mirror of
https://github.com/zeek/zeek.git
synced 2025-10-17 14:08:20 +00:00
Metrics framework checkpoint.
- New scan.bro merged in and reworked a bit. - Updated metrics API. Now possible to calculate much more.
This commit is contained in:
Seth Hall
parent
1200d04f81
commit
d9195076b1
15 changed files with 851 additions and 356 deletions
|
|
@ -3,9 +3,6 @@
|
|||
##! and will be depending on if the cluster framework has been enabled.
|
||||
##! The goal of this script is to make metric calculation completely and
|
||||
##! transparently automated when running on a cluster.
|
||||
##!
|
||||
##! Events defined here are not exported deliberately because they are meant
|
||||
##! to be an internal implementation detail.
|
||||
|
||||
@load base/frameworks/cluster
|
||||
@load ./main
|
||||
|
|
@ -24,36 +21,34 @@ export {
|
|||
## since it may opt not to if it requested a global view for the index
|
||||
## recently.
|
||||
const cluster_request_global_view_percent = 0.1 &redef;
|
||||
|
||||
## Event sent by the manager in a cluster to initiate the
|
||||
## collection of metrics values for a filter.
|
||||
|
||||
# Event sent by the manager in a cluster to initiate the
|
||||
# collection of metrics values for a filter.
|
||||
global cluster_filter_request: event(uid: string, id: string, filter_name: string);
|
||||
|
||||
## Event sent by nodes that are collecting metrics after receiving
|
||||
## a request for the metric filter from the manager.
|
||||
# Event sent by nodes that are collecting metrics after receiving
|
||||
# a request for the metric filter from the manager.
|
||||
global cluster_filter_response: event(uid: string, id: string, filter_name: string, data: MetricTable, done: bool);
|
||||
|
||||
## This event is sent by the manager in a cluster to initiate the
|
||||
## collection of a single index value from a filter. It's typically
|
||||
## used to get intermediate updates before the break interval triggers
|
||||
## to speed detection of a value crossing a threshold.
|
||||
# This event is sent by the manager in a cluster to initiate the
|
||||
# collection of a single index value from a filter. It's typically
|
||||
# used to get intermediate updates before the break interval triggers
|
||||
# to speed detection of a value crossing a threshold.
|
||||
global cluster_index_request: event(uid: string, id: string, filter_name: string, index: Index);
|
||||
|
||||
## This event is sent by nodes in response to a
|
||||
## :bro:id:`Metrics::cluster_index_request` event.
|
||||
global cluster_index_response: event(uid: string, id: string, filter_name: string, index: Index, data: DataPoint);
|
||||
# This event is sent by nodes in response to a
|
||||
# :bro:id:`Metrics::cluster_index_request` event.
|
||||
global cluster_index_response: event(uid: string, id: string, filter_name: string, index: Index, val: ResultVal);
|
||||
|
||||
## This is sent by workers to indicate that they crossed the percent of the
|
||||
## current threshold by the percentage defined globally in
|
||||
## :bro:id:`Metrics::cluster_request_global_view_percent`
|
||||
global cluster_index_intermediate_response: event(id: string, filter_name: string, index: Metrics::Index, val: count);
|
||||
# This is sent by workers to indicate that they crossed the percent of the
|
||||
# current threshold by the percentage defined globally in
|
||||
# :bro:id:`Metrics::cluster_request_global_view_percent`
|
||||
global cluster_index_intermediate_response: event(id: string, filter_name: string, index: Metrics::Index);
|
||||
|
||||
## This event is scheduled internally on workers to send result chunks.
|
||||
# This event is scheduled internally on workers to send result chunks.
|
||||
global send_data: event(uid: string, id: string, filter_name: string, data: MetricTable);
|
||||
|
||||
}
|
||||
|
||||
|
||||
# This is maintained by managers so they can know what data they requested and
|
||||
# when they requested it.
|
||||
global requested_results: table[string] of time = table() &create_expire=5mins;
|
||||
|
|
@ -76,7 +71,7 @@ global done_with: table[string] of count &create_expire=5mins &default=0;
|
|||
|
||||
# This variable is maintained by managers to track intermediate responses as
|
||||
# they are getting a global view for a certain index.
|
||||
global index_requests: table[string, string, string, Index] of DataPoint &create_expire=5mins &default=[];
|
||||
global index_requests: table[string, string, string, Index] of ResultVal &create_expire=5mins &default=[];
|
||||
|
||||
# This variable is maintained by all hosts for different purposes. Non-managers
|
||||
# maintain it to know what indexes they have recently sent as intermediate
|
||||
|
|
@ -95,23 +90,20 @@ redef Cluster::worker2manager_events += /Metrics::cluster_(filter_response|index
|
|||
@if ( Cluster::local_node_type() != Cluster::MANAGER )
|
||||
# This is done on all non-manager node types in the event that a metric is
|
||||
# being collected somewhere other than a worker.
|
||||
function data_added(filter: Filter, index: Index, val: count)
|
||||
function data_added(filter: Filter, index: Index, val: ResultVal)
|
||||
{
|
||||
# If an intermediate update for this value was sent recently, don't send
|
||||
# it again.
|
||||
if ( [filter$id, filter$name, index] in recent_global_view_indexes )
|
||||
return;
