Category: Technical How-to

As organizations mature in their cybersecurity capabilities, they are looking to try and leverage automation to reduce the operational burden of alerting, detecting, and responding to threats. This blog post walks through how to combine findings from disparate security systems into a single operational view to help analysts identify, respond, and remediate existing threats while maintaining a dynamic response platform that scales with their environment.

The AWS Migration Evaluator can help organizations with VMware fleets by collecting detailed data on VM (virtual machine) usage and using that to prepare a business case for moving to the cloud and estimate the cost of migration. However, sensitive network data collected by the Migration Evaluator, such as system names and IP addresses, cannot leave highly secured and regulated organisations. In this blog post, learn how a simple python script can anonymize AWS Migration Evaluator usage data, allowing it to be uploaded even in highly regulated environments.

Terabytes of Earth Observation (EO) data are collected each day, quickly leading to petabyte-scale datasets. By bringing these datasets to the cloud, users can use the compute and analytics resources of the cloud to reliably scale with growing needs. In this post, we show you how to set up a Pangeo solution with Kubernetes, Dask, and Jupyter notebooks step-by-step on Amazon Web Services (AWS), to automatically scale cloud compute resources and parallelize workloads across multiple Dask worker nodes.

Several smart cities use FIWARE, an open source framework supporting the development of smart solutions. FIWARE leverages sensing data from Internet of Things (IoT) devices, then collects, stores, and analyzes data with an API call. One FIWARE component, Orion Context Broker, gathers context information from diverse sources such as mobile apps, IoT devices, and social networking services, and manages the lifecycle of this context information, from registrations, updates, queries, and subscriptions. In this blog post, we address building Orion Context Broker on AWS. Learn how to deploy Orion Context Broker and Cygnus on AWS with AWS Cloud Development Kit (AWS CDK) and Docker Compose quickly.

In this blog post series on getting started building a data lake for healthcare with AWS, I focus on improving the security posture of our example build by incorporating the relatively new Attribute Based Access Control (ABAC) feature of Amazon Cognito. This helps to both streamline and improve the granularity of access control for various user profiles connected to our data lake scenario.

With Amazon Connect, nonprofits are able to build a robust, scalable omnichannel cloud contact center to provide reliable, secure, and cost-effective services to their community, all without needing to provision any underlying infrastructure. In this blog, learn how to leverage AWS CloudFormation templates to quickly and simply set up Amazon Connect.

Data is an invaluable asset in the world of nonprofits. In this blog post, we offer a technical walkthrough to learn how nonprofits of all sizes can use Amazon QuickSight to quickly create interactive dashboards with the help of machine learning, providing a self-service way to effectively consume and analyze data without writing any code or having to worry about infrastructure.

Discovery Education (DE) provides standards-aligned digital curriculum resources, engaging content, and professional learning for K12 classrooms. Learn how they worked with AWS to enhance its K12 learning platform with machine learning (ML) capabilities.

In the immediate aftermath of a natural disaster, cell towers, power lines, and telephone and internet cable are often damaged or destroyed, limiting the ability for responders to share data and access the internet. The AWS Disaster Response team conducted a field testing operation designed to replicate a common disaster response scenario, to show how to establish an ad-hoc network at field sites with limited connectivity and create a link to an office headquarters to provide access to cloud-based resources and data to responders in the field.

It’s time consuming for public sector organizations to sort through packed voicemail inboxes, figure out how to respond, return calls, and take detailed records on each call. So AWS developed a scalable call center solution that allows organizations to streamline the entire call process – from call intake, to generating actionable insights for response with artificial intelligence, to detailed recordkeeping and storage. This blog post guides you through how to create this task-generating cloud call center solution with Amazon Connect.