I’ll be the first to admit one of my weaknesses is public speaking. I spend hours before a training session, online seminar, or live event rehearsing exactly what I want to say and how I want to say it. But all my time spent practicing an engaging presentation only mildly prepares me for the moment I’m in front of others and it’s my time to speak.

Have you ever deployed a new application that ran fine at first, then slowed to crawl as more and more data was added? Or tried to run a report that took minutes or even hours to come back? Database performance is a frequent bottleneck for many applications, and in this post you’ll learn about a critical aspect of database performance—indexes.

Azure Functions are great for running bits of processing on a trigger without having to worry about hosting. Recently, I needed to debug an Azure Function—I needed to hunt down a particularly evasive bug that wasn’t showing up in the unit and integration tests. As it turns out, debugging an Azure Function isn’t as trivial as simply running the debugger in Visual Studio. Instead, it requires some setup to replicate the environment and configuration typically available in Azure.

By continuously running a well-built general-purpose database performance monitoring facility, organizations can gain constant visibility into the availability and responsiveness of their databases and database management systems (DBMSs). When such a tool is equipped with analytics to compare historical metrics against current values, administrators can immediately understand how current values and behaviors stack up against prior averages and typical baselines.

The public cloud has greatly increased the flexibility of businesses everywhere. Need another petabyte of storage? You’re but a few mouse clicks or a couple lines of code away from allocating all those disks with effectively no lead time. At the same time, it makes it easy for business units, a functional organization, or a disgruntled vice president with a corporate card—who may be frustrated with your IT for various reasons.

Poor application performance, besides being a sign of potential problems, is a strong predictor of unhappy users—and unhappy users are likely to become former customers. So software organizations are always searching for ways to improve the performance of their applications. One of the most effective of such ways to improve performance is obtaining visibility of your app’s behavior—which is something that can be achieved through monitoring.

Businesses both small and large require agility in how they handle device firmware and network configurations. For large networks especially, manual monitoring and change implementation can be inefficient. As such, more and more IT departments turn to automated network configuration management tools with bulk change capabilities.

Microservice architectures are everywhere these days. Even internal enterprise applications—which have typically been structured as self-contained monoliths—are now being designed using a microservices architecture. There are definite advantages to a microservices architecture. Breaking an application into discrete, independent chunks—basically mini apps—gives you enormous flexibility. But this flexibility dramatically increases complexity, especially when things go wrong.

One of the most common questions database professionals are asked by their systems and virtual machine (VM) administrators is “Why does the database server need so much memory?” You’ll get a more detailed answer to that question later in this post, but it’s important to understand a database engine is almost like a server within a server.