Managing a large computing environment can be a daunting task. In a typical computing environment, machines are made of smaller components like CPUs, memory and disks, housed in virtual components like hypervisors or physical objects like racks, rooms, floors and buildings.
Machines run software, such as operating systems, runtime environments and network services which may have dependencies on services running on other machines in different parts of the environment. There are people working on all of those machines, to keep them maintained and online.
Structure is designed to handle environments like the above and gives you insight into your environment, its components and the relationships between them.
Internally, Structure uses a graph to represent the environment. A graph is a lot more flexible than traditional data models when it comes to persisting and querying relationships between components, especially in the context of a computing environment.
Because of its graph foundations, Structure has the power to find the most common to the most obscure relationships between the entities in your data center, in extremely large data sets, in a very efficient manner.
Structure implements a concept we call instruments. Instruments are the tools you use to do something in your data center. They are used to manage services on every level, run health- checks and every other task that is usually performed in large scale computing environments. We'll provide you with plenty of instruments out-of-the-box and provide the end-user with the ability to create instruments themselves, in any language of choice.
Combined, these two mechanisms enables unprecedented flexibility. For example, say you use different remote administration protocols for different types of systems. Because Structure knows about these protocols, and knows what software implements these protocols (and most of the time already provides instruments for them), we can issue the same task to these different types of servers, and Structure makes sure everything gets done without you having to know all the intricate infrastructural details.
We are almost there. There are some milestones which we are working towards, like automated discovery of components in a network, which we expect to finish by the end of the first quarter of 2017 for our first official release. When we are at that point, we're going to expand our instruments to support everything you need.
Send us an email at firstname.lastname@example.org and we'll get back to you to schedule an appointment for a pre-availability demonstration.