mirror of
https://github.com/zeek/zeek.git
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Checkpoint, don't try running this. It's broken all over the place.
This commit is contained in:
Seth Hall
parent
8778761c07
commit
6dc204b385
14 changed files with 352 additions and 379 deletions
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@ -5,24 +5,16 @@
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module Measurement;
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export {
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## The metrics logging stream identifier.
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redef enum Log::ID += { LOG };
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## This is the interval for how often threshold based notices will happen
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## after they have already fired.
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const threshold_crossed_restart_interval = 1hr &redef;
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## The various calculations are all defined as plugins.
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type Calculation: enum {
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PLACEHOLDER
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};
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## Represents a thing which is having metrics collected for it. An instance
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## of this record type and an id together represent a single measurement.
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type Index: record {
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## Represents a thing which is having measurement results collected for it.
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type Key: record {
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## A non-address related metric or a sub-key for an address based metric.
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## An example might be successful SSH connections by client IP address
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## where the client string would be the index value.
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## where the client string would be the key value.
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## Another example might be number of HTTP requests to a particular
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## value in a Host header. This is an example of a non-host based
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## metric since multiple IP addresses could respond for the same Host
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@ -44,176 +36,152 @@ export {
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str: string &optional;
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};
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## Value supplied when a metric is finished. It contains all
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## of the measurements collected for the metric. Most of the
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## fields are added by calculation plugins.
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type ResultVal: record {
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## The time when this result was first started.
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type Reducer: record {
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## Data stream identifier for the reducer to attach to.
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stream: string;
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## The calculations to perform on the data points.
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apply: set[Calculation];
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## A predicate so that you can decide per key if you would like
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## to accept the data being inserted.
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pred: function(key: Measurement::Key, data: Measurement::DataPoint): bool &optional;
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## A function to normalize the key. This can be used to aggregate or
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## normalize the entire key.
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normalize_key: function(key: Measurement::Key): Key &optional;
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};
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## Value calculated for a data point stream fed into a reducer.
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## Most of the fields are added by plugins.
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type Result: record {
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## The time when the first data point was added to this result value.
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begin: time &log;
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## The time when the last value was added to this result.
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## The time when the last data point was added to this result value.
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end: time &log;
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## The number of measurements received.
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num: count &log &default=0;
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## A sample of something being measured. This is helpful in
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## some cases for collecting information to do further detection
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## or better logging for forensic purposes.
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samples: vector of string &optional;
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};
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type Measurement: record {
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## The calculations to perform on the data.
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apply: set[Calculation];
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## A predicate so that you can decide per index if you would like
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## to accept the data being inserted.
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pred: function(index: Measurement::Index, data: Measurement::DataPoint): bool &optional;
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## A function to normalize the index. This can be used to aggregate or
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## normalize the entire index.
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normalize_func: function(index: Measurement::Index): Index &optional;
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## A number of sample DataPoints to collect.
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samples: count &optional;
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};
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type Results: record {
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begin: time;
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end: time;
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result
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};
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## Type to store a table of metrics result values.
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type ResultTable: table[Index] of Results;
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## Type to store a table of measurement results. First table is
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## indexed on the measurement Key and the enclosed table is
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## indexed on the data id that the Key was relevant for.
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type ResultTable: table[Key] of table[string] of Result;
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## Filters define how the data from a metric is aggregated and handled.
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## Filters can be used to set how often the measurements are cut
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## and logged or how the data within them is aggregated.
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type Filter: record {
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## A name for the filter in case multiple filters are being
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## applied to the same metric. In most cases the default
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## filter name is fine and this field does not need to be set.
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id: string;
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## The interval at which this filter should be "broken" and written
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## to the logging stream. The counters are also reset to zero at
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type Measurement: record {
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## The interval at which this filter should be "broken" and the
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## callback called. The counters are also reset to zero at
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## this time so any threshold based detection needs to be set to a
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## number that should be expected to happen within this period.
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every: interval;
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epoch: interval;
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## Optionally provide a function to calculate a value from the ResultVal
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## structure which will be used for thresholding. If no function is
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## provided, then in the following order of preference either the
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## $unique or the $sum fields will be used.
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threshold_val_func: function(val: Measurement::ResultVal): count &optional;
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## The reducers for the measurement indexed by data id.
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reducers: set[Reducer];
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## Optionally provide a function to calculate a value from the Result
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## structure which will be used for thresholding.
