Quality medical care today relies on “health systems” built from geographically distributed healthcare settings such as hospitals, urgent care clinics, imaging centers, nursing homes, pharmacies, and specialist offices, among many others. Each setting shares data within the broader health system through Electronic Medical Records (EMRs). EMR systems, which were purpose-built to manage patient records, help improve patient outcomes through the real-time sharing of patient data.

Many businesses in the current market have integrated both DevOps and agile to stay ahead of the competition. A recent report showed that 97% of companies have now shifted to using agile development methods. By implementing the two concepts, businesses achieve higher customer satisfaction levels and more brand loyalty. One element that makes it possible to achieve these goals is process automation.

Today, Gremlin is introducing Gremlin for AWS, a suite of tools to more easily find and fix the reliability risks that cause downtime on AWS. The cloud opens up a range of reliability challenges that didn’t exist before, especially for customers running distributed, mission-critical workloads. Teams experience the pain of failed migrations, frequent incidents, and reliability toil, but often struggle to modernize their approach to reliability as they modernize their infrastructure.

Cortex is an Internal Developer Portal (IDP) that reduces friction in developing software that stays aligned to standards of excellence. While all IDPs offer some cataloging functionality, the ability of that catalog to match existing business logic can mean the difference between a true system of record, and yet-another--tool.

I had the opportunity to present with Michael Fratto, Senior Research Analyst at S&P Global Market Intelligence, at a virtual event hosted by Redmond. We discussed how telemetry pipelines are critical in controlling telemetry data (logs, metrics, events, and traces). Mike shared excellent insights from his recent research survey that discussed the proliferation of observability tools in enterprises and the challenges organizations face in managing those tools. ‍

Redgate Monitor is an essential tool for DBA teams worldwide, providing real-time monitoring of SQL Server and PostgreSQL performance. With RedgateMonitor, you can easily track deployments, errors, and other events on the timeline. This feature, called annotations, allows you to quickly identify the root cause of performance issues and take corrective action. Redgate Monitor’s timeline is a powerful tool that helps you stay on top of your database performance and keep your systems running smoothly.

Like many other industries, organisations in the public sector have been keen to make use of the flexibility offered by cloud computing, but are now observing unpredictable and rising costs. Much of which can be mitigated through careful planning and on-premise infrastructure. Government guidance now recommends switching to a strategy of the most appropriate solution for a problem, rather than a one-size-fits-all or carte blanche approach of shifting all applications to the cloud.

When it comes to observability, we believe open source will win in the end. It’s a sentiment shared by a wide spectrum of users, whether they work in auto manufacturing, banking, or shipping. The U.S. federal government is yet another industry to prove this, showing that even those operating under the strictest security and compliance requirements see OSS as their preferred approach.

Savvy organizations are embarking on a journey toward Autonomic IT to better manage their IT environments, particularly as hybrid configurations grow in popularity and are accompanied by greater complexity. Driven by AI and automation, Autonomic IT can help organizations optimize resource allocation, improve the effectiveness of maintenance efforts, avoid downtime, and keep end users happy.

PyTorch is an open source machine learning (ML) framework that makes it easy for researchers and developers to move their projects from prototyping to production. With PyTorch, you don’t have to learn complex C++ code - you can use regular Python for your ML projects. This makes it a great choice for anyone who wants to get started quickly and easily with ML.