Operations | Monitoring | ITSM | DevOps | Cloud

Canonical

Secure container orchestration at the edge

The cloud-native way of building software allows for consistency across developer environments and massive scalability of application deployments. Both these attributes are useful for edge, but create new challenges related to security and resilience. Watch this demo to see how Canonical’s modular technology stack addresses these challenges by using well-known cloud primitives.

Model-driven audit trail infrasructure

Graylog is one of the most popular tools for opensource monitoring and log management in telco environments. We will show how Charmed OSM with the help of juju eases its deployment and integration with MongoDB, elastic search, and other charmed telco network function elements. The same goes for a basic LMA stack with Prometheus and Grafana.

OpenStack CentOS alternatives:7 reasons to migrate to Ubuntu

Looking for OpenStack CentOS alternatives after recent changes in the CentOS project? Think Ubuntu – the most popular Linux distribution for OpenStack deployments, after CentOS, across development and production environments. Wondering what makes Ubuntu different? Here are seven reasons you should consider Ubuntu when planning your CentOS migration.

Fintech AI/ML on Ubuntu

The financial services (FS) industry is going through a period of change and disruption. Technology innovation has provided the means for financial institutions to reimagine the way in which they operate and interact with their customers, employees and the wider ecosystem. One significant area of development is the utilisation of artificial intelligence (AI) and machine learning (ML) which has the potential to positively transform the FS sector.

What is KFServing?

TL;DR: KFServing is a novel cloud-native multi-framework model serving tool for serverless inference. KFServing was born as part of the Kubeflow project, a joint effort between AI/ML industry leaders to standardize machine learning operations on top of Kubernetes. It aims at solving the difficulties of model deployment to production through the “model as data” approach, i.e. providing an API for inference requests.

Deploying Mattermost and Kubeflow on Kubernetes with Juju 2.9

Since 2009, Juju has been enabling administrators to seamlessly deploy, integrate and operate complex applications across multiple cloud platforms. Juju has evolved significantly over time, but a testament to its original design is the fact that the approach Juju takes to operating workloads hasn’t fundamentally changed; Juju still provides fine grained control over workloads by placing operators right next to applications on any platform.