Tablespoon is a real-time system metrics monitoring system. It uses agent-side filtering and a publish-subscribe pattern in order to minimise performance impact. In its current version, it is for the most part, customised for Karamel.

Getting started

Installation

Installing Tablespoon can be a bit tedious since you have to install the agents on each instance that you want to monitor. If you are using an orchestration tool of any sort, the installation of Tablespoon could be added with just a few lines extra code. All the necessary files are currently hosted on Dropbox, for more details check out how Karamel has implemented it.

API

The client-side API supports several features as seen in the table below.

Parameter	Description
subscriber	An interface that receives TablespoonEvent upon arrival.
groupId	Identifier for a group of machines.
machines	A set of specific machines, can not be used in conjunction with groupId.
eventType	Can be either GROUP AVERAGE, GROUP MEDIAN or REGULAR.
resource	Can be specified as one of 69 parameters, or more broadly as CPU, MEM, NET or DSK.
duration	Specifies for how long the topic will be active on agents.
sendRate	The rate at which agents send events.
retrievalDelay	An artifical delay added to prevent excessive querying.
high	A Threshold which filters events based on a percentile.
low	A secondary Threshold to create two boundaries.
replace	Is used to replace or replicate a topic.
submit	Submits the API call asynchronously.

The API can for example be used in the following way:

/* preparing resources */
Threshold t1 = new Threshold(70.0, LESS_THAN);
Resource r = new Resource(CPU);

/* first call to the API */
String uniqueId1 = api.submitter().
subscriber(subscriber).
groupId("group 1").
eventType(GROUP_AVERAGE).
resource(r).
duration(60).
sendRate(5).
high(t1).
submit();

/* second call to the API */
Threshold t2 = new Threshold(75.0, LESS_THAN);
String uniqueId2 = api.submitter().
replace(uniqueId1, true).
high(t2).
submit();