metricproxy

README

metricproxy

The SignalFx Metricproxy lets you aggregate metrics and send them to SignalFx. It is a multilingual datapoint demultiplexer that can accept time series data from the statsd, carbon, or signalfx protocols and emit those datapoints to a series of servers on the statsd, carbon, or signalfx protocol. We recommend placing the proxy either on the same server as another aggregator, such as statsd, or on a central server that is already receiving datapoints, such as graphite's carbon database.

Install and upgrade

  curl -s https://raw.githubusercontent.com/signalfx/metricproxy/master/install.sh | sudo sh
  # Config at    /etc/sfdbconfig.conf
  # Binary at    /opt/sfproxy/bin/metricproxy
  # Logs at      /var/log/sfproxy
  # PID file at  /var/run/metricproxy.pid

Running

   /etc/init.d/metricproxy start

Stopping the daemon

   /etc/init.d/metricproxy stop

Debugging

  cd /var/log/sfproxy
  tail -F *

Sizing

We are currently running 118,358 DPS (7,080,000 DPM) on a c3.2xlarge with 70% idle CPU (the metric to watch). I would recommend a server comparable to a c3.2xlarge for safety if running around 7 million DPM and a c3.xlarge for around 2-3M DPM. They can start with a server comparable to a AWS c3.xlarge and monitor idle CPU to see if they should increase to a c3.2xlarge comparable server.

Code layout

You only need to read this if you want to develop the proxy or understand the proxy's code.

The proxy is divided into two main components: forwarder and listener. The forwarder and listener are glued together by the demultiplexer.

When a listener receives a datapoint, it converts the datapoint into a basic datapoint type. This core datapoint type is then sent to the multiplexer that will send a pointer to that datapoint to each forwarder.

Sometimes there is a loss of fidelity during transmission if a listener and forwarder don't support the same options. While it's impossible to make something understand an option it does not, we don't want to forget support for this option when we translate a datapoint through the multiplexer. We work around this by sometimes encoding the raw representation of the datapoint into the Datapoint object we forward. For example, points from carbon are not only translated into our core datapoint format, but also support ToCarbonLine which allows us to directly convert the abstract datapoint into what it looked like for carbon, which allows us to forward the point to another carbon database exactly as we received it.

All message passing between forwarders, multiplexer, and listeners happen on golang's built in channel abstraction.

Development

If you want to submit patches for the proxy, make sure your code passes travis_check.sh with exit code 0. For help setting up your development enviroment, it should be enough to mirror the install steps of .travis.yml. You may need to make sure your GOPATH env variable is set correctly.

Docker

The proxy comes with a docker image that is built and deployed to quay.io. It assumes you will have a sfdbproxy.conf file cross mounted to /var/config/sfproxy/sfdbproxy.conf for the docker container.

Config file format

See the example config file for an example of how configuration looks. Configuration is a JSON file with two important fields: ListenFrom and ForwardTo.

ListenFrom

ListenFrom is where you define what services the proxy will pretend to be and what ports to listen for those services on.

collectd

You can receive data sent by CollectD by setting up a collectd endpoint. For this, you will need to specify which port to bind to. An example config:

        {
            "ListenAddr": "0.0.0.0:18000",
            "Type": "collectd"
        },

When configuring CollectD, the target URL path will be /post-collectd.

signalfx

You can pretend to be a SignalFx endpoint with the signalfx type. For this, you will need to specify which port to bind to. An example config:

        {
            "ListenAddr": "0.0.0.0:18080",
            "Type": "signalfx"
        },

carbon (for read)

You can pretend to be carbon (the graphite database) with this type. For this, you will need to specify the port to bind to. An example config:

        {
            "ListenAddr": "0.0.0.0:12003",
            "Type": "carbon"
        }

common properties

All listeners support a "Dimensions" property which is expected to be a map(string => string) and adds the dimensions to all points sent. For example:

    {
        "ListenAddr": "0.0.0.0:18080",
        "Dimensions": { "env": "prod" },
        "Type": "signalfx"
    }

ForwardTo

ForwardTo is where you define where the proxy should send datapoints. Each datapoint that comes from a ListenFrom definition will be send to each of these.

csv

You can write datapoints to a CSV file for debugging with this config. You will need to specify the filename.

