October 1, 2025: This post was updated to reflect the new name of Security Hub, which is AWS Security Hub CSPM (Cloud Security Posture Management). Security teams must efficiently validate and document exceptions to AWS Security Hub (Cloud Security Posture Management, previously known as Security Hub) findings, while maintaining proper governance. Enterprise security teams need […]| Amazon Web Services
As organizations rapidly deploy large language models (LLMs) and generative AI agents to power increasingly intelligent workloads, they struggle to monitor and troubleshoot the complex interactions within their AI applications. Traditional monitoring tools fall short in providing the visibility across components, leading to developers and AI/ML engineers to manually correlate interaction logs or building custom […]| Amazon Web Services
In today’s digital healthcare landscape, optimal application performance and user experience are crucial for business success. Indegene, a digital-first life sciences commercialization company, combines deep medical expertise with domain-contextualized technology to help clients accelerate innovation, modernize operations, and improve customer experience. With the world’s top 20 pharma companies among its clientele, Indegene brings an AI-first […]| Amazon Web Services
It's easy to get started with CloudWatch. Jump start your experience using documentation, blog posts, and tutorials intended to guide you to best practices.| Amazon Web Services, Inc.
AWS CloudWatch Logs intend to help developers store, access and monitor the log files within the Amazon EC2 instances. Apart from that, you can also access| Whizlabs Blog
Do you have thousands of Amazon CloudWatch alarms across AWS Regions and want to quickly identify which ones are low-value alarms or misconfigured alarms across regions? Are you looking for ways to identify alarms which are in ‘ALARM’ or ‘IN_SUFFICIENT’ state for several days and need to be revisited? Do you need a cleanup mechanism […]| Amazon Web Services
This article was originally posted on the Amazon Web Services Architecture blog. In a recent customer engagement, Quantiphi, Inc., a member of the Amazon Web Services Partner Network, built a solution capable of pre-processing tens of millions of PDF documents before sending them for inference by a machine learning (ML) model. While the customer's use case--and hence the ML model--was very specific to their needs, the pipeline that does the pre-processing of documents is reusable for a wide a...| packetmischief.ca