|
||||
|
||||
|
||||
# If val is 5 and global view % is 0.1 (10%), pct_val will be 50. If that
|
||||
# crosses the full threshold then it's a candidate to send as an
|
||||
# intermediate update.
|
||||
local pct_val = double_to_count(val / cluster_request_global_view_percent);
|
||||
|
||||
if ( check_threshold(filter, index, pct_val) )
|
||||
if ( check_thresholds(filter, index, val, cluster_request_global_view_percent) )
|
||||
{
|
||||
# kick off intermediate update
|
||||
event Metrics::cluster_index_intermediate_response(filter$id, filter$name, index, val);
|
||||
|
||||
event Metrics::cluster_index_intermediate_response(filter$id, filter$name, index);
|
||||
++recent_global_view_indexes[filter$id, filter$name, index];
|
||||
}
|
||||
}
|
||||
|
|
@ -137,9 +129,6 @@ event Metrics::send_data(uid: string, id: string, filter_name: string, data: Met
|
|||
# If data is empty, this metric is done.
|
||||
if ( |data| == 0 )
|
||||
done = T;
|
||||
|
||||
#print "Here is local_data";
|
||||
#print local_data;
|
||||
|
||||
event Metrics::cluster_filter_response(uid, id, filter_name, local_data, done);
|
||||
if ( ! done )
|
||||
|
|
@ -148,7 +137,7 @@ event Metrics::send_data(uid: string, id: string, filter_name: string, data: Met
|
|||
|
||||
event Metrics::cluster_filter_request(uid: string, id: string, filter_name: string)
|
||||
{
|
||||
#print fmt("WORKER %s: received the cluster_filter_request event.", Cluster::node);
|
||||
#print fmt("WORKER %s: received the cluster_filter_request event for %s.", Cluster::node, id);
|
||||
|
||||
# Initiate sending all of the data for the requested filter.
|
||||
event Metrics::send_data(uid, id, filter_name, store[id, filter_name]);
|
||||
|
|
@ -160,12 +149,12 @@ event Metrics::cluster_filter_request(uid: string, id: string, filter_name: stri
|
|||
|
||||
event Metrics::cluster_index_request(uid: string, id: string, filter_name: string, index: Index)
|
||||
{
|
||||
local data: DataPoint;
|
||||
if ( index in store[id, filter_name] )
|
||||
data = store[id, filter_name][index];
|
||||
|
||||
# fmt("WORKER %s: received the cluster_index_request event for %s=%d.", Cluster::node, index2str(index), val);
|
||||
event Metrics::cluster_index_response(uid, id, filter_name, index, data);
|
||||
if ( [id, filter_name] in store && index in store[id, filter_name] )
|
||||
{
|
||||
local data = store[id, filter_name][index];
|
||||
#print fmt("WORKER %s: received the cluster_index_request event for %s=%s.", Cluster::node, index2str(index), data);
|
||||
event Metrics::cluster_index_response(uid, id, filter_name, index, data);
|
||||
}
|
||||
}
|
||||
|
||||
@endif
|
||||
|
|
@ -177,7 +166,6 @@ event Metrics::cluster_index_request(uid: string, id: string, filter_name: strin
|
|||
event Metrics::log_it(filter: Filter)
|
||||
{
|
||||
#print fmt("%.6f MANAGER: breaking %s filter for %s metric", network_time(), filter$name, filter$id);
|
||||
|
||||
local uid = unique_id("");
|
||||
|
||||
# Set some tracking variables.
|
||||
|
|
@ -187,39 +175,44 @@ event Metrics::log_it(filter: Filter)
|
|||
# Request data from peers.
|
||||
event Metrics::cluster_filter_request(uid, filter$id, filter$name);
|
||||
# Schedule the log_it event for the next break period.
|
||||
schedule filter$break_interval { Metrics::log_it(filter) };
|
||||
schedule filter$every { Metrics::log_it(filter) };
|
||||
}
|
||||
|
||||
# This is unlikely to be called often, but it's here in case there are metrics
|
||||
# being collected by managers.
|
||||
function data_added(filter: Filter, index: Index, val: count)
|
||||
function data_added(filter: Filter, index: Index, val: ResultVal)
|
||||
{
|
||||
if ( check_threshold(filter, index, val) )
|
||||
threshold_crossed_alert( filter, index, val );
|
||||
#do_notice(filter, index, val);
|
||||
if ( check_thresholds(filter, index, val, 1.0) )
|
||||
threshold_crossed(filter, index, val);
|
||||
}
|
||||
|
||||
event Metrics::cluster_index_response(uid: string, id: string, filter_name: string, index: Index, data: DataPoint)
|
||||
event Metrics::cluster_index_response(uid: string, id: string, filter_name: string, index: Index, val: ResultVal)
|
||||
{
|
||||
#print fmt("%0.6f MANAGER: receiving index data from %s", network_time(), get_event_peer()$descr);
|
||||
#print fmt("%0.6f MANAGER: receiving index data from %s - %s=%s", network_time(), get_event_peer()$descr, index2str(index), val);
|
||||
|
||||
index_requests[uid, id, filter_name, index] = merge_data_points(index_requests[uid, id, filter_name, index], data);
|
||||
local merged_val = merge_result_vals(index_requests[uid, id, filter_name, index], val);
|
||||
index_requests[uid, id, filter_name, index] = merged_val;
|
||||
local ir = index_requests[uid, id, filter_name, index];
