustainable, the factors that limit safety, memory management, and concurrency are becoming increasingly obvious.