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 carbon (Graphite), collectd or SignalFx protocols and emit those datapoints to a series of servers using the carbon, collectd or SignalFx protocols. We recommend placing the proxy either on the same server as another existing metrics aggregator or on a central server that is already receiving datapoints, such as Graphite's carbon database.

$ 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

Additional Steps are required to install the metricproxy on Ubuntu machines because the golang package in Ubuntu is not up to date. The following steps to update the golang package on Ubuntu must be executed before running the install script.

sudo add-apt-repository ppa:gophers/archive
sudo apt-get update
sudo apt-get install golang-1.11.1

If /usr/bin/go does NOT exist then create a symbolic link

sudo ln /usr/lib/go-1.11.1/bin/go /usr/bin/go

Or if /usr/bin/go does exist, then overwrite the older binary

sudo cp /usr/lib/go-1.11.1/bin/go /usr/bin/go

/etc/init.d/metricproxy start

/etc/init.d/metricproxy stop

cd /var/log/sfproxy
tail -F *

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. One can start with a server comparable to a c3.xlarge and monitor idle CPU to see if this should be increased to a c3.2xlarge comparable server.

The go http code supports the use of an http proxy through the environment variable HTTP_PROXY="http://proxyhost:proxyport". With this the metricproxy will proxy all http connections through that host and port. This can be put into the start script, or as part of the environment sent into the container if using a container solution like maestro.

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.

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.

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.

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

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.

You can expose a SignalFx endpoint with the signalfx type. A SignalFx endpoint can listen on all the signalfx protocols in both "Protocol Buffers" and "JSON" for events and datapoints (e.g. /v2/datapoint, /v2/event). It can also listen on the collectd protocol (/v1/collectd).

Additionally, this listener will expose a /v1/trace endpoint to ingest trace spans. Both Jaeger's Thrift wire format and Zipkin's JSON formats (v1 and v2) are supported.

For this, you will need to specify which port to bind to. An example config:

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

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"
        }

You can optionally choose to listen to carbon over UDP as well (as opposed to the default of TCP).

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

You can use the metricproxy as prometheus remote storage. To do this, you will need to specify the port to bind to. An example config:

        {
            "ListenAddr": "0.0.0.0:12003",
            "Type": "prometheus",
            "ListenPath": "/write"
        }

...and then add the following to your prometheus.yml:

remote_write:
  - url: "http://hostname:12003/write"

If you want someting different than the default endpoint of "/write" you can specify it with "ListenPath". An alternative example config:

        {
            "ListenAddr": "0.0.0.0:12003",
            "Type": "prometheus",
            "ListenPath": "/receive"
        }

...and then add the following to your prometheus.yml:

remote_write:
  - url: "http://hostname:12003/receive"

You can send wavefront metrics to signalfx through our proxy in the same fashion as you would have sent them to the wavefront proxy. You will need to specify the port to bind to. An example config:

        {
            "ListenAddr": "0.0.0.0:12878",
            "Type": "wavefront",
            "ExtractCollectdDimensions": "false"
        }

You can optionally choose to decode dimensions like we do from collectd style metrics (although it's applied to all metrics coming in) by changing ExtractCollectdDimensions to true. Default is true. If you were encoding dimensions using the [foo=bar] sytnax inside instance and host fields, this will continue to give you the dimensions you expect.

        {
            "ListenAddr": "0.0.0.0:12878",
            "Type": "wavefront",
            "ExtractCollectdDimensions": "true"
        }

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 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.

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"
        }

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"
        }

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

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

By default gzip compression talking to SignalFx is turned on, if for some reason you want to turn it off you can disable it in the SigalFx forward config like this:

        {
            "type": "signalfx",
            "DefaultAuthToken": "___AUTH_TOKEN___",
            "Name": "testproxy",
            "DisableCompression" :true
        }

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",
      "ConnectionTimeout" : "2m"
    }
  ],

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

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"
    }
  ]
}

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",
      "ConnectionTimeout": "1m",
      "MetricDeconstructor": "commakeys",
      "MetricDeconstructorOptions": "mtypedim:metrictype"
    }
  ],

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

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.

{
  "Type": "carbon",
  "ListenAddr": "0.0.0.0:2003",
  "MetricDeconstructor": "regex",
  "MetricDeconstructorOptionsJSON": {
    "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.

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",
      "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": "counter",
            "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",
      "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":""
}

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.

StatsDelay being set to 1s means every 1s we'll emit metrics out all forwarders about the running metric proxy.

Also note that we're setting LateThreshold and FutureThreshold to 1s. This means we'll count datapoints, events and spans that exceed those thresholds (if set) and log them up to one per second. When you've turned on as described immediately above you'll see metrics named late.count and future.count emitted counting each type of data that was late or in the future respectively.

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

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

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"
    }
  ]
}

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",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder"
    }
  ]
}

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",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder",
      "Filters": {
        "Deny": [
          "^cpu"
        ],
        "Allow": [
          "^cpu.idle$"
        ]
      }
    }
  ]
}

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 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.

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",
      "DefaultAuthToken": "ABCD",
      "Name": "signalfxforwarder"
    }
  ]
}

Setup a debug config

{
  "DebugFlag": "secretdebug",
  "ForwardTo": [
    {
      "type": "signalfx",
      "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.

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

{
  "LocalDebugServer": "0.0.0.0:6060",
  "ForwardTo": [
    {
      "type": "signalfx",
      "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.