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Echo

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Echo serves as two purposes within Spinnaker:

  1. a router for events (e.g. a new build is detected by Igor which should trigger a pipeline)
  2. a scheduler for CRON triggered pipelines.

The following high level diagram shows how events flow through echo:
echo high level architecture

  1. igor sends events to echo when it discovers a delta in a service that it monitors (see igor readme for more details)
    e.g. A new build has completed or a new docker image was found in the docker registry

  2. gate sends events to echo as a result of user triggered actions
    e.g. User manually kicks off a pipeline from the UI (deck) or a user submit a pipeline or an orchestration for execution via the API (gate)

  3. swabbie sent a notification request to echo e.g. A resource is about to be deleted and swabbie would like an email notification to be sent out to the owner

  4. echo submits the pipeline/orchestration to orca for execution

  5. orca sends events to echo when:

    • a stage is starting/completed so echo can send notifications if any are defined on the stage
    • a pipeline (or orchestration) is starting/completed so echo can send notification as above
    • a manual judgement stage is reached - a notifcation from the user has clicked the page button on the application page
  6. echo uses external services (e.g. email/slack) to send notifications.
    Notifications can either be a result of an event received by echo (e.g. stage completed which has a notification on completion), or a specific notification request from another service (e.g. orca will send a notifcation for Manual Judgement stage)

  7. echo can also send events to any URL (à la webhook style)

Outgoing Events

Echo provides integrations for outgoing notifications in the echo-notifications package via:

  • email
  • Slack
  • Bearychat
  • Google Chat
  • Microsoft Teams
  • sms (via Twilio)
  • PagerDuty

Echo is also able to send events within Spinnaker to a predefined url, which is configurable under the echo-rest module.

You can extend the way in which echo events are sent by implementing the EventListener interface.

Event Types

Currently, echo receives build events from igor and orchestration events from orca.

Incoming Events

Echo also integrates with igor, front50 and orca to trigger pipeline executions.

It does so via two modules:

  • pipeline-triggers: Responsible firing off events from Jenkins Triggers
  • scheduler: Triggers pipelines off cron expressions. Support for cron expressions is provided by quartz

Running Echo

This can be done locally via ./gradlew bootRun, which will start with an embedded cassandra instance. Or by following the instructions using the Spinnaker installation scripts.

Debugging

To start the JVM in debug mode, set the Java system property DEBUG=true:

./gradlew -DDEBUG=true

The JVM will then listen for a debugger to be attached on port 8189. The JVM will not wait for the debugger to be attached before starting Echo; the relevant JVM arguments can be seen and modified as needed in build.gradle.

Configuration

echo can run in two modes: in-memory and SQL.

In-memory mode keeps all CRON trigger information in RAM.
While this is simpler to configure (this is the default) the in-memory mode does not provide for any redundancy because it requires that a single instance of echo scheduler be running. If there are multiple instances, they will all attempt to start executions for a given CRON trigger. There is no locking, leader election, or any other kind of coordination between scheduler instances using the in-memory mode.
If/when this single instance goes down, CRON triggers will not fire.

SQL mode keeps all CRON trigger information in a single SQL database. This allows for multiple echo scheduler instances to run providing redundancy (only one instance will trigger a given CRON).

To run in SQL mode you will need to initialize the database and provide a connection string in echo.yml (note these instructions assume MySQL).

  1. Create a database.
  2. Initialize the database by running the script (MySQL dialect provided here)
  3. Configure the SQL mode in echo.yml (obviously, change the connection strings below):
    sql:
      enabled: true
      connectionPool:
        jdbcUrl: jdbc:mysql://localhost:3306/echo?serverTimezone=UTC
        user: echo_service
      migration:
        jdbcUrl: jdbc:mysql://localhost:3306/echo?serverTimezone=UTC
        user: echo_migrate

See Sample deployment topology for additional information

Configuration options

echo has several configuration options (can be specified in echo.yml), key ones are listed below:

  • scheduler.enabled (default: false)
    when set to true this instance will schedule and trigger CRON events
  • scheduler.pipelineConfigsPoller.enabled (default: false)
    when true, will synchronize pipeline triggers (set this to true if you enable scheduler unless running a missed scheduler configuration)
  • scheduler.compensationJob.enabled (default: false)
    when true this instance will poll for missed CRON triggers and attempt to re-trigger them (see Missed CRON scheduler)
  • orca.pipelineInitiatorRetryCount (default: 5)
    Number of retries on orca failures (leave at default)
  • orca.pipelineInitiatorRetryDelayMillis (default: 5000ms)
    Number of milliseconds between retries to orca (leave at default)