|
||||
|
||||
# Mark that this worker is done.
|
||||
++done_with[uid];
|
||||
|
||||
#print ir;
|
||||
#print fmt("worker_count:%d :: done_with:%d", Cluster::worker_count, done_with[uid]);
|
||||
|
||||
if ( Cluster::worker_count == done_with[uid] )
|
||||
{
|
||||
local size = ir?$num ? ir$num : |ir$unique_vals|;
|
||||
if ( check_threshold(filter_store[id, filter_name], index, size) )
|
||||
threshold_crossed_alert( filter_store[id, filter_name], index, size );
|
||||
#do_notice(filter_store[id, filter_name], index, size);
|
||||
if ( check_thresholds(filter_store[id, filter_name], index, ir, 1.0) )
|
||||
{
|
||||
threshold_crossed(filter_store[id, filter_name], index, ir);
|
||||
}
|
||||
delete done_with[uid];
|
||||
delete index_requests[uid, id, filter_name, index];
|
||||
}
|
||||
}
|
||||
|
||||
# Managers handle intermediate updates here.
|
||||
event Metrics::cluster_index_intermediate_response(id: string, filter_name: string, index: Index, val: count)
|
||||
event Metrics::cluster_index_intermediate_response(id: string, filter_name: string, index: Index)
|
||||
{
|
||||
#print fmt("MANAGER: receiving intermediate index data from %s", get_event_peer()$descr);
|
||||
#print fmt("MANAGER: requesting index data for %s", index2str(index));
|
||||
|
|
@ -237,12 +230,12 @@ event Metrics::cluster_filter_response(uid: string, id: string, filter_name: str
|
|||
for ( index in data )
|
||||
{
|
||||
if ( index in local_data )
|
||||
local_data[index] = merge_data_points(local_data[index], data[index]);
|
||||
local_data[index] = merge_result_vals(local_data[index], data[index]);
|
||||
else
|
||||
local_data[index] = data[index];
|
||||
}
|
||||
|
||||
# Mark another worker as being "done" for this uid.
|
||||
# Mark another worker as being "done" for this uid.
|
||||
if ( done )
|
||||
++done_with[uid];
|
||||
|
||||
|
|
|
|||
|
|
@ -1,7 +1,5 @@
|
|||
##! The metrics framework provides a way to count and measure data.
|
||||
|
||||
@load base/frameworks/notice
|
||||
|
||||
module Metrics;
|
||||
|
||||
export {
|
||||
|
|
@ -11,15 +9,21 @@ export {
|
|||
## The default interval used for "breaking" metrics and writing the
|
||||
## current value to the logging stream.
|
||||
const default_break_interval = 15mins &redef;
|
||||
|
||||
## The default number of metric items which trigger
|
||||
## filter$custom_check_threshold
|
||||
const default_trigger_custom_check_threshold = 10 &redef;
|
||||
|
||||
## This is the interval for how often threshold based notices will happen
|
||||
## after they have already fired.
|
||||
const threshold_series_restart_interval = 1hr &redef;
|
||||
|
||||
type Calculation: enum {
|
||||
SUM,
|
||||
MIN,
|
||||
MAX,
|
||||
VARIANCE,
|
||||
STD_DEV,
|
||||
AVG,
|
||||
UNIQUE,
|
||||
};
|
||||
|
||||
## Represents a thing which is having metrics collected for it. An instance
|
||||
## of this record type and an id together represent a single measurement.
|
||||
type Index: record {
|
||||
|
|
@ -40,12 +44,47 @@ export {
|
|||
network: subnet &optional;
|
||||
} &log;
|
||||
|
||||
## Represents data being added for a single metric data point. Used internally.
|
||||
## Represents data being added for a single metric data point.
|
||||
type DataPoint: record {
|
||||
num: count &optional;
|
||||
unique_vals: set[string] &optional;
|
||||
num: count &optional;
|
||||
dbl: double &optional;
|
||||
str: string &optional;
|
||||
};
|
||||
|
||||
|
||||
## Value supplied when a metric is finished. It contains all
|
||||
## of the measurements collected for the metric.
|
||||
type ResultVal: record {
|
||||
## The number of measurements received.
|
||||
num: count &log &default=0;
|
||||
|
||||
## For numeric data, this tracks the sum of all values.
|
||||
sum: double &log &optional;
|
||||
|
||||
## For numeric data, this tracks the minimum value given.
|
||||
min: double &log &optional;
|
||||
|
||||
## For numeric data, this tracks the maximum value given.
|
||||
max: double &log &optional;
|
||||
|
||||
## For numeric data, this calculates the average of all values.
|
||||
avg: double &log &optional;
|
||||
|
||||
## For numeric data, this calculates the variance.
|
||||
variance: double &log &optional;
|
||||
|
||||
## For numeric data, this calculates the standard deviation.
|
||||
std_dev: double &log &optional;
|
||||
|
||||
## If cardinality is being tracked, the number of unique
|
||||
## items is tracked here.
|
||||
unique: count &log &optional;
|
||||
|
||||
## A sample of something being measured. This is helpful in
|
||||
## some cases for collecting information to do further detection
|
||||
## or better logging for forensic purposes.
|
||||
sample: set[DataPoint] &optional;
|
||||
};
|
||||
|
||||
## The record type that is used for logging metrics.
|
||||
type Info: record {
|
||||
## Timestamp at which the metric was "broken".
|
||||
|
|
@ -57,67 +96,58 @@ export {
|
|||
## the data so this is necessary to understand the value.
|
||||
filter_name: string &log;
|
||||
## What measurement the metric represents.
|
||||
metric_id: string &log;
|
||||
metric: string &log;
|
||||
## What the metric value applies to.
|
||||
index: Index &log;
|
||||
## The simple numeric value of the metric.
|
||||
value: count &log;
|
||||
result: ResultVal &log;
|
||||
};
