Operations | Monitoring | ITSM | DevOps | Cloud

When a disaster occurs, the ability to successfully restore SQL Server databases is fundamental for avoiding data loss. It’s not enough to rely on hardware and software technologies to replicate data because these technologies can go wrong or there can be multiple failures during a disaster, meaning you have to rely on backups to recover. SQL Server allows multiple types of backups, and a multitude of options to use with those backups.

Testing is one of those activities that if not exhaustive will not have its complete impact on your software development process. Oftentimes developers are only concerned about testing the application layer of the system (a.k.a the codebase) and ignore testing the data layer (the database) which is also as important as testing the code itself.

Storage is one of the most critical components for any relational database management system, and getting the right storage configuration affects reliability, availability, and performance. When it comes to SQL Server storage best practices, choosing between storage hardware options has changed significantly over the last decade, but that doesn’t necessarily make choosing the correct storage options for SQL Server any easier.

Every year, the Accelerate State of DevOps Report examines the capabilities and practices that drive software delivery, operational, and organizational performance. The 2021 report from the DevOps Research and Assessment (DORA) team at Google Cloud has now been published and provides highlights from seven years of research and data from more than 32,000 professionals worldwide. So what are those highlights? Where should IT teams be focusing their efforts on their journey to DevOps?

Redis is a simple – but very well optimized – key-value open source database that is widely used in cloud-native applications. In this article, you will learn how to monitor Redis with Prometheus, and the most important metrics you should be looking at. Despite its simplicity, Redis has become a key component of many Kubernetes and cloud applications. As a result, performance issues or problems with its resources can cause other components of the application to fail.

I am currently trialing pgmetrics and pgDash for monitoring PostgreSQL databases. Here are my notes on it. pgmetrics is a command-line tool you point at a PostgreSQL cluster and it spits out statistics and diagnostics in a text or JSON format. It is a standalone binary written in Go, and it is open source. Here is a sample pgmetrics report. Rapidloop, the company that develops pgmetrics, also runs pgDash – a web service that collects reports generated by pgmetrics and displays them in a web UI.