|By Business Wire||
|July 28, 2014 08:05 AM EDT||
GigaSpaces Technologies today announced it has completely re-architected its Cloudify offering to provide Intelligent Orchestration of applications on the cloud. With this product rewrite, the new Cloudify orchestration platform simplifies the application deployment, management and scaling experience on OpenStack, VMware vSphere and other clouds and environments.
In current orchestration models, most tools focus primarily on application installation, while much of application management occurs after deployment. As a result, vast custom tool chains are often used to manually manage post-deployment processes such as monitoring and logging, leading to significant overhead, complexity and inconsistency across systems. Cloudify’s redesign provides a simple solution for managing the full application lifecycle. The new intelligent orchestration model introduces a feedback loop that automates fixes and updates without manual intervention, all with a single platform that integrates with any tool chain. Cloudify 3.0 reduces the complexity of cloud application management and ensures that managed applications meet their desired SLA.
“To deliver this next generation, intelligent orchestration, we needed to rethink Cloudify’s design,” said Yaron Parasol, VP of Product at GigaSpaces. “With a new language of code, adoption of industry standards and development of scalable and custom workflows, we created something that few are doing today - orchestration of the entire app lifecycle that encompasses both pre-deployment and post-deployment management with a single platform.”
- New intelligence in orchestration: Cloudify 3.0 eliminates the boundaries between orchestration and monitoring, providing a mechanism that automatically reacts to monitored events with appropriate corrective measures. Version 3.0 includes these building blocks of custom workflows, a workflow engine and a modeling language that enables the automation of any process and any stack. The subsequent release (due in Q4 2014) will introduce monitoring and custom policies for automated triggering of such corrective measures to provide auto-healing and auto-scaling capabilities.
- Integrating the entire automation and monitoring tool chain: Cloudify 3.0 brings together a variety of tools that are used throughout the various stages of the application lifecycle. In doing so, Cloudify promotes common industry best practices, making it easy to integrate and use best-of-breed tools to manage the environment. Cloudify has a new plug-in architecture that enables easy integration of a wide range of tools for monitoring, configuration management and cloud infrastructure. Examples of such integration include Chef, Puppet, Fabric and Docker for configuration management, OpenStack Heat for infrastructure orchestration, logstash and Elasticsearch for logging and monitoring, and Reimann.IO for real-time analytics.
- Native integration with OpenStack: As OpenStack is fast becoming the de facto standard for private clouds, Cloudify 3.0 offers even tighter integration with OpenStack technology and core services, including KeyStone, Neutron, Nova and Heat. The underlying design of Cloudify was re-architected to match the design principles of OpenStack services, including the rewriting of the core services in Python and leveraging common infrastructure building blocks such as RabbitMQ.
- Support for VMware, CloudStack, SoftLayer and other clouds: Cloudify 3.0 contains built-in plug-ins for VMware vSphere and Apache CloudStack, and will soon have plug-ins for vCloud and SoftLayer. It comes with open plug-in architecture to support other clouds, including Amazon AWS, GCE and Linux containers such as Docker (plug-ins for all of which will be released in the coming few weeks). With Cloudify 3.0, users can span the same application across multiple cloud environments without creating a new Cloudify setup per environment. This is useful for users who are transitioning from their existing environment into a cloud environment and also for allowing bursting and hybrid deployments between OpenStack, VMware, Amazon and other clouds.
- New topology-driven monitoring: Cloudify 3.0 introduces a new concept of topology-driven monitoring in which the entire application management and tracking system is centralized around the application topology, rather than the infrastructure. This makes it possible at any given moment to track not only the state of the application, but also the status of deployment, updates and scaling processes through a single view. As the monitoring system is integrated with the orchestration engine, the two systems are always in sync and up to date, eliminating the need to rely on external discover services.
- Support for the TOSCA specification: TOSCA (Topology and Orchestration Specification for Cloud Applications) allows users to describe any set of automation processes on cloud applications with an extendable set of hooks and component types. Cloudify 3.0 uses a YAML-based orchestration template driven by the TOSCA specification. The next release of Cloudify will include full syntax compatibility with the TOSCA specification as soon as it becomes officially supported.
- Multiple applications that can span thousands of nodes: Cloudify 3.0 allows for management and monitoring of large scale applications using a message broker to manage the communication with its managed instances and a logging and analysis engine for big data scale.
GigaSpaces Technologies provides software middleware for deployment, management and scaling of mission-critical applications on cloud environments through two main product lines, XAP In-Memory Computing and Cloudify. Hundreds of Tier-1 organizations worldwide are leveraging GigaSpaces’ technology to enhance IT efficiency and performance, from top financial firms, e-commerce companies, online gaming providers, healthcare organizations and telecom carriers.
In a recent research, analyst firm IDC found that the average cost of a critical application failure is $500,000 to $1 million per hour and the average total cost of unplanned application downtime is $1.25 billion to $2.5 billion per year for Fortune 1000 companies. In addition to the findings on the cost of the downtime, the research also highlighted best practices for development, testing, application support, infrastructure, and operations teams.
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