|
||||
|
||||
# TODO: configure a metrics filter logging stream to log the current
|
||||
# metrics configuration in case someone is looking through
|
||||
# old logs and the configuration has changed since then.
|
||||
|
||||
## Filters define how the data from a metric is aggregated and handled.
|
||||
## Filters can be used to set how often the measurements are cut or "broken"
|
||||
## Filters can be used to set how often the measurements are cut
|
||||
## and logged or how the data within them is aggregated. It's also
|
||||
## possible to disable logging and use filters for thresholding.
|
||||
## possible to disable logging and use filters solely for thresholding.
|
||||
type Filter: record {
|
||||
## The name for this filter so that multiple filters can be
|
||||
## applied to a single metrics to get a different view of the same
|
||||
## metric data being collected (different aggregation, break, etc).
|
||||
name: string &default="default";
|
||||
## The :bro:type:`Metrics::ID` that this filter applies to.
|
||||
id: string &optional;
|
||||
name: string &default="default";
|
||||
## The metric that this filter applies to.
|
||||
id: string &optional;
|
||||
## The measurements to perform on the data.
|
||||
measure: set[Calculation] &optional;
|
||||
## A predicate so that you can decide per index if you would like
|
||||
## to accept the data being inserted.
|
||||
pred: function(index: Index, str: string): bool &optional;
|
||||
## A function to normalize the index. This can be used to normalize
|
||||
## any field in the index and is likely most useful to normalize
|
||||
## the $str field.
|
||||
normalize_func: function(index: Index): Index &optional;
|
||||
## Global mask by which you'd like to aggregate traffic.
|
||||
aggregation_mask: count &optional;
|
||||
## This is essentially a mapping table between addresses and subnets.
|
||||
aggregation_table: table[subnet] of subnet &optional;
|
||||
pred: function(index: Metrics::Index, data: DataPoint): bool &optional;
|
||||
## A function to normalize the index. This can be used to aggregate or
|
||||
## normalize the entire index.
|
||||
normalize_func: function(index: Metrics::Index): Index &optional;
|
||||
## Global mask by to aggregate traffic measuring an attribute of hosts.
|
||||
## This is a special case of the normalize_func.
|
||||
aggregation_mask: count &optional;
|
||||
## The interval at which this filter should be "broken" and written
|
||||
## to the logging stream. The counters are also reset to zero at
|
||||
## this time so any threshold based detection needs to be set to a
|
||||
## number that should be expected to happen within this period.
|
||||
break_interval: interval &default=default_break_interval;
|
||||
every: interval &default=default_break_interval;
|
||||
## This determines if the result of this filter is sent to the metrics
|
||||
## logging stream. One use for the logging framework is as an internal
|
||||
## thresholding and statistics gathering utility that is meant to
|
||||
## never log but rather to generate notices and derive data.
|
||||
log: bool &default=T;
|
||||
## A straight threshold for generating a notice.
|
||||
default_threshold: count &optional;
|
||||
log: bool &default=T;
|
||||
## A direct threshold for calling the $threshold_crossed function when
|
||||
## the SUM is greater than or equal to this value.
|
||||
threshold: count &optional;
|
||||
## A series of thresholds for calling the $threshold_crossed function.
|
||||
threshold_series: vector of count &optional;
|
||||
## A predicate so that you can decide when to flexibly declare when
|
||||
## a threshold crossed, and do extra stuff
|
||||
custom_check_threshold: function(index: Index, default_thresh: count,
|
||||
val: count ): bool &optional;
|
||||
## Even if custom_check_threshold has been defined, we don't want
|
||||
## to call it every time because of function call overhead.
|
||||
## Metrics::Filter$trigger_custom_check_threshold describes how often
|
||||
## custom_check_threshold will be called
|
||||
## e.g. call custom_check_threshold for every 10 items seen by the metrics fw
|
||||
trigger_custom_check_threshold: count &default=default_trigger_custom_check_threshold;
|
||||
## A predicate that is called whenever a threshold is crossed
|
||||
## ToDo: Also have a parameter here that is a sample of the
|
||||
## observed trackable items
|
||||
threshold_crossed: function(index: Index, val: count );
|
||||
## A series of thresholds at which to generate notices.
|
||||
threshold_series: vector of count &optional;
|
||||
## a threshold crossed, and do extra work.
|
||||
threshold_func: function(index: Metrics::Index, val: Metrics::ResultVal): bool &optional;
|
||||
## A function callback that is called when a threshold is crossed.
|
||||
threshold_crossed: function(index: Metrics::Index, val: Metrics::ResultVal) &optional;
|
||||
## A number of sample DataPoints to collect for the threshold
|
||||
## crossing callback.
|
||||
samples: count &optional;
|
||||
};
|
||||
|
||||
## Function to associate a metric filter with a metric ID.
|
||||
|
|
@ -125,70 +155,72 @@ export {
|
|||
## id: The metric ID that the filter should be associated with.
|
||||
##
|
||||
## filter: The record representing the filter configuration.
|
||||
global add_filter: function(id: string, filter: Filter);
|
||||
global add_filter: function(id: string, filter: Metrics::Filter);
|
||||
|
||||
## Add data into a :bro:type:`Metrics::ID`. This should be called when
|
||||
## Add data into a metric. This should be called when
|
||||
## a script has measured some point value and is ready to increment the
|
||||
## counters.
|
||||
##
|
||||
## id: The metric ID that the data represents.
|
||||
## id: The metric identifier that the data represents.
|
||||
##
|
||||
## index: The metric index that the value is to be added to.
|
||||
##
|
||||
## increment: How much to increment the counter by.
|
||||
global add_data: function(id: string, index: Index, increment: count);