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threshold_val: function(result: Measurement::Result): count &optional;
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## The threshold value for calling the $threshold_crossed callback.
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threshold: count &optional;
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## A series of thresholds for calling the $threshold_crossed callback.
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threshold_series: vector of count &optional;
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## A callback that is called when a threshold is crossed.
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threshold_crossed: function(key: Measurement::Key, result: Measurement::Result) &optional;
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## A callback with the full collection of ResultVals for this filter.
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## A callback with the full collection of Results for this filter.
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## It's best to not access any global state outside of the variables
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## given to the callback because there is no assurance provided as to
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## where the callback will be executed on clusters.
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period_finished: function(data: Measurement::ResultTable) &optional;
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## A callback that is called when a threshold is crossed.
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threshold_crossed: function(index: Measurement::Index, val: Measurement::ResultVal) &optional;
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};
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## Function to associate a metric filter with a metric ID.
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##
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## id: The metric ID that the filter should be associated with.
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##
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## filter: The record representing the filter configuration.
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global add_filter: function(id: string, filter: Measurement::Filter);
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## Create a measurement.
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global create: function(m: Measurement::Measurement);
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## Add data into a metric. This should be called when
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## a script has measured some point value and is ready to increment the
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## counters.
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##
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## id: The metric identifier that the data represents.
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##
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## index: The metric index that the value is to be added to.
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## key: The metric key that the value is to be added to.
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##
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## increment: How much to increment the counter by.
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global add_data: function(id: string, index: Measurement::Index, data: Measurement::DataPoint);
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## data: The data point to send into the stream.
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global add_data: function(id: string, key: Measurement::Key, data: Measurement::DataPoint);
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## Helper function to represent a :bro:type:`Measurement::Index` value as
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## Helper function to represent a :bro:type:`Measurement::Key` value as
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## a simple string.
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##
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## index: The metric index that is to be converted into a string.
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## key: The metric key that is to be converted into a string.
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##
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## Returns: A string reprentation of the metric index.
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global index2str: function(index: Measurement::Index): string;
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## Event to access metrics records as they are passed to the logging framework.
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global log_metrics: event(rec: Measurement::Info);
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## Returns: A string representation of the metric key.
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global key2str: function(key: Measurement::Key): string;
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}
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redef record Filter += {
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# Internal use only. The metric that this filter applies to. The value is automatically set.
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id: string &optional;
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redef record Reducer += {
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# Internal use only. Measurement ID.
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mid: string &optional;
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};
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redef record ResultVal += {
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# Internal use only. This is the queue where samples
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# are maintained since the queue is self managing for
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# the number of samples requested.
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sample_queue: Queue::Queue &optional;
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redef record Result += {
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# Internal use only. Indicates if a simple threshold was already crossed.
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is_threshold_crossed: bool &default=F;
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# Internal use only. Current index for threshold series.
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# Internal use only. Current key for threshold series.
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threshold_series_index: count &default=0;
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};
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# Store the filters indexed on the metric identifier and filter name.
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global filter_store: table[string, string] of Filter = table();
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redef record Measurement += {
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# Internal use only (mostly for cluster coherency).
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id: string &optional;
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};
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# This is indexed by metric id and filter name.
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global store: table[string, string] of ResultTable = table();
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# Store of reducers indexed on the data id.
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global reducer_store: table[string] of set[Reducer] = table();
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# This is a hook for watching thresholds being crossed. It is called whenever
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# index values are updated and the new val is given as the `val` argument.
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# Store of results indexed on the measurement id.
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global result_store: table[string] of ResultTable = table();
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# Store of measurements indexed on the measurement id.
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global measurement_store: table[string] of Measurement = table();
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# This is called whenever
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# key values are updated and the new val is given as the `val` argument.
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# It's only prototyped here because cluster and non-cluster have separate
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# implementations.
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global data_added: function(filter: Filter, index: Index, val: ResultVal);
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global data_added: function(m: Measurement, key: Key, result: Result);
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# Prototype the hook point for plugins to do calculations.
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global add_to_calculation: hook(filter: Filter, val: double, data: DataPoint, result: ResultVal);
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# Prototype the hook point for plugins to merge Measurements.
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global plugin_merge_measurements: hook(result: ResultVal, rv1: ResultVal, rv2: ResultVal);
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global add_to_reducer: hook(r: Reducer, val: double, data: DataPoint, result: Result);
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# Prototype the hook point for plugins to merge Results.
