Operations | Monitoring | ITSM | DevOps | Cloud

For DevOps teams managing mission-critical databases, SQL Server observability is a fundamental capability that provides comprehensive insight into database performance and health. Effective observability practices enable teams to identify potential issues before they impact end users and provide the context necessary to resolve problems efficiently. SQL Server observability involves collecting and analyzing metrics, logs, and traces to build a complete picture of database behavior.

Scalable systems thrive on schema clarity—without it, you pay in rework. That’s why 96% of engineers now use visual tools, particularly database diagram tools, to map and manage their databases. Diagramming tools bring structure to complexity. They surface design flaws early, improve collaboration across teams, and turn undocumented systems into shared infrastructure. These advantages are fueling widespread adoption.

These days, information has enormous power. If you have access to sensitive data, you can do anything with it. It all depends on your imagination. As we know, all data is stored in databases. The reputation, efficiency, and profitability of many companies often depend on the private information they collect and store in databases. One of the most dangerous things that can happen to your database is a data breach.

Frameworks evolve, libraries change, and APIs get rewritten. But your ORM decision? That one sticks—it shapes your architecture, guides how your team writes queries, and affects how painful refactors become later on. In.NET, this choice often narrows to Dapper and NHibernate—two trusted tools with fundamentally different approaches. NHibernate offers deep abstraction, rich mappings, and built-in caching, while Dapper gives you raw speed, total SQL control, and zero overhead.

In.NET, data access has evolved, but finding the right tool still comes down to control vs. convenience. You have to decide: do you prefer to write every query or move faster with something easier to maintain? Can you manage the boilerplate, or would you rather work with leaner syntax? For many.NET developers, the answers point to one of two popular tools—ADO.NET or Dapper. ADO.NET gives you complete control but with boilerplate and manual overhead.

Prometheus Monitoring: Instant Queries and Range Queries Explained This discussion is part of the basic monitoring series, an effort to clarify monitoring concepts for both beginners and experienced users.

Time flies, and just like that, we are already in April! The first quarter of 2025 has been packed with exciting updates for VictoriaMetrics Cloud. If you joined our latest Quarterly Virtual Meetup, you might have already seen some of these announcements alongside other great improvements across all things VictoriaMetrics. In this post, we’ll take a closer look at what’s new in VictoriaMetrics Cloud.

With the introduction of Aiven for AlloyDB Omni, many of our customers have wondered what the difference is between AlloyDB Omni and its architectural source project, open source PostgreSQL. AlloyDB Omni is more than just a re-implementation of PostgreSQL, and understanding how it is similar – and how it differs – from open source PostgreSQL is a valuable exercise.