AWS Partner Network (APN) Blog
Tag: AWS Competency Partners
Announcing Changes to APN Tiers, Benefits, and Requirements for 2019 and Beyond
We announced at AWS re:Invent 2018 updates to the overall APN program that will further recognize and support the growth, investment, and innovation of our evolving APN Partner community, and better align APN Partners to more structured program benefits. These changes include renaming the Standard Tier to Select Tier and updating APN requirements to measure each APN Partner’s knowledge, experience, and customer success.
Introducing the AWS Container Competency Program
Containers are an increasingly important way for developers to package and deploy their applications. AWS customers use containers as the fundamental unit of compute to deploy both existing and net-new workloads like microservices, big data, machine learning models, and batch jobs. At AWS re:Invent 2018, we announced the AWS Container Competency Program to highlight top APN Partner solutions that offer support to run workloads on containers on AWS.
Building the Business Case for Machine Learning in the Real World
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.
Say Hello to 25 New AWS Competency Partners Added in October
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!
Simplicity and Security Through Centralized Application Delivery and F5 Networks
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.
Automating Remediation of Amazon GuardDuty Findings with Dome9 CloudBots
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.
Artificial Intelligence and Machine Learning: Going Beyond the Hype to Drive Better Business Outcomes
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.
Understanding the Data Science Life Cycle to Drive Competitive Advantage
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.
An Executive’s Guide to Delivering Business Value Through Data-Driven Innovation and AI
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.
The Curse of Big Data Labeling and Three Ways to Solve It
The nature of data has changed dramatically. Just a decade back, the majority of our data was structured (residing in relational databases) or textual. Now, with the advent of self-driving vehicles, drones, and the Internet of Things (IoT), images and video data are taking the lion’s share of the data storage zoo. As we create more and more data on more and more devices, however, this problem is not going away. In fact, we have reached a point where there aren’t enough people on the planet to label all the data we’re creating.