Developing and deploying database changes can be a complex task, made more challenging by the fact that development teams need to move fast, while also protecting an organization’s crown jewels: its data. Speed of delivery and protecting data can often feel incompatible, but there are industry-proven database DevOps practices that bring them together in harmony.

We now support SSO (single-sign on), offering an improved login experience for our customers. SSO can be enabled on our website. We want our customers to have a great experience when using our products and part of that is an easy sign-in experience for users. Enabling SSO will remove the need for users to use their Redgate ID and password when signing into the customer portal and compatible products.

To find out more about cloud migrations, the pitfalls that await the unwary, and what the security implications are, I recently sat down with Dustin Dorsey, Systems & Data Architect at Biobot Analytics, based in Cambridge, MA. In the first post in this series, we talked about cloud providers being responsible for security ‘of’ the cloud, while their clients are responsible for security ‘in’ the cloud.

While the cloud is recognized as more secure than on-premises servers and infrastructures, it does come with the often talked about shared responsibility model. Cloud providers are responsible for security ‘of’ the cloud, while their clients are responsible for security ‘in’ the cloud. It’s ‘differently secure’, rather than the traditionally secure organizations have been used to when working with on-premises environments.

With the huge growth in volume and complexity, data management has become a key priority in most Enterprises. But for this data to be utilised in a meaningful way, how do you tackle the added complexity of controlling access across both technical and business departments? Our CPO, David Gummer recently interviewed the CEO of the popular Universal Database management tool, DBeaver, Tatiana Krupenya, to discuss the often-feared topic of sharing access to the database. Prefer video? Watch the interview here.

More and more organizations are migrating their data to the cloud but the majority are likely to end up managing hybrid estates, with some data managed through a cloud provider and some managed locally. This leads to some unique issues, especially around monitoring and services. If the objective of migrating to the cloud is simply to implement virtual machines (VMs) in a different location than you traditionally do, there will be fewer challenges.

The SPACE framework is an acronym for an approach to measuring, understanding, and optimizing engineering productivity. Outlined by researchers from GitHub, Microsoft, and the University of Victoria, it encourages leaders to look at productivity holistically, placing leading metrics in context with each other and linking them to output, often team goals, rather than individual effort. The SPACE framework breaks productivity into five metrics.

Over the last decade, I’ve rarely met a data professional whose organization wasn’t experiencing data growth and making more demands of their data. We build and deploy new applications faster than we retire old ones, and new data is accumulating dramatically faster on our existing systems than our ability to decide to delete older information. Additionally, the ever-growing number of users and devices interacting with that data increases the strain on the infrastructure underpinning it.

In a series of blog posts about AI, I’ve been looking at how intelligent ChatGPT is, how good ChatGPT and Bing are when you employ them as a technology writer, and how the engineering team at Redgate is using GitHub Copilot to aid with writing code. Now it’s time to take a look at image creation tools, and where better to start than Andy Warhol? I like Andy Warhol.

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.