Category: Artificial Intelligence

Artificial intelligence operations (AIOps) is the process of using machine learning techniques to solve operational problems. The goal of AIOps is to reduce human intervention in IT operations processes. By using advanced machine learning techniques, you can reduce operational incidents and increase service quality, and AIOps can help you predict incidents before they happen. Amazon […]

In this post, we’ll show how enterprises can use AWS Service Catalog to create AWS Service Catalog products based on AWS machine learning (ML) services, such as Amazon Polly and Amazon Rekognition. These products are packaged in AWS Service Catalog portfolios that customers can use for their use cases. These portfolios can generate revenue for […]

AWS allows customers to assign metadata to their AWS resources in the form of tags. Each tag consists of a customer-defined key and an optional value. Tags can make it easier to manage, search for, and filter resources by purpose, owner, environment, or other criteria. AWS tags can be used for many purposes like organizing […]

When customers begin their machine learning (ML) journey, it’s common for individual teams in a line of business (LoB) to set up their own ML environments. This provides teams with flexibility in their tooling choices, so they can move fast to meet business objectives. However, a key difference between ML projects and other IT projects is […]

Customers are constantly looking to innovate in order to remain competitive in their respective markets. One way to achieving such competitiveness is through the ability to build services and applications fast and cost effectively, thereby reducing time to market while driving down costs. One of the feedback we regularly get from customers is that, applications […]

AWS Control Tower is a managed AWS service that automates the creation of a multi-account AWS environment based upon the AWS Well-Architected Framework. It builds the environment using AWS best practices for security and management services. In this blog post, we’ll show how a managed service provider can use AWS Control Tower and AWS Service […]

Many customers need a secure method to access Amazon SageMaker notebooks within their private network without logging in to the AWS console, or using the AWS CLI/SDKs. This may be desired for enhanced security or to provide an easier self-service path for data scientists. In this blog post, we show you a how to connect […]

Amazon DevOps Guru, now in preview, is an ML-powered cloud operations service that assists you in improving application availability. It’s easy to set up and use, and leverages machine learning models informed by years of operational expertise in building, scaling, and maintaining highly available applications at Amazon.com. DevOps Guru continuously analyzes streams of disparate data […]

Conversational interfaces like chatbots have become an important channel for brands to communicate with their customers, partners, and employees. They help with faster service, 24/7 availability, and reduced service costs. By monitoring conversations between your customers and the bot, you can gain insights into user interactions, trends, and missed utterances. The additional insights will help […]

by Sanjay Garje and Vebhhav (Veb) Singh Enterprises of all sizes are moving to the AWS Cloud. We hear from leadership of those enterprise teams that they are looking to provide a safe, cost-governed way to provide easy access to Amazon SageMaker to promote experimentation with data science to unlock new business opportunities and disrupt […]