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global compose_resultvals_hook: hook(result: Result, rv1: Result, rv2: Result);
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# Event that is used to "finish" metrics and adapt the metrics
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# Event that is used to "finish" measurements and adapt the measurement
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# framework for clustered or non-clustered usage.
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global finish_period: event(filter: Measurement::Filter);
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global finish_period: event(m: Measurement);
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event bro_init() &priority=5
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{
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Log::create_stream(Measurement::LOG, [$columns=Info, $ev=log_metrics]);
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}
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function index2str(index: Index): string
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function key2str(key: Key): string
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{
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local out = "";
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if ( index?$host )
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out = fmt("%shost=%s", out, index$host);
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if ( index?$str )
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out = fmt("%s%sstr=%s", out, |out|==0 ? "" : ", ", index$str);
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return fmt("metric_index(%s)", out);
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if ( key?$host )
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out = fmt("%shost=%s", out, key$host);
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if ( key?$str )
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out = fmt("%s%sstr=%s", out, |out|==0 ? "" : ", ", key$str);
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return fmt("metric_key(%s)", out);
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}
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function merge_result_vals(rv1: ResultVal, rv2: ResultVal): ResultVal
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function compose_resultvals(rv1: Result, rv2: Result): Result
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{
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local result: ResultVal;
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local result: Result;
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# Merge $begin (take the earliest one)
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result$begin = (rv1$begin < rv2$begin) ? rv1$begin : rv2$begin;
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@ -224,16 +192,6 @@ function merge_result_vals(rv1: ResultVal, rv2: ResultVal): ResultVal
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# Merge $num
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result$num = rv1$num + rv2$num;
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hook plugin_merge_measurements(result, rv1, rv2);
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# Merge $sample_queue
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if ( rv1?$sample_queue && rv2?$sample_queue )
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result$sample_queue = Queue::merge(rv1$sample_queue, rv2$sample_queue);
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else if ( rv1?$sample_queue )
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result$sample_queue = rv1$sample_queue;
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else if ( rv2?$sample_queue )
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result$sample_queue = rv2$sample_queue;
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# Merge $threshold_series_index
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result$threshold_series_index = (rv1$threshold_series_index > rv2$threshold_series_index) ? rv1$threshold_series_index : rv2$threshold_series_index;
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@ -241,105 +199,103 @@ function merge_result_vals(rv1: ResultVal, rv2: ResultVal): ResultVal
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if ( rv1$is_threshold_crossed || rv2$is_threshold_crossed )
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result$is_threshold_crossed = T;
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hook compose_resultvals_hook(result, rv1, rv2);
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return result;
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}
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function reset(filter: Filter)
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function reset(m: Measurement)
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{
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if ( [filter$id, filter$name] in store )
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delete store[filter$id, filter$name];
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if ( m$id in result_store )
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delete result_store[m$id];
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store[filter$id, filter$name] = table();
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result_store[m$id] = table();
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}
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function add_filter(id: string, filter: Filter)
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function create(m: Measurement)
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{
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if ( [id, filter$name] in store )
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m$id=unique_id("");
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measurement_store[m$id] = m;
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for ( reducer in m$reducers )
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{
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Reporter::warning(fmt("invalid Metric filter (%s): Filter with same name already exists.", filter$name));
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return;
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reducer$mid = m$id;
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if ( reducer$stream !in reducer_store )
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reducer_store[reducer$stream] = set();
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add reducer_store[reducer$stream][reducer];
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}
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if ( ! filter?$id )
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filter$id = id;
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filter_store[id, filter$name] = filter;
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store[id, filter$name] = table();
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schedule filter$every { Measurement::finish_period(filter) };
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reset(m);
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schedule m$epoch { Measurement::finish_period(m) };
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}
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function add_data(id: string, index: Index, data: DataPoint)
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function add_data(data_id: string, key: Key, data: DataPoint)
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{
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# Try to add the data to all of the defined filters for the metric.
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for ( [metric_id, filter_id] in filter_store )
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# Try to add the data to all of the defined reducers.
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if ( data_id !in reducer_store )
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return;
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for ( r in reducer_store[data_id] )
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{
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local filter = filter_store[metric_id, filter_id];
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# If this filter has a predicate, run the predicate and skip this
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# index if the predicate return false.
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if ( filter?$pred && ! filter$pred(index, data) )
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# If this reducer has a predicate, run the predicate
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# and skip this key if the predicate return false.
