Model-driven automation, versus purpose-built, demonstrates significant value when you need to dynamically change your application’s flow (a common need), such as workflows and policies.
This is especially true with containers and microservices architectures, that are highly componentized, and fragile when it comes to static processes and workflows – and can even lead to cascading failures, when these processes are broken. The monitoring of a model driven topology gives you a much deeper, robust ability to react and respond to changes.
Orchestration of services across platform domains.
Modeling is done independent of the Container platform (“where”) and independent of how the service is orchestrated (“how”).
Provision containers platform across clouds and manage their resource availability and capacity.
Kubernetes has turned into possibly the most widely adopted Docker container management project, surpassing Docker Swarm, which is now making strides, and gaining renewed adoption. That said, bringing up a Kubernetes cluster can often times be a complex undertaking, while deploying code can many times be error-prone, with a lot of manual intervention and no way simple to rollback, and infrastructure scaling can be time consuming and often times under-utilizes the underlying infrastructure. Cloudify can automate the deployment, management of Kubernetes as well as Docker and other containers on any infrastructure in a hybrid environment, in a manner that is infrastructure-aware, enabling cost savings through maximum utilization.
Docker containers were created for fast and reliable deployment of self-contained application components on any underlying infrastructure. However, applications are typically multi-tier in their architecture, which means that each container has dependencies which need to be managed properly.
Cloudify’s Docker orchestration will take care of the timing of container creation by order of dependency, as well as all of the necessary configurations to allow the containers to communicate and pass the required runtime properties to one another.
Based on TOSCA, Cloudify’s YAML-based blueprints, enable you to describe even the most complex topologies, including the infrastructure, middleware tier, and app layers on top of these.
Cloudify has a built-in Docker pluginand matching types, which allow users to use Docker containers as part of any topology. This provides a full-blown orchestration and automation method for large-scale Docker-based systems.
Mesos has become a popular container and cloud cluster scheduler, and is used often times to manage container clusters at a massive scale. Cloudify has integrated with Mesos to deliver clusters on demand, as well as auto-scale and heal, even Mesos-scale deployments.
Being API-driven, Cloudify is also able to plugin to Mesos and orchestrate southbound, as Mesos manages the higher-level applicative components.
Checkout the README and Mesos Blueprint in our examples catalog.