Real-time Analytics News Roundup for Week Ending December 5

Real-time Analytics News Roundup for Week Ending December 5

Real-time Analytics News Roundup for Week Ending December 5. Amazon Web Services made announcements related to DevOps and new container capabilities, the MLCommons launched MLPerf to accelerate adoption of ML.

Amazon Web Services made announcements related to DevOps and new container capabilities, the MLCommons consortium launched MLPerf to accelerate adoption of ML, and more.

Keeping pace with news and developments in the real-time analytics market can be a daunting task. We want to help by providing a summary of some of the items our staff came across each week. Here is a short list of some news from this week:

Amazon Web Services announced Amazon DevOps Guru, a fully-managed operations service that uses machine learning to make it easier for developers to improve application availability by automatically detecting operational issues and recommending specific actions for remediation. The tool automatically collects and analyzes data like application metrics, logs, events, and traces for identifying behaviors that deviate from normal operating patterns. When Amazon DevOps Guru identifies anomalous application behavior (e.g., increased latency, error rates, resource constraints, etc.) that could cause potential outages or service disruptions, it alerts developers with issue details via Amazon Simple Notification Service (SNS) and partner integrations like Atlassian Opsgenie and PagerDuty. The notifications help them quickly understand the potential impact and likely causes of the issue with specific recommendations for remediation.

In complementary news, PagerDuty announced a product collaboration with Amazon DevOps Guru. Through this new integration, PagerDuty will automatically ingest observability data from Amazon DevOps Guru. PagerDuty consolidates these digital health signals and alerts and uses AIOps to contextualize and filter out the noise so teams can remediate issues in real-time, and customers can ensure critical business services get delivered.

Amazon Web Services announced four new container capabilities to help businesses develop, deploy, and scale modern applications. AWS is now making it even easier to provision, deploy, and manage container applications. It is doing this by enabling customers to run Amazon Elastic Container Service (ECS) or Amazon Elastic Kubernetes Service (EKS) in their own data centers, adding a new service for automated container and serverless application development and deployment, and providing a new container registry that gives developers an easy and highly available way to share and deploy container software publicly. The new services include Amazon EKSAmazon ECSAWS Fargate, and AWS Proton.

Senet, Inc. announced it is collaborating with CNIguard and Semtech Corporation to deliver natural gas monitoring solutions to utilities across the United States. Through this partnership, the companies are addressing the utility industry‚Äôs digitization requirements by providing an intelligent network infrastructure designed to support a massive ecosystem of utility-centric LoRaWAN devices for gas safety and service delivery.

Iguazio announced that it has achieved the AWS Outposts Ready designation, part of the Amazon Web Services (AWS) Service Ready Program. This development AWS and Iguazio customers who can utilize Amazon SageMaker to develop artificial intelligence (AI) models and data pipelines, and easily deploy and manage these in production using the Iguazio Data Science Platform on AWS and now also on AWS Outposts, benefiting from the same high performance at scale in hybrid AWS environments.

Veritone, the creator of an operating system for artificial intelligence (AI), aiWARE, announced it now supports the NVIDIA CUDA platform, enabling organizations to run intensive AI and machine learning (ML) tasks on NVIDIA GPUs, whether on-premises or in the Microsoft Azure and Amazon Web Services (AWS) clouds.

GigaSpaces announced the InsightEdge portfolio, a new suite of in-memory computing platforms designed to drive enterprise digital transformation offering speed, performance, and scale. Combined with AIOps functionality, GigaSpaces delivers an easy to deploy and manage portfolio of software platforms to meet enterprise data and analytics processing needs.

 MLCommons, an open engineering consortium, launched its industry-academic partnership to accelerate machine learning innovation and broaden access to this critical technology for the public good. The non-profit organization initially formed as MLPerf, now boasts a founding board that includes representatives from Alibaba, Facebook AI, Google, Intel, NVIDIA, and Professor Vijay Janapa Reddi of Harvard University; and a broad range of more than 50 founding members.

analytics big data big data analysis tools big data platforms cloud real-time decisions cloud services containers digital twin

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