Category: Amazon RDS

Organizations have been using data warehouse and business intelligence (DWBI) workloads to support business decision making for many years. These workloads are brought to the Amazon Web Services (AWS) platform to utilize the benefit of AWS cloud. However, these workloads are built using multiple vendor tools and technologies, and the customer faces the burden of […]

As customers commit to a DevOps mindset and embrace a nearly continuous integration/continuous delivery model to implement change with a higher velocity, assessing every change impact on an application resilience is key. This blog shows an architecture pattern for automating resiliency assessments as part of your CI/CD pipeline. Automatically running a resiliency assessment within CI/CD […]

Many organizations have applications that require Microsoft SQL Server to run relational database workloads: some applications can be proprietary software that the vendor mandates Microsoft SQL Server to run database service; the other applications can be long-standing, home-grown applications that included Microsoft SQL Server when they were initially developed. When organizations migrate applications to AWS, […]

Enterprise customers often need to architect a hybrid Active Directory solution to support running applications in the existing on-premises corporate data centers and AWS cloud. There are many reasons for this, such as maintaining the integration with on-premises legacy applications, keeping the control of infrastructure resources, and meeting with specific industry compliance requirements. To extend […]

There has been a tectonic shift in the approach to hosting enterprise workloads. Companies are rapidly moving from on-premises data centers to cloud-based services. The driving factor has been the ability to innovate faster on the cloud. Your transition to cloud can be straightforward, but it does go beyond the usual ‘lift-and-shift’ approach. To start […]

Data is at the center of stateful applications. Data consistency models will vary when choosing in-Region vs. multi-Region. In this post, part 2 of 3, we continue to filter through AWS services to focus on data-centric services with native features to help get your data where it needs to be in support of a multi-Region […]

Deploying global applications has many challenges, especially when accessing a database to build custom pages for end users. One example is an application using AWS Lambda@Edge. Two main challenges include performance and availability. This blog explains how you can optimally deploy a global application with fast response times and without application changes. The Amazon Aurora […]

The ability to analyze your Internet of Things (IoT) data can help you prevent loss, improve safety, boost productivity, and even develop an entirely new business model. This data is even more valuable, with the ever-increasing number of connected devices. Companies use Amazon Web Services (AWS) IoT services to build innovative solutions, including secure edge […]

This blog post was last reviewed/updated August, 2022. The updated version shown below is based on working backwards from a customer need to ensure data consistency post migration, to a modernized microservice architecture. A queuing system is composed of producers and consumers. A producer enqueues messages (writes messages to a database) and a consumer dequeues […]

The relational database is a critical resource in application architecture. Enterprise organizations often use relational database management systems (RDBMS) to provide embedded workflow state management. But this can present problems, such as inefficient use of data storage and compute resources, performance issues, and decreased agility. Add to this the responsibility of managing workflow states through […]