|
||||
|
||||
# This function does the following:
|
||||
# If index (src,) doesn't exist, it creates an entry for this index. It
|
||||
# adds data (c$id$orig_h) to a set associated with this index. If the number
|
||||
# of unique data values for an index exceeds threshold, a notice is generated.
|
||||
# So the threshold applies to the number of unique data values associated with
|
||||
# an index.
|
||||
|
||||
global add_unique: function(id: string, index: Index, data: string);
|
||||
global add_data: function(id: string, index: Metrics::Index, data: Metrics::DataPoint);
|
||||
|
||||
## Helper function to represent a :bro:type:`Metrics::Index` value as
|
||||
## a simple string
|
||||
## a simple string.
|
||||
##
|
||||
## index: The metric index that is to be converted into a string.
|
||||
##
|
||||
## Returns: A string reprentation of the metric index.
|
||||
global index2str: function(index: Index): string;
|
||||
|
||||
## Event that is used to "finish" metrics and adapt the metrics
|
||||
## framework for clustered or non-clustered usage.
|
||||
##
|
||||
## ..note: This is primarily intended for internal use.
|
||||
global log_it: event(filter: Filter);
|
||||
|
||||
global index2str: function(index: Metrics::Index): string;
|
||||
|
||||
## Event to access metrics records as they are passed to the logging framework.
|
||||
global log_metrics: event(rec: Info);
|
||||
global log_metrics: event(rec: Metrics::Info);
|
||||
|
||||
## Type to store a table of metrics values. Interal use only!
|
||||
type MetricTable: table[Index] of DataPoint;
|
||||
}
|
||||
|
||||
redef record Notice::Info += {
|
||||
metric_index: Index &log &optional;
|
||||
redef record ResultVal += {
|
||||
# Internal use only. Used for incrementally calculating variance.
|
||||
prev_avg: double &optional;
|
||||
|
||||
# Internal use only. For calculating variance.
|
||||
var_s: double &optional;
|
||||
|
||||
# Internal use only. This is not meant to be publically available
|
||||
# because we don't want to trust that we can inspect the values
|
||||
# since we will like move to a probalistic data structure in the future.
|
||||
# TODO: in the future this will optionally be a hyperloglog structure
|
||||
unique_vals: set[DataPoint] &optional;
|
||||
};
|
||||
|
||||
# Type to store a table of metrics values.
|
||||
type MetricTable: table[Index] of ResultVal;
|
||||
|
||||
# Store the filters indexed on the metric identifier.
|
||||
global metric_filters: table[string] of vector of Filter = table();
|
||||
|
||||
# Store the filters indexed on the metric identifier and filter name.
|
||||
global filter_store: table[string, string] of Filter = table();
|
||||
|
||||
# This is indexed by metric ID and stream filter name.
|
||||
# This is indexed by metric id and filter name.
|
||||
global store: table[string, string] of MetricTable = table() &default=table();
|
||||
|
||||
# This function checks if a threshold has been crossed and generates a
|
||||
# notice if it has. It is also used as a method to implement
|
||||
# mid-break-interval threshold crossing detection for cluster deployments.
|
||||
global check_threshold: function(filter: Filter, index: Index, val: count): bool;
|
||||
# This is hook for watching thresholds being crossed. It is called whenever
|
||||
# index values are updated and the new val is given as the `val` argument.
|
||||
global data_added: function(filter: Filter, index: Index, val: count);
|
||||
|
||||
# This stores the current threshold index for filters using $threshold_series.
|
||||
global threshold_series_index: table[string, string, Index] of count = {} &create_expire=threshold_series_restart_interval &default=0;
|
||||
|
||||
# This is hook for watching thresholds being crossed. It is called whenever
|
||||
# index values are updated and the new val is given as the `val` argument.
|
||||
# It's only prototyped here because cluster and non-cluster has separate
|
||||
# implementations.
|
||||
global data_added: function(filter: Filter, index: Index, val: ResultVal);
