System Garden

Habitat Features

System & Application Monitor

cpu Real time monitor and visualiser of data metrics from applications and operating system. Built in probes include CPU utilization, storage, memory, network and processes. Take a look at the full list of probes to see what is actually collected.

Graphical Visualisation

Multiple Sources Fast graphical desktop tool displays current data with updates from the local client and other hosts that also run habitat. Data sets can come from anywhere and be retrieved from any time in the past for comparison or later analysis.

Add your own Data

Any user data can be added for time series tracking from either the graphical tool or the command line. Scripting languages of all types can send data to a habitat file or the repository, even in real time! If the data can be made to look like a series of tables, then it can live with habitat (providing its text and numbers!).

Charts, Tables or Text

I/O Charts
Habitat draws charts, renders tables or draws text of of your data sources, updated at the frequency of the source collection. Multi instance data, like disks, network interfaces or processors are split into adjacent charts.

Drill-down Data

graph rulers
Zoom in to years of data to show a graph of just a few seconds with just a few clicks of the zoom button, then scroll back and forth in time. In Habitat its fast to explore even big time series sets and easy to keep track of with the adaptive time scales

Switchable Collection Scenarios

Custom Graphs
How and what you collect depends on your purpose. Habitat's job table is completely customisable and a set of prefabricated tables have been created to suit many collection scenarios from bechmarking to low latency.

Storage and Data Routing

Low maintenance local storage All collected data is recorded into a ringbuffer on the machine's local disk, which is a structure that automatically removes old data without the need for administrators. Histories of significant length can be built up over time without resorting to shared archives for absolutely everything, so keeping high performance.
Replication to System Garden System Garden's central repository is used for to collect data from many machines into one place. It is the venue for social IT mangagement, sharing data and analysis among colleagues and a place for long term trends and high density data points Its also useful in reducing the load on a busy host and for seeing a machine's data if it is inaccessible or down. It can be read back and treated in the same way as local data.
Multiple data formats Import and export data held in CSV or other tabular formats into Habitat's fat headed array format, used to move data around internally. Data can be saved to and read back from local or archived storage with command line tools for batched transfers or interactively with MyHabitat.
Data consolidation Modest storage consumtion is achieved by removing older high frequency data and replacing it with low frequency samples to reduce data consumption. Habitat carries out this operation several times but is still able to reassemble a single continuous set of data. Use System Garden's repository for long term high frequency data. The parameters for sample frequency, retained quanity and archive replication details can be tuned to suit your circumstances.
Multi-protocol data sources All data sources in Habitat are integraded into a common I/O system with a URL-like addresses. Protocols include: file, standard in, out and error, ringstore (the local storage), sg (remote system garden archive), HTTP, HTTPS, even FTP.

Customisation and Programming

User development For developers there is an API for extending the collector (called clockwork) with plug-ins, allowing data to be pulled in from other sources created by users. Data from many sources can then be plotted along side each other.
Log file recording As well as performance data, log files can be captured at regular intervals to provide a context of events. Metrics and events can then be see alongside each other.
Alerts and alarms Patterns in log files or threshold crossing can trigger internal actions and command line execution. This can add an extra level of intellegence to the collection of statistics.
Multi level configuration Highly configurable, Habitat allows layers of directives to make maintenance easy. Users can pick up their personal preferences, whilst still using System Garden defaults and site customisations.


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