Loggregator

Logging in the Clouds

Loggregator is the user application logging subsystem of Cloud Foundry.

Features

Loggregator allows users to:

1. Tail their application logs.
2. Dump a recent set of application logs (where recent is a configurable number of log packets).
3. Continually drain their application logs to 3rd party log archive and analysis services.
4. (Operators and administrators only) Access the firehose, which includes the combined stream of logs from all apps, plus metrics data from CF components.

Usage

First, make sure you're using the new golang based CF CLI. Once that's installed:

cf logs APP_NAME [--recent]

For example:

$ cf logs private-app
Connected, tailing...
Oct 3 15:09:26 private-app App/0 STDERR This message is on stderr at 2013-10-03 22:09:26 +0000 for private-app instance 0
Oct 3 15:09:26 private-app App/0 STDERR 204.15.2.45, 10.10.2.148 - - [03/Oct/2013 22:09:26] "GET / HTTP/1.1" 200 81 0.0010
Oct 3 15:09:26 private-app App/0 This message is on stdout at 2013-10-03 22:09:26 +0000 for private-app instance 0
Oct 3 15:09:26 private-app App/0 STDERR This message is on stderr at 2013-10-03 22:09:26 +0000 for private-app instance 0
^C

Constraints

1. Loggregator collects STDOUT & STDERR from applications. This may require configuration on the developer's side.

• Warning: the DEA logging agent expects an application to have open connections on both STDOUT and STDERR. Closing either of these (for example, by redirecting output to /dev/null) will be read by the logging agent as a misbehaving application, and it will disconnect from all sockets for that app.

1. A Loggregator outage must not affect the running application.
2. Loggregator gathers and stores logs in a best-effort manner. While undesirable, losing the current buffer of application logs is acceptable.
3. The 3rd party drain API should mimic Heroku's in order to reduce integration effort for our partners. The Heroku drain API is simply remote syslog over TCP.

Architecture

Loggregator is composed of:

• Sources: Logging agents that run on the Cloud Foundry components.
• Metron: Metron agents are co-located with sources. They collect logs and forward them to:
• Doppler: Responsible for gathering logs from the Metron agents, storing them in temporary buffers, and forwarding logs to 3rd party syslog drains.
• Traffic Controller: Handles client requests for logs. Gathers and collates messages from all Doppler servers, and provides external API and message translation (as needed for legacy APIs).

Source agents emit the logging data as protocol-buffers, and the data stays in that format throughout the system.

In a redundant CloudFoundry setup, Loggregator can be configured to survive zone failures. Log messages from non-affected zones will still make it to the end user. On AWS, availability zones could be used as redundancy zones. The following is an example of a multi zone setup with two zones.

The role of Metron is to take traffic from the various emitter sources (dea, dea-logging-agent, router, etc) and route that traffic to one or more dopplers. In the current config we route this traffic to the dopplers in the same az. The traffic is randomly distributed across dopplers.

The role of Traffic Controller is to handle inbound HTTP and WebSocket requests for log data. It does this by proxying the request to all dopplers (regardless of AZ). Since an application can be deployed to multiple AZs, its logs can potentially end up on dopplers in multiple AZs. This is why the traffic controller will attempt to connect to dopplers in each AZ and will collate the data into a single stream for the web socket client.

The traffic controller itself is stateless; an incoming request can be handled by any instance in any AZ.

Traffic controllers also exposes a firehose web socket endpoint. Connecting to this endpoint establishes connections to all dopplers, and streams logs and metrics for all applications and CF components.

Emitting Messages from other Cloud Foundry components

Cloud Foundry developers can easily add source clients to new CF components that emit messages to the doppler. Currently, there are libraries for Go and Ruby. For usage information, look at their respective READMEs.

Deploying via BOSH

Below are example snippets for deploying the DEA Logging Agent (source), Doppler, and Loggregator Traffic Controller via BOSH.

jobs:
- name: dea_next
  templates:
  - name: dea_next
    release: cf
  - name: dea_logging_agent
    release: cf
  - name: metron_agent
    release: cf
  instances: 1
  resource_pool: dea
  networks:
  - name: cf1
    default:
    - dns
    - gateway
  properties:
    dea_next:
      zone: z1
    metron_agent:
      zone: z1
    networks:
      apps: cf1

- name: doppler_z1 # Add "doppler_zX" jobs if you have runners in zX
  templates: 
  - name: doppler
    release: cf
  - name: syslog_drain_binder
    release: cf
  - name: metron_agent
    release: cf
  instances: 1  # Scale out as neccessary
  resource_pool: common
  networks:
  - name: cf1
  properties:
    doppler:
      zone: z1
    networks:
      apps: cf1

- name: loggregator_trafficcontroller_z1
  templates: 
  - name: loggregator_trafficcontroller
    release: cf
  - name: metron_agent
    release: cf
  instances: 1  # Scale out as necessary
  resource_pool: common
  networks:
  - name: cf1
  properties:
    traffic_controller:
      zone: z1 # Denoting which one of the redundancy zones this traffic controller is servicing
    metron_agent:
      zone: z1
    networks:
      apps: cf1


properties:
  loggregator:
    servers:
      z1: # A list of loggregator servers for every redundancy zone
      - 10.10.16.14
    incoming_port: 3456
    outgoing_port: 8080
    
  loggregator_endpoint: # The end point sources will connect to
    shared_secret: loggregatorEndPointSharedSecret  
    host: 10.10.16.16
    port: 3456

Configuring the Firehose

The firehose feature includes the combined stream of logs from all apps, plus metrics data from CF components, and is intended to be used by operators and adminstrators.