|
||||
|
||||
## Event that is used to "finish" metrics and adapt the metrics
|
||||
## framework for clustered or non-clustered usage.
|
||||
global log_it: event(filter: Metrics::Filter);
|
||||
|
||||
|
||||
event bro_init() &priority=5
|
||||
{
|
||||
Log::create_stream(Metrics::LOG, [$columns=Info, $ev=log_metrics]);
|
||||
|
|
@ -206,29 +238,91 @@ function index2str(index: Index): string
|
|||
return fmt("metric_index(%s)", out);
|
||||
}
|
||||
|
||||
function merge_data_points(dp1: DataPoint, dp2: DataPoint): DataPoint
|
||||
function do_calculated_fields(val: ResultVal)
|
||||
{
|
||||
local result: DataPoint;
|
||||
if ( dp1?$num || dp2?$num )
|
||||
if ( val?$unique_vals )
|
||||
val$unique = |val$unique_vals|;
|
||||
if ( val?$var_s )
|
||||
val$variance = (val$num > 1) ? val$var_s/val$num : 0.0;
|
||||
if ( val?$variance )
|
||||
val$std_dev = sqrt(val$variance);
|
||||
}
|
||||
|
||||
function merge_result_vals(rv1: ResultVal, rv2: ResultVal): ResultVal
|
||||
{
|
||||
local result: ResultVal;
|
||||
|
||||
# Merge $num
|
||||
result$num = rv1$num + rv2$num;
|
||||
|
||||
# Merge $sum
|
||||
if ( rv1?$sum || rv2?$sum )
|
||||
{
|
||||
result$num = 0;
|
||||
if ( dp1?$num )
|
||||
result$num += dp1$num;
|
||||
if ( dp2?$num )
|
||||
result$num += dp2$num;
|
||||
result$sum = 0;
|
||||
if ( rv1?$sum )
|
||||
result$sum += rv1$sum;
|
||||
if ( rv2?$sum )
|
||||
result$sum += rv2$sum;
|
||||
}
|
||||
|
||||
if ( dp1?$unique_vals || dp2?$unique_vals )
|
||||
|
||||
# Merge $max
|
||||
if ( rv1?$max && rv2?$max )
|
||||
result$max = (rv1$max > rv2$max) ? rv1$max : rv2$max;
|
||||
else if ( rv1?$max )
|
||||
result$max = rv1$max;
|
||||
else if ( rv2?$max )
|
||||
result$max = rv2$max;
|
||||
|
||||
# Merge $min
|
||||
if ( rv1?$min && rv2?$min )
|
||||
result$min = (rv1$min < rv2$min) ? rv1$min : rv2$min;
|
||||
else if ( rv1?$min )
|
||||
result$min = rv1$min;
|
||||
else if ( rv2?$min )
|
||||
result$min = rv2$min;
|
||||
|
||||
# Merge $avg
|
||||
if ( rv1?$avg && rv2?$avg )
|
||||
result$avg = ((rv1$avg*rv1$num) + (rv2$avg*rv2$num))/(rv1$num+rv2$num);
|
||||
else if ( rv1?$avg )
|
||||
result$avg = rv1$avg;
|
||||
else if ( rv2?$avg )
|
||||
result$avg = rv2$avg;
|
||||
|
||||
# Merge $prev_avg
|
||||
if ( rv1?$prev_avg && rv2?$prev_avg )
|
||||
result$prev_avg = ((rv1$prev_avg*rv1$num) + (rv2$prev_avg*rv2$num))/(rv1$num+rv2$num);
|
||||
else if ( rv1?$prev_avg )
|
||||
result$prev_avg = rv1$prev_avg;
|
||||
else if ( rv2?$prev_avg )
|
||||
result$prev_avg = rv2$prev_avg;
|
||||
|
||||
# Merge $var_s
|
||||
if ( rv1?$var_s && rv2?$var_s )
|
||||
{
|
||||
local rv1_avg_sq = (rv1$avg - result$avg);
|
||||
rv1_avg_sq = rv1_avg_sq*rv1_avg_sq;
|
||||
local rv2_avg_sq = (rv2$avg - result$avg);
|
||||
rv2_avg_sq = rv2_avg_sq*rv2_avg_sq;
|
||||
result$var_s = rv1$num*(rv1$var_s/rv1$num + rv1_avg_sq) + rv2$num*(rv2$var_s/rv2$num + rv2_avg_sq);
|
||||
}
|
||||
else if ( rv1?$var_s )
|
||||
result$var_s = rv1$var_s;
|
||||
else if ( rv2?$var_s )
|
||||
result$var_s = rv2$var_s;
|
||||
|
||||
if ( rv1?$unique_vals || rv2?$unique_vals )
|
||||
{
|
||||
result$unique_vals = set();
|
||||
if ( dp1?$unique_vals )
|
||||
for ( val1 in dp1$unique_vals )
|
||||
if ( rv1?$unique_vals )
|
||||
for ( val1 in rv1$unique_vals )
|
||||
add result$unique_vals[val1];
|
||||
if ( dp2?$unique_vals )
|
||||
for ( val2 in dp2$unique_vals )
|
||||
if ( rv2?$unique_vals )
|
||||
for ( val2 in rv2$unique_vals )
|
||||
add result$unique_vals[val2];
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
do_calculated_fields(result);
|
||||
return result;
|
||||
}
|
||||
|
||||
|
|
@ -236,24 +330,18 @@ function write_log(ts: time, filter: Filter, data: MetricTable)
|
|||
{
|
||||
for ( index in data )
|
||||
{
|
||||
local val = 0;
|
||||
if ( data[index]?$unique_vals )
|
||||
val = |data[index]$unique_vals|;
|
||||
else
|
||||
val = data[index]$num;
|
||||
local m: Info = [$ts=ts,
|
||||
$ts_delta=filter$break_interval,
|
||||
$metric_id=filter$id,
|
||||
$ts_delta=filter$every,
|
||||
$metric=filter$id,
|
||||
$filter_name=filter$name,
|
||||
$index=index,
|
||||
$value=val];
|
||||
$result=data[index]];
|
||||
|
||||
if ( filter$log )
|
||||
Log::write(Metrics::LOG, m);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
function reset(filter: Filter)
|
||||
{
|
||||
store[filter$id, filter$name] = table();
|
||||
|
|
@ -261,45 +349,16 @@ function reset(filter: Filter)
|
|||
|
||||
function add_filter(id: string, filter: Filter)
|
||||
{
|
||||
if ( filter?$aggregation_table && filter?$aggregation_mask )
|
||||
if ( filter?$normalize_func && filter?$aggregation_mask )
|
||||
{
|
||||
print "INVALID Metric filter: Defined $aggregation_table and $aggregation_mask.";
|
||||
Reporter::warning(fmt("invalid Metric filter (%s): Defined $normalize_func and $aggregation_mask.", filter$name));
|
||||
return;
|
||||
}
|
||||
if ( [id, filter$name] in store )
|
||||
{
|
||||
print fmt("INVALID Metric filter: Filter with name \"%s\" already exists.", filter$name);
|
||||
Reporter::warning(fmt("invalid Metric filter (%s): Filter with same name already exists.", filter$name));
|
||||
return;
|
||||
}
|
||||
if ( !filter?$threshold_series && !filter?$default_threshold )
|
||||
{
|
||||
print "INVALID Metric filter: Must define one of $default_threshold and $threshold_series";