Trigger suppression

There are several ways to suppress triggers in echo (note, all of the below are backed by DynamicConfigService and therefore can be modified at runtime)

  • orca.enabled (default: true)
    top level knob that disables communication with orca and thus ALL triggers
  • scheduler.triggers.enabled (default: true)
    allows suppressing triggering of events from the CRON scheduler only
  • scheduler.compensationJob.triggers.enabled (default: true)
    allows suppressing triggering of events from the compensation job (aka missed CRON scheduler) only

There are two settings for each trigger, e.g. scheduler.enabled and scheduler.triggers.enabled. The reason for this complexity is to allow scenarios where there are two echo clusters that are running the scheduler for redundancy reasons (e.g. in two regions).
In order to correctly switch which cluster (region) is generating triggers they both need to be "up-to-speed" hence you'd run the scheduler in both clusters but only one would trigger. That way, when you switch which cluster does the triggering it will trigger the correct events without duplicates.

Missed CRON scheduler

The missed CRON scheduler is a feature in echo that ensures that CRON triggers are firing reliably. It is enabled by setting scheduler.compensationJob.enabled configuration option.
In an event that a CRON trigger fails to fire or it fires but, for whatever reason, the execution doesn't start the missed CRON scheduler will detect it and attempt to re-trigger the pipeline.
The main scenario when missed cron scheduler is useful is for main scheduler outages either planned (upgrade) or unplanned (hardware failure).
Missed scheduler should be run as a separate instance as that will provide the most benefit and the resilience needed. Most situation likely don't necessitate the need for a missed scheduler instance, especially if you elect to run in SQL mode. (With the SQL mode support and pending additional investigation this feature will likely be removed all-together)

Sample deployment topology

Here are two examples of what configurations you can deploy echo.

Using in-memory Using SQL
Server Group 1 3x echo 3x echo with echo-scheduler
Server Group 2 1x echo-scheduler 1x echo-missed-scheduler*
Server Group 3 1x echo-missed-scheduler* n/a

* optional echo-missed-scheduler see Missed CRON scheduler

If you opt for using an in-memory execution mode, take care when deploying upgrades to echo. Since only instance should be running at a time, a rolling-push strategy will need to be used. Furthermore, if using echo-missed-scheduler, make sure to upgrade echo-scheduler followed by echo-missed-scheduler to ensure pipelines (which had a trigger during the deploy period) are re-triggered correctly after deploy.

The following are configuration options for each server group (note that other configurations options will be required, which halyard will configure):
echo (this instance handles general events)

scheduler:
  enabled: false
  pipelineConfigsPoller:
    enabled: false
  compensationJob:
    enabled: false

echo-scheduler (this instance triggers pipelines on a CRON)

scheduler:
  enabled: true
  pipelineConfigsPoller:
    enabled: true
  compensationJob:
    enabled: false

echo-missed-scheduler (this instance triggers "missed" pipelines)

scheduler:
  enabled: true
  pipelineConfigsPoller:
    enabled: false
  compensationJob:
    enabled: true
    pipelineFetchSize: 50

    # run every 1 min to minimize the skew between expected and actual trigger times
    recurringPollIntervalMs: 60000

    # look for missed cron triggers in the last 5 mins (allows for a restart of the service)
    windowMs: 300000

Monitoring

echo emits numerous metrics that allow for monitoring its operation.
Some of the key metrics are listed below:

  • orca.trigger.success
    Number of successful triggers. That is when orca returns HTTP 200 on a given trigger

  • orca.trigger.errors
    Number of failed triggers. When orca fails to execute a pipeline (returns non-successful HTTP status code).
    This is a good metric to monitor as it indicates either invalid pipelines or some system failure in triggering pipelines

  • orca.trigger.retries
    Number of retries to orca. Failed calls to orca will be retried (assuming they are network type errors).
    Consistent non-zero numbers here means there is likely a networking issue communicating with orca and should be investigated.

  • echo.triggers.sync.error,
    echo.triggers.sync.failedUpdateCount, and
    echo.triggers.sync.removeFailCount
    Indicates a failure during trigger synchronization. This likely means there are pipeline with invalid CRON expressions which will not trigger.
    echo logs should provide additional information as to the cause of the issue