        {
            "Filename": "/tmp/filewrite.csv",
            "Name": "filelocal",
            "type": "csv"
        }

carbon (for write)

You can write datapoints to a carbon server. If the point came from a carbon listener, it will write the same way the proxy saw it. Host/Port define where the carbon server is.

        {
            "Name": "ourcarbon",
            "Host": "example.com",
            "Port": 2003,
            "type": "carbon"
        },

signalfx-json

You can write datapoints to SignalFx with this endpoint. You will need to configure your auth token inside DefaultAuthToken.

        {
            "type": "signalfx-json",
            "DefaultAuthToken": "___AUTH_TOKEN___",
            "Name": "testproxy",
        },

Example configs

Basic

This config will listen for graphite metrics on port 2003 and forward them to signalfx with the token ABCD. It will also report local stats to signalfx at 1s intervals

{
  "StatsDelay": "1s",
  "LogDir": "/var/log/sfproxy",
  "ListenFrom": [
    {
      "Type": "carbon",
      "ListenAddr" : "0.0.0.0:2003",
      "Timeout" : "2m"
    },
  ],

  "ForwardTo": [
    {
      "type": "signalfx-json",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder"
    }
  ]
}

Graphite Options

This config will listen using CollectD's HTTP protocol and forward all those metrics to a single graphite listener. It will collect stats at 1s intervals. It also signals to graphite that when it creates a graphite name for a metric, it should put the 'source' (which is usually proxy) and 'forwarder' (in this case 'graphite-west') first in the graphite dot delimited name.

{
  "StatsDelay": "1s",
  "ListenFrom": [
    {
      "Type": "collectd",
      "ListenAddr" : "0.0.0.0:8081",
    },
  ],

  "ForwardTo": [
    {
      "type": "carbon",
      "DefaultAuthToken": "ABCD",
      "Host": "graphite.database.dc1.com",
      "DimensionsOrder": ["source", "forwarder"],
      "Name": "graphite-west"
    }
  ]
}

Graphite Dimensions

This config will pull dimensions out of graphite metrics if they fit the commakeys format. That format is "_METRIC_NAME_[KEY:VALUE,KEY:VALUE]". For example, "user.hit_rate[host:server1,type:production]". It also has the extra option of adding a metric type to the datapoints. For example, if one of the dimensions is "metrictype" in this config and the dimension's value is "count", then the value is sent upstream as a datapoint.Count.

It also sets the timeout on idle connections to 1 minute, from the default of 30 seconds.

{
  "StatsDelay": "1s",
  "ListenFrom": [
    {
      "Type": "carbon",
      "ListenAddr" : "0.0.0.0:2003",
      "Timeout": "1m",
      "MetricDeconstructor": "commakeys",
      "MetricDeconstructorOptions": "mtypedim:metrictype"
    },
  ],

  "ForwardTo": [
    {
      "type": "signalfx-json",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder",
    }
  ]
}

Graphite Dimensions using Regular Expressions

You can use MetricRules to extract dimensions and metric names from the dot- separated names of graphite metrics using regular expressions.

A metric will be matched to the first rule that matches the regular expression. If no groups are specified the entire metric will be used as the metric name and no dimensions will be parsed out. All groups should be named. If the named group starts with sf_metric it will be appended together to form the metric name, otherwise it will become a dimension with the name of the group name, and the value of what it matches.

For each rule, you can define the following:

1. Regex - REQUIRED - regular expression with optionally named matching groups
2. AdditionalDimensions - used to add static dimensions to every metric that matches this rule
3. MetricType - to set the specific type of metric this is; default is gauge
4. MetricName - if present this will be the first part of the metricName. If no named groups starting with sf_metric are specified, this will be the entire metric name.

e.g.

