Operations | Monitoring | ITSM | DevOps | Cloud

Distributed Tracing, combined with end-to-end monitoring, lets organizations keep track of their business transactions and receive alerts when anomalies happen. End-to-end monitoring benefits business users and functional administrators more than developers and technical administrators. Nowadays, for developing integration solutions, microservice architectures are becoming the norm. A solution based on such an architecture relies on different services that shape a specific solution together.

Scaling up your development organization typically involves spreading development across multiple locations around the globe. One of the key challenges with multisite development is ensuring reliable access to required software packages and artifacts for teams collaborating across time zones. The JFrog Software Supply Chain Platform solves this challenge with federated repositories in JFrog Artifactory.

Rancher is a Kubernetes management platform that creates a consistent environment for multicloud container operation. It solves several of the challenges around multicloud Kubernetes deployments, such as poor visibility into where workloads are running and the lack of centralized authentication and access control. Multicloud improves resiliency by letting you distribute applications across providers.

In this post we want to give a simple introduction for using network policies in a sample project and explaining how it works in K3s to help improving the security of your deployments. There is a common misunderstanding about K3s support for network policies, as K3s is using flannel CNI by default, and the Flannel CNI doesn’t support network polices.

Preview environments are temporary environments where developers can test code changes before deploying them to production, also called ephemeral environments, they’re temporary and should be discarded after testing changes. Carrying out tests using accurate data is a major challenge when creating and destroying environments. Put differently, you need realistic data and traffic in the preview environment to reflect the performance of code changes in production.

Today’s Cognitive Network Operations Center (Cognitive NOC) is a significant advancement that employs artificial Intelligence (AI) and machine learning (ML) to dramatically modernize and improve network management and operations. Working together, the NOC and IT Process Automation (ITPA) propel superior efficiency and effectiveness of network operations, minimize downtime, lower operational costs, and overcome additional challenges in optimizing network performance.

Canonical is happy to announce that Charmed Kubeflow 1.7 is now available in Beta. Kubeflow is a foundational part of the MLOps ecosystem that has been evolving over the years. With Charmed Kubeflow 1.7, users benefit from the ability to run serverless workloads and perform model inference regardless of the machine learning framework they use.