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if ( r?$pred && ! r$pred(key, data) )
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next;
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#if ( filter?$normalize_func )
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# index = filter$normalize_func(copy(index));
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if ( r?$normalize_key )
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key = r$normalize_key(copy(key));
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local metric_tbl = store[id, filter$name];
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if ( index !in metric_tbl )
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metric_tbl[index] = [$begin=network_time(), $end=network_time()];
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local m = measurement_store[r$mid];
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local results = result_store[m$id];
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if ( key !in results )
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results[key] = table();
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if ( data_id !in results[key] )
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results[key][data_id] = [$begin=network_time(), $end=network_time()];
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local result = metric_tbl[index];
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local result = results[key][data_id];
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++result$num;
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# Continually update the $end field.
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result$end=network_time();
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# If a string was given, fall back to 1.0 as the value.
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local val = 1.0;
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if ( data?$num || data?$dbl )
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val = data?$dbl ? data$dbl : data$num;
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++result$num;
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# Continually update the $end field.
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result$end=network_time();
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#if ( filter?$samples && filter$samples > 0 && data?$str )
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# {
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# if ( ! result?$sample_queue )
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# result$sample_queue = Queue::init([$max_len=filter$samples]);
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# Queue::push(result$sample_queue, data$str);
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# }
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hook add_to_calculation(filter, val, data, result);
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data_added(filter, index, result);
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hook add_to_reducer(r, val, data, result);
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data_added(m, key, result);
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}
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}
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# This function checks if a threshold has been crossed. It is also used as a method to implement
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# mid-break-interval threshold crossing detection for cluster deployments.
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function check_thresholds(filter: Filter, index: Index, val: ResultVal, modify_pct: double): bool
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function check_thresholds(m: Measurement, key: Key, result: Result, modify_pct: double): bool
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{
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if ( ! (filter?$threshold || filter?$threshold_series) )
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return;
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if ( ! (m?$threshold || m?$threshold_series) )
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return F;
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local watch = 0.0;
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if ( val?$unique )
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watch = val$unique;
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else if ( val?$sum )
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watch = val$sum;
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#if ( val?$unique )
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# watch = val$unique;
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#else if ( val?$sum )
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# watch = val$sum;
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if ( filter?$threshold_val_func )
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watch = filter$threshold_val_func(val);
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if ( m?$threshold_val )
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watch = m$threshold_val(result);
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if ( modify_pct < 1.0 && modify_pct > 0.0 )
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watch = watch/modify_pct;
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if ( ! val$is_threshold_crossed &&
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filter?$threshold && watch >= filter$threshold )
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if ( ! result$is_threshold_crossed &&
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m?$threshold && watch >= m$threshold )
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{
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# A default threshold was given and the value crossed it.
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return T;
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}
|
||||
|
||||
if ( filter?$threshold_series &&
|
||||
|filter$threshold_series| >= val$threshold_series_index &&
|
||||
watch >= filter$threshold_series[val$threshold_series_index] )
|
||||
if ( m?$threshold_series &&
|
||||
|m$threshold_series| >= result$threshold_series_index &&
|
||||
watch >= m$threshold_series[result$threshold_series_index] )
|
||||
{
|
||||
# A threshold series was given and the value crossed the next
|
||||
# value in the series.
|
||||
|
|
@ -349,19 +305,19 @@ function check_thresholds(filter: Filter, index: Index, val: ResultVal, modify_p
|
|||
return F;
|
||||
}
|
||||
|
||||
function threshold_crossed(filter: Filter, index: Index, val: ResultVal)
|
||||
function threshold_crossed(m: Measurement, key: Key, result: Result)
|
||||
{
|
||||
if ( ! filter?$threshold_crossed )
|
||||
if ( ! m?$threshold_crossed )
|
||||
return;
|
||||
|
||||
if ( val?$sample_queue )
|
||||
val$samples = Queue::get_str_vector(val$sample_queue);
|
||||
#if ( val?$sample_queue )
|
||||
# val$samples = Queue::get_str_vector(val$sample_queue);
|
||||
|
||||
filter$threshold_crossed(index, val);
|
||||
val$is_threshold_crossed = T;
|
||||
m$threshold_crossed(key, result);
|
||||
result$is_threshold_crossed = T;
|
||||
|
||||
# Bump up to the next threshold series index if a threshold series is being used.
|
||||
if ( filter?$threshold_series )
|
||||
++val$threshold_series_index;
|
||||
if ( m?$threshold_series )
|
||||
++result$threshold_series_index;
|
||||
}
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue