The INDIGO-DataCloud PaaS relies on Apache Mesos for:
- managed service deployment
- user applications execution
The instantiation of the high-available Mesos cluster is managed by the INDIGO Orchestrator in a fully automated way as soon as a user request described by a TOSCA template is submitted. Once the cluster is up and running, it can be re-used for successive requests.
Mesos is able to manage cluster resources (cpu, mem) providing isolation and sharing across distributed applications (frameworks)
Sophisticated two-level scheduling and efficient resource isolation are the key-features of the Mesos middleware that are exploited in the INDIGO PaaS, in order to run different workloads (long-running services, batch jobs, etc) on the same resources while preserving isolation and prioritizing their execution.
INDIGO PaaS uses:
- Marathon to deploy, monitor and scale Long-Running services, ensuring that they are always up and running.
- Chronos to run user applications (jobs), taking care of fetching input data, handling dependencies among jobs, rescheduling failed jobs.
- Support for Ubuntu 16.04
- Mesos upgraded to 1.1.0
- Marathon upgraded to 1.4.1
- Chronos upgraded to 3.0.2
- marathon-consul, mesos-consul, haproxy-consul replaced with marathon-lb
- Support for persistent storage (using rex-ray driver)
- New TOSCA templates for Mesos Cluster:
- added cluster elasticity
- deployment on AWS
The supported platforms*
Operating System: Ubuntu 14.04, CentOS 7, Ubuntu 16.04 Cloud Management Frameworks - any
- Mesos Clusters can be automatically deployed using the available TOSCA templates. The deployment is performed through ansible recipes
List of the affected packages and/or containers:*
Updated ansible roles:
New ansible roles:
Deprecated ansible roles:
Updated docker images:
- Link to the GitBook documentation: https://www.gitbook.com/book/indigo-dc/mesos-cluster/details
- Please use the INDIGO - DataCloud CatchAll GGUS Support Unit