Apache Guacamole 1.1 has been announced. Apache Guacamole is a clientless remote desktop gateway. The latest release includes two subprojects, the HTML5 web application which serves the Guacamole client to users, and “guacamole-server”, the remote desktop proxy which the web application communicates with.
The 1.1.0 release also features support for dynamic image quality and for connecting directly to the terminals of Kubernetes pods.
The full details on the release are available here.
Ktor, the web framework for Kotlin, announces new update
Ktor 1.3 was released with improved integration with the kotlinx.serialization library, and support for CIO (a co-routines-based I/O search engine) on Kotlin/Native to make a default multiplatorm engine used in HttpClient.
An incompatible change was introduced in Ktor 1.3 in which HttpResponse no longer implements the Closeable interface. The HttpClient adds experimental support for proxy. If you need to send requests under proxy, you can configure its address in the corresponding parameters:
Also, there is no binary compatibility with 1.2.x, so if you use any external Ktor features you’ll need to recompile them against the latest version.
The full details on the new release are available here.
FireEye acquires Cloudvisory, a multi-cloud security platform
FireEye acquired Cloudvisory and is planning to add cloud workload security capabilities to FireEye Helix to serve as one integrated security operations platform for cloud and container security.
“Security is top of mind for almost all organizations as they migrate critical workloads to the cloud,” said Grady Summers, executive vice president of products and customer success at FireEye. “With the addition of the Cloudvisory technology, FireEye is able to offer a comprehensive, intelligence-led solution to secure today’s hybrid, multi-platform environments.”
The Cloudvisory platform is designed to provide visibility into network traffic for workloads, applications and microservices, the ability to remediate misconfigurations, and provide compliance assurance controls.
IBM’s Cloud Annotations project gets a new automated labeling tool for data labeling
IBM’s Cloud Annotations project gets a new automated labeling tool that takes advantage of AI to assist the labeling process and to cut down the time that developers have to manually draw.
Backed by IBM Cloud Object Storage, Cloud Annotations enables users to store as much data as they need, access the data from anywhere and share across multiple collaborators in real-time.
“Currently, it takes 200-500 samples of hand-labeled images for a model to detect one specific object,” IBM wrote in a post. “Autolabeling images speeds the process and gives developers back valuable time to work on other innovative projects.”