AWS Partner Network (APN) Blog

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.

Many organizations feel that AI will be the biggest disruptor to their industry in the next five years, and many leaders are asking if machine learning is right for their business. We offer an approach to identifying real business value using ML and discuss how to identify and quantify which use cases are the best fit for your industry and how to derive business value with the help of AWS Machine Learning Competency Partners.

Managed services have historically been tied to infrastructure, but next-generation MSPs are involved at a much deeper level on the AWS Cloud. It’s not just about managing the infrastructure anymore. It’s about managing the full lifecycle of services—from planning and designing to building and optimizing workloads for AWS Customers. The AWS MSP Partner Program recognizes leading APN Consulting Partners that are highly skilled at providing full lifecycle solutions to AWS Customers.

The AWS Competency Program welcomed 25 new APN Partners in October—spanning workload, solution, and industry designations. The AWS Competency Program helps customers identify and choose the world’s top APN Partners that have demonstrated technical proficiency and proven customer success in specialized solution areas. Please join us in welcoming our newest AWS Competency Partners!

NetOps ensures the infrastructure used to support application delivery is configured for performance, scalability, and availability. SecOps ensures that applications, regardless of where they are deployed, are done so in a consistent and secure manner. F5 Networks shows how to walk through a typical application deployment utilizing the F5 BIG-IP Cloud Edition to provide a centralized point of control for provisioning, configuring, and managing F5 BIG-IP application delivery controllers.

Ippon Technologies has successfully re-written a large mainframe third-party software package to Java Angular Spring Boot microservices. The package supported 130 TPS and 1,800 MIPS, catered to over 5,000 users, and housed more than 5 TB of business-critical data. Ippon helped the customer define the approach and architecture, and then developed the microservices along with the CI/CD pipeline on AWS. Learn about the project’s technical aspects, methodologies, and lessons learned.

Dome9’s integration with Amazon GuardDuty brings to the table a way of surfacing security findings, providing context and creating automated remediations. Users that identify a finding can look through their Dome9 console and pinpoint the exact instance, VPC, and security group associated with it. This helps customers identify the compromised instance, as well as potential instances that may have a similar posture, thereby allowing you to mitigate the risk before exposure.

Do you want to become more familiar with how your company can use artificial intelligence (AI) and machine learning (ML) but feel a bit lost amongst the buzzwords and hype? Driving business outcomes with AI doesn’t need to be overwhelming. It’s all about exploring which business problems you want to solve, how good predictions can help you achieve those outcomes, and then taking practical steps to get there while implementing an organization-wide AI strategy.

Companies struggling with data science don’t understand the data science life cycle. As a result, they fall into the trap of the model myth. This is the mistake of thinking that because data scientists work in code, the same processes that works for building software will work for building models. Models are different, and the wrong approach leads to trouble. Domino Data Lab shares that organizations excelling at data science are those that understand it as a unique endeavor, requiring a new approach.

Fostering a data-driven culture within your organization isn’t only about technology. It’s also about enabling stakeholders to make better decisions and realizing new opportunities by embracing an AI-driven mentality for solving business problems. In this post, AWS Machine Learning Competency Partner Crayon discusses some of the first steps you should take and the essential questions to ask yourself as you thoughtfully develop your company’s relationship with data.