|
||||
return;
|
||||
}
|
||||
if ( filter?$threshold_series && filter?$custom_check_threshold )
|
||||
{
|
||||
print "INVALID Metric filter: Cannot define $custom_check_threshold with $threshold_series";
|
||||
return;
|
||||
}
|
||||
if ( filter?$threshold_series && filter?$default_threshold )
|
||||
{
|
||||
print "INVALID Metric filter: Cannot define both $default_threshold and $threshold_series";
|
||||
return;
|
||||
}
|
||||
if ( filter?$custom_check_threshold && !filter?$default_threshold )
|
||||
{
|
||||
print "INVALID Metric filter: Must define $default_threshold with $custom_check_threshold";
|
||||
return;
|
||||
}
|
||||
if ( !filter?$trigger_custom_check_threshold && filter?$custom_check_threshold )
|
||||
{
|
||||
print "INVALID Metric filter: You defined $trigger_custom_check_threshold but $custom_check_threshold is missing";
|
||||
return;
|
||||
}
|
||||
if ( !filter?$trigger_custom_check_threshold && filter?$custom_check_threshold )
|
||||
{
|
||||
print "WARNING Metric filter: You did not define $trigger_custom_check_threshold (default will be used)";
|
||||
}
|
||||
|
||||
if ( ! filter?$id )
|
||||
filter$id = id;
|
||||
|
|
@ -311,10 +370,10 @@ function add_filter(id: string, filter: Filter)
|
|||
filter_store[id, filter$name] = filter;
|
||||
store[id, filter$name] = table();
|
||||
|
||||
schedule filter$break_interval { Metrics::log_it(filter) };
|
||||
schedule filter$every { Metrics::log_it(filter) };
|
||||
}
|
||||
|
||||
function add_it(id: string, index: Index, integer_value: bool, num: count, str: string)
|
||||
function add_data(id: string, index: Index, data: DataPoint)
|
||||
{
|
||||
if ( id !in metric_filters )
|
||||
return;
|
||||
|
|
@ -328,103 +387,140 @@ function add_it(id: string, index: Index, integer_value: bool, num: count, str:
|
|||
|
||||
# If this filter has a predicate, run the predicate and skip this
|
||||
# index if the predicate return false.
|
||||
if ( filter?$pred && ! filter$pred(index,str) )
|
||||
if ( filter?$pred && ! filter$pred(index, data) )
|
||||
next;
|
||||
|
||||
if ( index?$host )
|
||||
if ( filter?$normalize_func )
|
||||
index = filter$normalize_func(copy(index));
|
||||
|
||||
if ( index?$host && filter?$aggregation_mask )
|
||||
{
|
||||
if ( filter?$normalize_func )
|
||||
{
|
||||
index = filter$normalize_func(copy(index));
|
||||
}
|
||||
|
||||
if ( filter?$aggregation_mask )
|
||||
{
|
||||
index$network = mask_addr(index$host, filter$aggregation_mask);
|
||||
delete index$host;
|
||||
}
|
||||
else if ( filter?$aggregation_table )
|
||||
{
|
||||
# Don't add the data if the aggregation table doesn't include
|
||||
# the given host address.
|
||||
if ( index$host !in filter$aggregation_table )
|
||||
return;
|
||||
index$network = filter$aggregation_table[index$host];
|
||||
delete index$host;
|
||||
}
|
||||
index$network = mask_addr(index$host, filter$aggregation_mask);
|
||||
delete index$host;
|
||||
}
|
||||
|
||||
local metric_tbl = store[id, filter$name];
|
||||
if ( integer_value )
|
||||
if ( index !in metric_tbl )
|
||||
metric_tbl[index] = [];
|
||||
|
||||
local result = metric_tbl[index];
|
||||
|
||||
# If a string was given, fall back to 1.0 as the value.
|
||||
local val = 1.0;
|
||||
if ( data?$num || data?$dbl )
|
||||
val = data?$dbl ? data$dbl : data$num;
|
||||
|
||||
++result$num;
|
||||
|
||||
if ( SUM in filter$measure )
|
||||
{
|
||||
if ( index !in metric_tbl )
|
||||
metric_tbl[index] = [$num=0];
|
||||
metric_tbl[index]$num += num;
|
||||
data_added(filter, index, metric_tbl[index]$num);
|
||||
if ( ! result?$sum ) result$sum = 0;
|
||||
result$sum += val;
|
||||
}
|
||||
else
|
||||
|
||||
if ( MIN in filter$measure )
|
||||
{
|
||||
if ( index !in metric_tbl )
|
||||
if ( ! result?$min )
|
||||
result$min = val;
|
||||
else if (val < result$min)
|
||||
result$min = val;
|
||||
}
|
||||
|
||||
if ( MAX in filter$measure )
|
||||
{
|
||||
if ( ! result?$max )
|
||||
result$max = val;
|
||||
else if (val > result$max)
|
||||
result$max = val;
|
||||
}
|
||||
|
||||
if ( AVG in filter$measure || VARIANCE in filter$measure )
|
||||
{
|
||||
if ( ! result?$avg )
|
||||
{
|
||||
local empty_ss: set[string] = set();
|
||||
metric_tbl[index] = [$unique_vals=empty_ss];
|
||||
result$avg = val;
|
||||
result$prev_avg = val;
|
||||
}
|
||||
else
|
||||
{
|
||||
result$prev_avg = result$avg;
|
||||
result$avg += (val - result$avg) / result$num;
|
||||
}
|
||||
add metric_tbl[index]$unique_vals[str];
|
||||
#print metric_tbl[index]$unique_vals;
|
||||
#print "-------------------------------------";
|
||||
data_added(filter, index, |metric_tbl[index]$unique_vals|);
|
||||
}
|
||||
|
||||
if ( VARIANCE in filter$measure )
|
||||
{
|
||||
if ( ! result?$var_s ) result$var_s = 0.0;
|
||||
result$var_s += (val - result$prev_avg)*(val - result$avg);
|
||||
}
|
||||
|
||||
if ( STD_DEV in filter$measure )
|
||||
{
|
||||
#if ( result?$variance )
|
||||
# result$std_dev = sqrt(result$variance);
|
||||
}
|
||||
|
||||
if ( UNIQUE in filter$measure )
|
||||
{
|
||||
if ( ! result?$unique_vals ) result$unique_vals=set();
|
||||
add result$unique_vals[data];
|
||||
}
|
||||
|
||||
do_calculated_fields(result);
|
||||
data_added(filter, index, result);
|
||||
}
|
||||
}
|
||||
|
||||
function add_data(id: string, index: Index, increment: count)
