Yesterday, Docker announced that Docker for AWS is graduating to public beta. Docker for AWS is a great way for ops to setup and maintain secure and scalable Docker deployments on AWS. With Docker for AWS, IT ops teams can deploy a standard Docker platform, integrate deeply with underlying infrastructure to ensure Docker takes advantage of the host environment’s native capabilities and exposes a familiar interface to administrators, deploy the platform to all the places where you want to run Dockerized vApp and make sure the latest and greatest Docker versions are available for the hardware, OSs, and infrastructure you love.
The VDI UDS Enterprise 2.0 connection broker supports OpenNebula as a hypervisor for accessing and managing Windows and Linux virtual desktops. In fact, our software has received the OpenNebula Ready certification, which guarantees the perfect integration of the two solutions and the correct operation of a joint infrastructure.
Among other advantages, UDS Enterprise gives OpenNebula unlimited flexibility, adds compatibility with practically any hypervisor, authenticator and connection protocol, and offers the possibility of using many of these components simultaneously.
To manage an OpenStack cloud infrastructure, you need to manage the configuration of the individual cloud services and the orchestration between them. There are some Open Source tools that can help you with these tasks, and there are many ways to evaluate them. Some considerations include the language used or perhaps availability of a UI.
Open Source automation tools have modules to manage OpenStack and free up time for other tasks. Puppet is used in Red Hat OpenStack Platform Director, Chef is used by SUSE, Ansible is used by HPE Helion and Juju has its own configuration engine and collection of Charms to deploy and manage OpenStack.
In addition to the advantages of VDI, in this document the consulting firm also details the five main challenges most companies face when they are planning to adopt this technology:
–High initial investment in hardware and licenses: Many corporations require a fast return on investment. However, this does not always occur, due to the initial investment needed. Another factor is that the cost per user makes VDI virtually unfeasible for those companies with a large amount of users.
Monitoring a server involves watching the performance of a single physical or virtual machine. Conversely, VDI almost always consists of multiple servers working together. As such, one of the big VDI monitoring challenges is scalability: Admins must simultaneously monitor the performance of each of the servers that plays a role in VDI. The second factor that complicates VDI monitoring is translating the raw performance metrics into something meaningful.
Now, imagine a VDI server clocks in with an excessively high CPU utilization value. What does it mean for the end-user experience? It is really difficult to say for sure. The user might suffer severe performance problems as a result of insufficient CPU resources.
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