Echo serves as two purposes within Spinnaker:
The following high level diagram shows how events flow through
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
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 (
swabbie sent a notification request to
e.g. A resource is about to be deleted and swabbie would like an email notification to be sent out to the owner
echo submits the pipeline/orchestration to
orca for execution
orca sends events to
echocan send notifications if any are defined on the stage
echocan send notification as above
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)
echo can also send events to any URL (à la webhook style)
Echo provides integrations for outgoing notifications in the
echo-notifications package via:
Echo is also able to send events within Spinnaker to a predefined url, which is configurable under the
You can extend the way in which
echo events are sent by implementing the
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
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.
To start the JVM in debug mode, set the Java system property
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
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).
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
echo has several configuration options (can be specified in
echo.yml), key ones are listed below:
truethis instance will schedule and trigger CRON events
true, will synchronize pipeline triggers (set this to
trueif you enable
schedulerunless running a missed scheduler configuration)
truethis instance will poll for missed CRON triggers and attempt to re-trigger them (see Missed CRON scheduler)
orcafailures (leave at default)
orca(leave at default)
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)
orcaand thus ALL triggers
There are two settings for each trigger, e.g.
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.
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)
Here are two examples of what configurations you can deploy
|Using in-memory||Using SQL|
|Server Group 1||3x
|Server Group 2||1x
|Server Group 3||1x
echo-missed-scheduler see Missed CRON scheduler
If you opt for using an in-memory execution mode, take care when deploying upgrades to
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
echo emits numerous metrics that allow for monitoring its operation.
Some of the key metrics are listed below:
Number of successful triggers. That is when
HTTP 200 on a given trigger
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
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.
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