|
||||
# This function checks if a threshold has been crossed and generates a
|
||||
# notice if it has. It is also used as a method to implement
|
||||
# mid-break-interval threshold crossing detection for cluster deployments.
|
||||
function check_thresholds(filter: Filter, index: Index, val: ResultVal, modify_pct: double): bool
|
||||
{
|
||||
add_it(id, index, T, increment, "");
|
||||
}
|
||||
|
||||
function add_unique(id: string, index: Index, data: string)
|
||||
{
|
||||
add_it(id, index, F, 0, data);
|
||||
}
|
||||
|
||||
function check_threshold(filter: Filter, index: Index, val: count): bool
|
||||
{
|
||||
local def_thresh = 0;
|
||||
local watch = 0.0;
|
||||
if ( val?$unique )
|
||||
watch = val$unique;
|
||||
else if ( val?$sum )
|
||||
watch = val$sum;
|
||||
|
||||
if ( filter?$default_threshold )
|
||||
def_thresh = filter$default_threshold;
|
||||
|
||||
if ( filter?$custom_check_threshold && ( val%filter$trigger_custom_check_threshold == 0 ) )
|
||||
return filter$custom_check_threshold( index, def_thresh, val );
|
||||
if ( modify_pct < 1.0 && modify_pct > 0.0 )
|
||||
watch = watch/modify_pct;
|
||||
|
||||
# No custom check threshold defined
|
||||
else if ( !filter?$custom_check_threshold )
|
||||
if ( filter?$threshold && watch >= filter$threshold )
|
||||
{
|
||||
if ( filter?$default_threshold )
|
||||
{
|
||||
if ( val > def_thresh)
|
||||
return T;
|
||||
}
|
||||
|
||||
else if ( filter?$threshold_series )
|
||||
{
|
||||
if ( |filter$threshold_series| >= threshold_series_index[filter$id, filter$name, index] &&
|
||||
val >= filter$threshold_series[threshold_series_index[filter$id, filter$name, index]] )
|
||||
return T;
|
||||
}
|
||||
# A default threshold was given and the value crossed it.
|
||||
return T;
|
||||
}
|
||||
|
||||
if ( filter?$threshold_series &&
|
||||
|filter$threshold_series| >= threshold_series_index[filter$id, filter$name, index] &&
|
||||
watch >= filter$threshold_series[threshold_series_index[filter$id, filter$name, index]] )
|
||||
{
|
||||
# A threshold series was given and the value crossed the next
|
||||
# value in the series.
|
||||
return T;
|
||||
}
|
||||
|
||||
if ( filter?$threshold_func &&
|
||||
filter$threshold_func(index, val) )
|
||||
{
|
||||
# The threshold function indicated it was crossed.
|
||||
return T;
|
||||
}
|
||||
|
||||
return F;
|
||||
}
|
||||
|
||||
function threshold_crossed_alert(filter: Filter, index: Index, val: count)
|
||||
function threshold_crossed(filter: Filter, index: Index, val: ResultVal)
|
||||
{
|
||||
if ( filter?$threshold_crossed )
|
||||
filter$threshold_crossed( index, val );
|
||||
filter$threshold_crossed(index, val);
|
||||
|
||||
# If I don't reset here, the value just keeps
|
||||
# retriggering once the threshold has been exceeded
|
||||
# retriggering once the threshold has been exceeded.
|
||||
if ( !filter?$threshold_series )
|
||||
{
|
||||
reset(filter);
|
||||
}
|
||||
else
|
||||
{
|
||||
# This just needs set to some value so that it doesn't refire the
|
||||
|
|
|
|||
|
|
@ -6,16 +6,16 @@ event Metrics::log_it(filter: Filter)
|
|||
{
|
||||
local id = filter$id;
|
||||
local name = filter$name;
|
||||
|
||||
|
||||
write_log(network_time(), filter, store[id, name]);
|
||||
reset(filter);
|
||||
|
||||
schedule filter$break_interval { Metrics::log_it(filter) };
|
||||
schedule filter$every { Metrics::log_it(filter) };
|
||||
}
|
||||
|
||||
|
||||
function data_added(filter: Filter, index: Index, val: count)
|
||||
function data_added(filter: Filter, index: Index, val: ResultVal)
|
||||
{
|
||||
if ( check_threshold(filter, index, val) )
|
||||
threshold_crossed_alert( filter, index, val );
|
||||
if ( check_thresholds(filter, index, val, 1.0) )
|
||||
threshold_crossed(filter, index, val);
|
||||
}
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue