The MiCADO framework v0.8.0
The Open-source framework is based on K8s and dedicated to automate configuration, coordination, and management of Docker containers and its run-time in various cloud environments. It is able to simulataneously monitor multiple parameters to auto-scale microservices to ensure the idle status of your applications.
Open-source, GDPR compliant, reliable
MiCADO Master is deployed on a virtual machine via an Ansible playbook, configured as the Kubernetes Master Node and has installed:
- the Docker Engine,
- Occopus to scale VMs,
- Prometheus for monitoring,
- the COLA Policy Keeper to act on scaling decisions and
- the COLA Submitter to provide a submission endpoint.
The MiCADO Master Node supports the operation, management and monitoring of applications based on specific parameters such CPU or network traffic, detecting bottlenecks, and realising the autoscaling control loops. The desired deployment and run-time characteristics of the application are defined in a TOSCA-based Application Description Template (ADT) that provides all relevant information, application requirements, infrastructure characteristics and scaling policies to roll out the Infrastructure and manage the application cluster. Additionally, scaling decision can be further improved with a machine learning based optimiser.
MiCADO’s Industrial Demonstrators
To prove and demonstrate MiCADO’s applicability for industry-scale problems, three near production quality demonstrators and 24 further proof of concepts were implemented during the project’s lifetime. The three large MiCADO demonstrators and a commercial trial are briefly described below.
Audience Finder is a national audience data and development tool in the UK that enables cultural organisations to understand, compare and apply audience insight. Before implementing MiCADO, the software was hosted on a large AWS EC2 instance to meet the required computational power and provide seamless services. Outside high peaks the instance was barely used, and the under-utilised resources generated unnecessary costs. To manage peak-loads and server capacities with MiCADO, and to reduce operational costs, WordPress and Audience Finder were dockerised and hosted on small AWS EC2 instances. Within the MiCADO framework, Audience Finder’s microservices can be separately managed, debugged and scaled according to the occurring demand.
Evacuation plans are required for high hazard fields production areas, like nuclear plants or chemical plants, by the authorities. In case of emergency, time to act is limited and it is needed to have a valid plan to decide and act on. To accomplish this, simulation models need to be set-up and different cases of emergency considered, like single sets of possibilities, starting conditions, while respecting the specific kind of emergency. Evacuation simulation models are computed various times, each scenario runs for multiple replications to allow variance in statistical distributions, for example, different walking speeds. By introducing MiCADO, the simulation of experiments can be restricted to a certain time frame and resources as well as microservices scale based on the desired deadline. This allows running simulations in the desired time while improving the quality of decision-making processes by reducing time-to-decision and providing more information to the decision-maker and improve the confidence of making a decision.
Nextcloud is an online storage and collaboration tool. Nextcloud Enterprise is aiming to create a Cloud storage for companies in compliance with internal specifications, the European GDPR and generally accepted accounting principles (GAAP). By joining forces, the MiCADO team and HKN, a German data center are working on the dockerisation of the application enabling automated deployment processes and additional services, such as Disaster Recovery and High Availability of databases and clusters.