  "FallbackDeconstructor": nil,
  "MetricRules": [
    {
      "Regex": "(?P<sf_metric_0>foo.*)\\.(?P<middle>.*)(?P<sf_metric_1>\\.baz)",
      "AdditionalDimensions": {
        "key": "value"
      }
    },
    {
      "Regex": "(?P<sf_metric>counter.*)",
      "MetricType": "cumulative_counter"
    },
    {
      "Regex": "madeup.*",
      "MetricName": "synthetic.metric"
    },
    {
      "Regex": "common.*"
    }
  ]

In the above example, if you sent in the metric foo.bar.baz it would match the first rule and the metric name would become foo.baz with a dimensions of "middle":"bar", and then an additional metric with "key":"value" added and the type would be the default of gauge.

If you sent in the metric "counter.page_views" the resulting metric name would continue to be "counter.page_views" (because you named it sf_metric)_but have the type of cumulative counter. No dimensions are being extracted or added in this example.

If you sent in the metric "madeup.page_faults" the resulting metric name would be "synthetic.metric" with type gauge.

If you sent in the metric "common.page_load_max", the resulting metric name would continue to be "common.page_load_max" (because no groups were specified) of type gauge.

If you sent in the metric "albatros.cpu.idle", this would fall through and go to the FallbackDeconstructor and in this case since we're using the nil deconstructor, be rejected and won't be passed on to SignalFx.

Graphite Dimensions using Delimiters

You can use MetricRules to extract dimensions from the dot-separated names of graphite metrics.

A metric will be matched to only one matching rule. When multiple rules are provided, they are evaluated for a match to a metric in the following order:

1. The rule must contain the same number of terms as the name of the metric to be matched.
2. If there is more than one rule with the same number of terms as the metric name, then matches will be evaluated in the order in which they are defined in the config.
3. If there are no rules that match the metric name, the FallbackDeconstructor is applied. By default this is "identity": all metrics are emitted as gauges with unmodified names.

The simplest rule contains only a DimensionsMap with the same number of terms and separated by the same delimiter as the incoming metrics. In the following example, the configuration contains two rules: one that matches all metrics with four terms, and one that matches all metrics with six terms.

If the following example config were used to process a graphite metric called cassandra.cassandra23.production.thread_count, it would output the following:

metricName = thread_count
metricType = Gauge
dimensions = {service=cassandra, instance=cassandra23, tier=production}

{
  "ListenFrom": [
    {
      "Type": "carbon",
      "ListenAddr": "0.0.0.0:2003",
      "MetricDeconstructor": "delimiter",
      "MetricDeconstructorOptionsJSON": {
        "MetricRules": [
          {
            "DimensionsMap": "service.instance.tier.%"
          },
          {
            "DimensionsMap": "service.instance.tier.module.submodule.%"
          }
        ]
      }
    }
  ],
  "ForwardTo": [
    {
      "type": "signalfx-json",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder"
    }
  ]
}

You can define more complex rules for determining the name, type and dimensions of metrics to be emitted. In this next more complex example, we first define Dimensions that will be added to every datapoint ('customer: Acme'). We then explicitly define the metrics that will be sent in as counters rather than gauges (anything that ends with 'counter.count' or starts with 'counter').

Define a MetricPath separately from the DimensionsMap to match only certain metrics.

In the example below, the MetricPath kafka|cassandra.*.*.*.!database matches metrics under the following conditions:

1. If the first term of the metric name separated by '.' matches either 'kafka' or 'cassandra'
2. And the metric contains exactly 10 terms
3. And the fifth term des not match the string 'database'

The MetricPath is followed by a DimensionsMap: component.identifier.instance.-.type.tier.item.item.%.%

1. The first three terms in the metric will be mapped to dimensions as indicated in the DimensionsMap: 'component', 'identifier', and 'instance', respectively.
2. The fourth term in the metric will be ignored, since it's specified in the DimensionsMap as the default ignore character '-'.
3. The fifth and sixth terms will be mapped to dimensions 'type' and 'tier', respectively.
4. The seventh and eighth terms will be concatenated together delimited by the default separator character '.', because they are both mapped to the dimension called 'item'.
5. The ninth and tenth terms are '%', the default metric character, which indicates that they should be used for the metric name.

This config also contains MetricName, the value of which will be prefixed onto the name of every metric emitted.

