Tag: Amazon Aurora

We are excited to highlight 29 APN Partners that received new designations in January for our global AWS Competency, AWS Managed Service Provider (MSP), and AWS Service Delivery programs. These designations span workload, solution, and industry, and help AWS customers identify top APN Partners that can deliver on core business objectives. APN Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.

The AWS Service Delivery Program identifies and endorses APN Partners with validated customer experience and a deep understanding of specific AWS services, such as Amazon Aurora, Amazon Redshift, and Amazon EC2 for Windows. Please join us in congratulating these top 8 APN Partners on achieving AWS Service Delivery Program designations in October. Each organization follows AWS best practices and has proven success delivering AWS services to end customers.

With the introduction of Amazon Aurora Serverless (currently in preview), SaaS providers are now equipped with a model to bring the scale and cost efficiency of serverless computing directly to storage partitioning models of SaaS solutions. We take a closer look at how Aurora Serverless works and how it influences your approach to storage partitioning in SaaS environments. The goal here is to highlight the implications of the serverless storage model, identifying key areas that will be of particular interest to SaaS developers.

As part of the onboarding process when joining the AWS Service Delivery Program, APN Partners must go through a technical audit of their experience delivering AWS services to end customers. This audit is conducted by internal technical experts who validate the APN Partner’s knowledge and capabilities for a specific AWS service. To help APN Partners better understand this process, we are introducing Validation Checklists that provide visibility into the criteria we use during an organization’s technical validation.

While modernizing customer mainframes, the team at Blu Age discovered that Batch can be a complex aspect of a mainframe migration to AWS. It’s critical to design your AWS architecture to account for the key Batch stringent performance requirements such as intensive I/Os, large datasets, and short durations. Let’s explore how to migrate mainframe Batch to AWS microservices using Blu Age automated transformation technology.

Introduction by Terry Wise, Global Vice President, Channels & Alliances at AWS What can your data do for you? More importantly, how can insights derived from your data help you drive additional value for end customers? Our APN partners offer services and solutions that complement what AWS has to offer. As an example, many customers […]