Operations | Monitoring | ITSM | DevOps | Cloud

You’ve made it to Senior engineer. Now what? You’re now staring at the next level, Staff typically, sometimes Principal, or whatever your company calls it. The path feels murky. Your manager gives you feedback like “show more technical leadership” or “think bigger picture”, but what does that actually mean day-to-day? I’ve been there. I’ve also been on the other side, helping engineers grow through whatever explicit (or implicit) levels a company has.

"There are only two hard things in Computer Science: cache invalidation and naming things."—Phil Karlton In the age of increasingly frequent deploys, edge caching, and Jamstack adoption, caching plays a key role across the software delivery life cycle. In build and CI pipelines, caching compiled assets or dependencies helps reduce compute costs, speed up job runtimes, and lower the environmental impact (regarding energy usage) of repeated builds.

MongoDB is a popular NoSQL database used by many modern web applications. Once your web application is up and running, you might find you need to monitor the application data for operational purposes. For example, you may need to report on user sign-ups, or monitor for problems like invalid data. SquaredUp is an easy-to-use dashboard that plugs directly into your MongoDB database to visualize and monitor your data.

Effective alerting is the backbone of any observability strategy. But as your systems grow, managing hundreds or even thousands of rules can become a significant challenge. And when something goes wrong, the last thing you want is to fight with your tooling. That’s why we’re thrilled to announce the launch of our brand new alert rules list page, which we built to provide a faster, more intuitive, and scalable experience for teams of all sizes!

From optimizing supply chains to personalizing customer experiences, artificial intelligence and machine learning models are no longer statistics-based revenue initiatives; they’re foundational to modern business strategy. Organizations are pouring resources into developing and deploying AI, driven by the promise of unprecedented efficiency, insight, and competitive advantage. Yet, beneath this surging wave of innovation lies a growing tension: the Innovation vs. Control Syndrome.

Many, many years ago, I was a computer science major at the University of Illinois, hoping someday I’d be able to write code for a living. I started my career in QA hoping to learn the ins and outs of software development. But it turns out I wasn’t very good at coding. I was just good enough to get a role as a sales engineer, where all I had to do was write code that could hold together for 30 minutes in a demo.

Zoho CRM integration is a game-changer for businesses that want to convert raw customer data into powerful, crystal-clear insights. In an era where every click, call, and customer interaction generates valuable data, the ability to instantly connect your CRM with analytics and data visualization platforms can make the difference between thriving and merely surviving. Imagine having a live, visual pulse on your sales pipeline, customer behaviors, and revenue forecast all in one place.

Transaction logs play a crucial role in database management, especially in SQL Server databases. These logs meticulously record every transaction and the corresponding changes made to the database. Such detailed tracking is indispensable for identifying issues and restoring the database to a specific state and time if any failures occur. In SQL Server, every database includes a transaction log, a feature that is always enabled and cannot be turned off.

Without site context, your 5-minute fix becomes a 30-minute hunt through spreadsheets and Slack channels while users wait. This isn’t just inconvenient—it’s expensive. Every minute of downtime costs your business, and every minute spent playing IP detective is a minute not spent solving the actual problem. As networks scale across cloud, hybrid, and on-premises environments, this lack of infrastructure context creates real operational pain for your team.

When cloud costs spike, compute is often the culprit. Using Azure Spot Instances could cut your compute costs by up to 90%. But Spot VMs come with trade-offs, including unpredictable evictions and capacity constraints. And that makes them tricky to use without the right strategy and visibility. In this guide, we will share how to make them work for you.