Finally, note that the MetricPath contains five terms, but the DimensionsMap contains ten. This means that the MetricPath implicitly contains five additional metric terms that are '*' (match anything).

If this config were used to process a metric named cassandra.bbac.23.foo.primary.prod.nodefactory.node.counter.count, it would output the following:

metricName = tiered.counter.count
metricType = counter
dimensions = {customer=Acme, component=cassandra, identifier=bbac,
              instance=23, type=primary, tier=prod, item=nodefactory.node,
              business_unit=Coyote}

{
  "ListenFrom": [
    {
      "Type": "carbon",
      "ListenAddr": "0.0.0.0:2003",
      "MetricDeconstructor": "delimiter",
      "MetricDeconstructorOptionsJSON": {
        "Dimensions": {
          "customer": "Acme"
        },
        "TypeRules": [
          {
            "MetricType": "count",
            "EndsWith": "counter.count"
          },
          {
            "MetricType": "cumulative_counter",
            "StartsWith": "counter"
          }
        ],
        "FallbackDeconstructor": "nil",
        "MetricRules": [
          {
            "MetricPath": "kafka|cassandra.*.*.*.!database",
            "DimensionsMap": "component.identifier.instance.-.type.tier.item.item.%.%",
            "Dimensions": {
              "business_unit": "Coyote"
            },
            "MetricName": "tiered"
          }
        ]
      }
    }
  ],
  "ForwardTo": [
    {
      "type": "signalfx-json",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder"
    }
  ]
}

The following is a full list of overrideable options and their defaults:

// For the top level
{
  "Delimiter":".",
  "Globbing":"*",
  "OrDelimiter":"|",
  "NotDelimiter":"!",
  "IgnoreDimension":"-",
  "MetricIdentifer":"%",
  "DefaultMetricType":"Gauge",
  "FallbackDeconstructor":"identity",
  "FallbackDeconstructorConfig":"",
  "TypeRules":[],
  "MetricRules":[],
  "Dimensions":{}
}
// A MetricRule
{
  "MetricType":"Gauge", // overrides the DefaultMetricType or TypeRules
  "MetricPath":"",
  "DimensionsMap":"",
  "MetricName":"",
  "Dimensions":{}
}
// A TypeRule. If StartsWith and EndsWith are both specified, they must both match.
{
  "MetricType":"Gauge",
  "StartsWith":"",
  "EndsWith":""
}

SignalFx perf options

This config listens for carbon data on port 2003 and forwards it to signalfx using an internal datapoint buffer size of 1,000,000 and sending with 50 threads simultaniously with each thread sending no more than 5,000 points in a single call. It also turns on debug logging, which will spew a large number of log messages. Only use debug logging temporarily.

{
  "StatsDelay": "1s",
  "LogLevel": "debug",
  "ListenFrom": [
    {
      "Type": "carbon",
      "ListenAddr" : "0.0.0.0:2003"
    },
  ],

  "ForwardTo": [
    {
      "type": "signalfx-json",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder",
      "BufferSize": 1000000,
      "DrainingThreads": 50,
      "MaxDrainSize": 5000
    }
  ]
}

CollectD listener dimensions

The CollectD listener supports setting dimensions on all recieved metrics with the Dimensions attribute which expects a map of string => string.

{
  "StatsDelay": "1s",
  "ListenFrom": [
    {
      "Type": "collectd",
      "ListenAddr" : "0.0.0.0:8081",
      "Dimensions" : {"hello": "world"}
    },
  ],

  "ForwardTo": [
    {
      "type": "carbon",
      "DefaultAuthToken": "ABCD",
      "Host": "graphite.database.dc1.com",
      "DimensionsOrder": ["source", "forwarder"],
      "Name": "graphite-west"
    }
  ]
}

SignalFx to SignalFx

This config listens using the signalfx protocol, buffers, then forwards points to signalfx.

