Operations | Monitoring | ITSM | DevOps | Cloud

The rise in popularity of open-source RBDMs has encouraged many organizations to adopt PostgreSQL, but as a DBA or Developer, it can be challenging when exploring new database platforms, no matter how experienced you are. When looking at SQL Server, it has many similarities to PostgreSQL, but there are several big differences too.

As the size and complexity of database estates increases, with more workloads and data being hosted on more platforms, both on-premises and in the cloud, so the appeal of third-party database monitoring tools has also grown. Their ability to provide a holistic view of an entire estate and monitor multiple databases and platforms from a single dashboard has been shown to save DBAs and IT teams many hours of time when compared to home-grown solutions.

The last few years have seen a big change in the size, make-up, and nature of database estates. Data is growing both in volume and complexity, it is now normal to have workloads as well as data in multiple public clouds, and organizations are increasingly using different kinds of databases for different use cases.

Migrating to the cloud has many advantages … until you’re the one tasked with making it happen. For many data professionals, this will be a first step from the traditional, predictable challenges of managing on-premises servers to the many and varied databases and platforms in the cloud. As many have discovered, it’s not simply a case of ‘lift and shift’.

There’s been a lot of talk about GitHub Copilot recently, loudly touted as Your AI pair programmer. According to GitHub, Copilot for Business brings the power of generative AI to engineering teams, accelerating the speed of software development and innovation. At the back end is OpenAI Codex, a modified version of the GPT-3 Large Language Model (LLM) used in ChatGPT. At the front end it integrates with code editors like Visual Studio and JetBrains to automatically generate code.

Most applications have large and complex databases at the back end, making it hard for developers to adequately test their work before it goes out. Having a fast, repeatable process to deliver data on demand is an essential part of an effective software development lifecycle, ultimately leading to improved customer satisfaction.

Are you looking to modernize and migrate your data but have questions about the complex organizational challenges? We recently hosted the webinar: Overcoming Organizational Challenges in Data Modernization and Cloud Migration: A Guide for Senior IT Leaders.

In this series of blog posts, we speak with database professionals from financial services organizations around the world to better understand how DevOps is shaping the sector. On the way, we dig into key current factors including the rise of technology upstarts in fintech and insurtech, the speed of digital transformation, and the ever-increasing threat of cyberattacks.

It’s a constant challenge for many businesses: where and how to focus investment in technology to remain competitive and stay current with the latest trends and development practices, while still meeting changing customer demands.

Managing an IT team is a tough job. While demands on services are increasing, both internally and externally, the need to be aware of and in control of application and server performance is a constant pressure. Right now, there are four key areas that are of particular concern for those responsible for IT departments and teams.