Access to the firehose requires a user with the doppler.firehose scope.

The "cf" UAA client needs permission to grant this custom scope to users. The configuration of the uaa job in Cloud Foundry adds this scope by default. However, if your Cloud Foundry instance overrides the properties.uaa.clients.cf property in a stub, you need to add doppler.firehose to the scope list in the properties.uaa.clients.cf.scope property.

Configuring at deployment time (via deployment manifest)

In your deployment manifest, add

properties:
  …
  uaa:
    …
    clients:
      …
      cf:
        scope: …,doppler.firehose
      …
      doppler:
        override: true
        authorities: uaa.resource
        secret: YOUR-DOPPLER-SECRET

(The properties.uaa.clients.doppler.id key should be populated automatically.) These are also set by default in cf-properties.yml.

Adding scope to a running cluster (via uaac)

Before continuing, you should be familiar with the uaac tool.

1. Ensure that doppler is a UAA client. If uaac client get doppler returns output like

  scope: uaa.none
  client_id: doppler
  resource_ids: none
  authorized_grant_types: authorization_code refresh_token
  authorities: uaa.resource

then you're set.

1. If it does not exist, run uaac client add doppler --scope uaa.none --authorized_grant_types authorization_code,refresh_token --authorities uaa.resource (and set its secret).
2. If it exists but with incorrect properties, run uaac client update doppler --scope uaa.none --authorized_grant_types "authorization_code refresh_token" --authorities uaa.resource.
3. Grant firehose access to the cf client.
4. Check the scopes assigned to cf with uaac client get cf, e.g.

```
  scope: cloud_controller.admin cloud_controller.read cloud_controller.write openid password.write scim.read scim.userids scim.write
  client_id: cf
  resource_ids: none
  authorized_grant_types: implicit password refresh_token
  access_token_validity: 600
  refresh_token_validity: 2592000
  authorities: uaa.none
  autoapprove: true
```

1. Copy the existing scope and add doppler.firehose, then update the client

```
uaac client update cf --scope "cloud_controller.admin cloud_controller.read cloud_controller.write openid password.write scim.read scim.userids scim.write doppler.firehose"
```

Consuming log and metric data

The NOAA Client library, written in Golang, can be used by Go applications to consume app log data as well as the log + metrics firehose. If you wish to write your own client application using this library, please refer to the NOAA source and documentation.

Multiple subscribers may connect to the firehose endpoint, each with a unique subscription_id. Each subscriber (in practice, a pool of clients with a common subscription_id) receives the entire stream. For each subscription_id, all data will be distributed evenly among that subscriber's client pool.

Development

The Cloud Foundry team uses GitHub and accepts contributions via pull request.

Follow these steps to make a contribution to any of our open source repositories:

1. Complete our CLA Agreement for individuals or corporations

2. Set your name and email

   git config --global user.name "Firstname Lastname"
   git config --global user.email "[email protected]"
   

3. Fork the repo (from develop branch to get the latest changes)

4. Make your changes on a topic branch, commit, and push to github and open a pull request against the develop branch.

Once your commits are approved by Travis CI and reviewed by the core team, they will be merged.

Go version support

As of version ca517531f4ef646435365996c791c5031b75fc9d, all Loggregator components are deployed to Cloud Foundry with Go 1.4. As of that revision, support for earlier versions of the language are not guaranteed.

OS X prerequisites

Use brew and do

brew install go --cross-compile-all
brew install direnv

Make sure you add the proper entry to load direnv into your shell. See brew info direnv for details. To be safe, close the terminal window that you are using to make sure the changes to your shell are applied.

Checkout

git clone https://github.com/cloudfoundry/loggregator
cd loggregator # When you cd into the loggregator dir for the first time direnv will prompt you to trust the config file
git submodule update --init

Please run bin/install-git-hooks before committing for the first time. The pre-commit hook that this installs will ensure that all dependencies are properly listed in the bosh/packages directory. (Of course, you should probably convince yourself that the hooks are safe before installing them.) Without this script, it is possible to commit a version of the repository that will not compile.

Additional go tools

Install go vet and go cover

go get golang.org/x/tools/cmd/vet
go get golang.org/x/tools/cmd/cover

Install gosub

go get github.com/vito/gosub

Running tests

bin/test

Running specific tests

export GOPATH=`pwd` #in the root of the project
go get github.com/onsi/ginkgo/ginkgo
export PATH=$PATH:$GOPATH/bin
cd src/loggregator # or any other component
ginkgo -r

Debugging

Doppler will dump information about the running goroutines to stdout if sent a USR1 signal.

goroutine 1 [running]:
runtime/pprof.writeGoroutineStacks(0xc2000bc3f0, 0xc200000008, 0xc200000001, 0xca0000c2001fcfc0)
	/home/travis/.gvm/gos/go1.1.1/src/pkg/runtime/pprof/pprof.go:511 +0x7a
runtime/pprof.writeGoroutine(0xc2000bc3f0, 0xc200000008, 0x2, 0xca74765c960d5c8f, 0x40bbf7, ...)
	/home/travis/.gvm/gos/go1.1.1/src/pkg/runtime/pprof/pprof.go:500 +0x3a
....

Editing Manifest Templates

Currently the Doppler/Metron manifest configuration lives here. Editing this file will make changes in the manifest templates in cf-release. When making changes to these templates, you should be working out of the loggregator submodule in cf-release. After changing this configuration, you will need to run the tests in root directory of cf-release with bundle exec rspec. These tests will pull values from lamb-properties in order to populate the fixtures. Necessary changes should be made in lamb-properties.