John Martin

Moving a database from on-premises to the cloud is easy to get wrong: undersized instances, surprise costs, unplanned downtime. Join Kellyn and John as we look at Redgate Monitor's new database migration planning feature, designed to help you size, plan, and cost a move with real data instead of guesswork.

AI assistants and MCP servers are already connecting to production databases, whether a developer wired one up to chase a bug or an analyst is using one to query data. For most DBAs, the question isn’t whether to allow it. It’s whether you’d notice if something went wrong. In Redgate’s State of...

There are many reasons to look at using PostgreSQL for your database systems, but what if you're already using SQL Server? In this session we will walk through the process needed to migrate a SQL Server database to PostgreSQL running on Azure Database for PostgreSQL Flexible Server.

Azure SQL Database has several Automatic Tuning features which can be enabled, one of these is Automatic Index Management. It can identify which indexes are needed or not and make recommendations or you can let it create and drop them as needed. What could possibly go wrong... In this session we will look at how to enable the capabilities, find the recommendations, and the changes to the way we will need to handle database development if we want to let Azure SQL Database manage the indexes in our databases too.

Database security has long been considered the realm of the DBA. However, this is not the case, the developers are the owners of the database and the security is part of the schema. Together let's look at why this is, and should be the case that database security is shifted left and how we can look to incorporate security into our development processes.

Azure SQL Database has several Automatic Tuning features which can be enabled, one of these is Automatic Index Management. It can identify which indexes are needed or not and make recommendations or you can let it create and drop them as needed. What could possibly go wrong... In this session we will look at how to enable the capabilities, find the recommendations, and the changes to the way we will need to handle database development if we want to let Azure SQL Database manage the indexes in our databases too.

As data platforms are becoming more complex it can be challenging to keep track of what is going on in your data platform. Finding out who is logging in, making configuration changes, or accessing data, the options are varied and disjointed. Together we will look at where and how we can obtain the data to be able to answer these questions.

SaaS and hosted applications are the norm in many businesses now. Whereas previously we could go direct to a database to extract data for our warehouses, now it is common to interact with these systems via APIs which were not designed for bulk data operations.

Unit testing and integration testing have become part and parcel of development processes the world over. So why don't we apply the same rigour to the data persistence layer? We trust that our unit tests will catch bad data being sent to the data store, but what if they let us down? A great (or terrible, depending on your view) example of what can happen is the failed Horizon project at the UK Post Office. I'll propose why we should, and how we might go about adding a robust testing mechanism for the data store which can help spot issues earlier in the SDLC before end users are involved and start reporting issues.

APIs, once the preserve of application developers or enterprise service bus integration solutions, are now commonplace for data engineers to use. With increased use of SaaS platforms holding key business data, we can no longer connect to the database directly.

APIs, once the preserve of application developers or enterprise service bus integration solutions, are now commonplace for data engineers to use. With increased use of SaaS platforms holding key business data, we can no longer connect to the database directly. Rather, we need to pull data from an API, which will be unique per-platform. Join me as I work through the key characteristics of APIs, from authentication, headers, body, and parameters, through to pagination for large volumes of data. I will demonstrate how we can utilise APIs in our data pipelines to get the data we need, when we need it.

Understanding that there is no panacea when it comes to securing your data assets is important. We will look at how to adopt the right mindset and then build a secure architecture to minimise the risk to your data.

In recent years we have seen and heard about a scenarios where hackers gained access to your system, databases are encrypted and where data is stolen. The question is not if our systems are going to be attacked, but rather when this is going to happen. As a data professional you have the obligation to protect the data to the best of your abilitity. You have to deal with both outsider and insider threats. Outside attackers motivated by profit, activism, retribution, or mischief. Insider threats may have the same motives but could be tied to workplace issues resulting in people abusing their access privileges to inflict harm. When you have been attacked it is really important to find out what happened and how to mititgate the attack. Mitigation, or Attack Mitigation, is the reduction in seriousness or severity of an event. In mitigation we center around strategies to limit the impact of a threat against our data. In this session we will discuss: * Teach you how you can attack your systems * Mitigate the attack * Log your findings

Moving databases to the cloud is relatively easy, but doing it in a way that ensures successful outcomes for our business or customers is less so. The database is one piece of a larger puzzle, putting all the pieces together is important. Together we will look at a scenario, then walk through and discuss just what it would take to make it work and answer any questions you might have about the process. This session will focus on the situations, questions, and challenges that need to be overcome rather than specific technologies.

Large-scale data analytics has traditionally meant integrating multiple technologies to deliver results. Amazon Redshift changes this by providing a Massively Parallel Processing (MPP) engine which spans your data lake, relational, and non-relational stores.

Azure SQL DB Managed Instance is here, Microsoft want us to use it, but what is it good for and how should you use it? Let us get past the marketing hype and take a more in-depth look at Managed Instance and see what we can do with it. To get the most out of Managed Instance you need to understand the Azure infrastructure that underpins it and how this behaves, as well as understanding the differences between General Purpose and Business Critical tiers. There is far more to Managed Instance than meets the eye and if you do not understand the details then you run the risk of spending a lot more money and not getting the performance you want. During this training day we will cover the core Azure infrastructure components that underpin Managed Instance and look at how these can impact its usability and performance. We will work through use cases and migration scenarios that are available for us to use when it comes to making the jump to Azure. We will also look at how applications that use with SQL Server on-premises can be updated to get the most out of Managed Instance, including authentication and high-level architecture.