Features

Extensibility to Future & Legacy Technology

Support New Technologies and Breathe New Life Into Existing

Service Delivery That’s Painless and Future-proof

  • Integrate public cloud delivery with new and existing systems from your datacenter without struggle or workarounds
  • Embrace the new, respect the old—extend the functionality of your legacy technology investments
  • Easily coordinate multiple existing systems while being prepared for future systems yet to be deployed

WE GET WHERE YOU’RE COMING FROM

Coordinating multiple existing technologies while staying agile enough to accommodate future technologies is no easy task. Successfully extending to multiple cloud providers in an organized fashion while trying to predict the future is a herculean task without the right platform. All the while, your end-users are demanding easier access to their resources to deliver more, faster.

The ability to bring together both new and legacy technologies while staying prepared for the integration of future systems is within reach. CloudBolt marries the technologies found in private data centers with public clouds to deliver new and exciting services that combine the strengths of the latest technologies and maximizes existing technology investments.

How CloudBolt Makes It Happen

CloudBolt uses a plug-in architecture that allows users to create plug-ins in the form of Python scripts, remote shell scripts, web hooks, and email notifications. Plug-ins can be triggered in response to job events, rules, and user actions on services.

CloudBolt’s open architecture allows nearly unlimited possibilities for extension. It’s easy to integrate with existing processes, yet it’s upgrade-safe.

TECHNICAL FEATURES

The CloudBolt rules engine is a simple, yet powerful way to test for a condition either in CloudBolt or in an external system, and execute a script if that condition holds true. A common use-case is to check a threshold on the number of servers deployed in a given environment, and sending an email if it’s exceed. Another example is calling to an external monitoring system to determine if the current system load across a given service requires CloudBolt to create a new cloud server to burst to the cloud.

Pluggable to its core, CloudBolt allows almost all aspects of its workflows to be customized. In addition to extending workflows, the CloudBolt user interface can also be extended with custom views to add new or enterprise-proprietary applications. CloudBolt plug-ins are written as Python scripts and can be shared between CloudBolt workflows and stored in a source code repository such as GitHub or GitLab.

Need to provide end-users with information about a server, environment or service beyond the default CloudBolt view? CloudBolt accommodates this need with its UI Extension framework that allows administrators to extend existing views with their own. These views might provide detailed monitoring information, back-end storage control, and much more.

CloudBolt Snapshot

Features & Competitive Comparison
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