{
  "StatsDelay": "1s",
  "ListenFrom": [
    {
      "Type": "signalfx",
      "ListenAddr" : "0.0.0.0:8080",
    },
  ],

  "ForwardTo": [
    {
      "type": "signalfx-json",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder",
    }
  ]
}

Teeing a subset of metrics on a forwarder

The config listens on signalfx and graphite, and forwards everything to graphite, and a smaller subset (excludes anything starting with cpu) to SignalFx. Below any metric starting with cpu will be denied, except for cpu.idle. If only allow was specificed, those that matched would be allowed and those that failed would be denied. If only deny was provided those that matched would be denied and those that were not would be allowed.

{
  "StatsDelay": "1s",
  "LogDir": "/tmp",
  "ListenFrom": [
    {
      "Type": "carbon",
      "ListenAddr": "0.0.0.0:2003"
    },
    {
      "Type": "signalfx",
      "ListenAddr": "0.0.0.0:8080"
    }
  ],
  "ForwardTo": [
    {
      "type": "carbon",
      "Name": "ourcarbon",
      "Host": "example.com",
      "Port": 2003
    },
    {
      "type": "signalfx-json",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder",
      "Filters": {
        "Deny": [
          "^cpu"
        ],
        "Allow": [
          "^cpu.idle$"
        ]
      }
    }
  ]
}

Status Page and profiling

This config only loads a status page. You can see configuration information at http://localhost:6009/debug/vars, explore the objects in memory at http://localhost:6009/debug/explorer/, and pprof information at http://localhost:6009/debug/pprof/. You can learn more about pprof for golang on the pprof help page.

{
  "LocalDebugServer": "0.0.0.0:6009"
}

Health checks

Health checks are available on the listening port of any collectd or signalfx listener. E.g. If you had a signalfx listener at 8080, the healthcheck would be located at http://localhost:8080/healthz. Healthchecks are useful when putting the proxy behind a loadbalancer.

Graceful Shutdown

The below config specifies what are the default values for the graceful shutdown parameters. Upon receiving a SIGTERM, the graceful shutdown procedure will close all health checks to prevent a loadbalancer from initiating any new connections. Now it will check every GracefulCheckInterval to see if the number of in flight datapoints and events is 0. If it then stays 0 for SilentGracefulTime, or the entire graceful shutdown takes longer than MaxGracefulWaitTime the listeners and forwarders will be closed and the process will exit.

If yo're in front of a load balancer we recommend a MaxGracefulWaitTime of "30s". This gives the lb time to hit the health check and divert traffic.

If you're not in front of a load balancer you will always hit the MaxGracefulWaitTime so you probably want to set that to something low like 1s. The config below is this use case.

{
  "MaxGracefulWaitTime": "1s",
  "GracefulCheckInterval": "1s",
  "SilentGracefulTime": "2s",
  "StatsDelay": "1s",
  "LogDir": "/tmp",
  "ListenFrom": [
    {
      "Type": "carbon",
      "ListenAddr": "0.0.0.0:2003"
    },
    {
      "Type": "signalfx",
      "ListenAddr": "0.0.0.0:8080"
    }
  ],
  "ForwardTo": [
    {
      "type": "signalfx-json",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder"
    }
  ]
}

Debugging connections via headers

Setup a debug config

{
  "DebugFlag": "secretdebug",
  "ForwardTo": [
    {
      "type": "signalfx-json",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder",
    }
}

Then, send a request with the debug header set to secretdebug.

curl -H "X-Debug-Id:secretdebug" -H "Content-Type: application/json" -XPOST \
   -d '{"gauge": [{"metric":"bob", "dimensions": {"org":"dev"}, "value": 3}]}' localhost:8080/v2/datapoint

The config will tell the HTTP request to debug each datapoint sent with X-Debug-Id set to secretdebug and log statements will show when each item is through the proxy pipeline.

Debugging connections via debug dimensions

Setup a local debug server, then you can configure which dimensions are logged out.

{
  "LocalDebugServer": "0.0.0.0:6060",
  "ForwardTo": [
    {
      "type": "signalfx-json",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder",
    }
}

Then set which dimensions to debug via a POST.

curl -XPOST -d '{"org":"dev"}' localhost:6060/debug/dims

Then, any datapoints with the "org" dimension of "dev" will be logged.