Setup guide

Please follow these steps to setup the Snowplow Indicative Relay on AWS Lambda:

1. Create your Indicative account

If you do not have an Indicative account, go to Indicative to create an account.

2. Obtain an API key from Indicative

• If you are a new Indicative user, go to https://app.indicative.com/#/onboarding/snowplow. Then select Snowplow and copy the API Key. Save it, you will need it later

• If you want to send data to an existing project, go to https://app.indicative.com/#/account/projects

3. Create an IAM Role for the Lambda

Your AWS Lambda needs to have an Execution Role that allows it to use the Kinesis Stream and CloudWatch. Open the AWS Management Console and follow these steps:

1. Go to IAM Management in the Console, choose Roles from the sidebar, then click Create role.
2. As shown in the screenshot below, for the type of trusted entity select AWS Service and for the service that will use this role choose Lambda.

3. Now you need to choose a permission policy for the role. The Lambda needs to have read access to Kinesis and write access to CloudWatch logs – for that we will choose AWSLambdaKinesisExecutionRole.
4. On the next screen provide a name for the newly created role, then click Create role to finish the process.

4. Create the Lambda function

As with the IAM Role, we will be using the AWS Console to get our Lambda function up and running.

1. On the Console navigate to Lambda section and click Create a function. Runtime should be Java 8. In the Role dropdown pick Choose an existing role, then in the dropdown below choose the name of the role you have created in the previous part of the guide. Click Create function.

2. The Lambda has been created, although it does not do anything yet. We need to provide the code and configure the function. Take a look at the Function code box. In the Handler textbox paste: com.snowplowanalytics.indicative.LambdaHandler::recordHandler
   From the Code entry type dropdown pick Upload a file from Amazon S3. A textbox labeled S3 Link URL will appear. We are hosting the code through our hosted assets. You will need to choose the S3 bucket in the same region as your AWS Lambda function, for example if your Lambda is us-east-1 region, paste the following URL: s3://snowplow-hosted-assets-us-east-1/relays/indicative/indicative-relay-0.4.0.jar in the textbox. Take a look at this table to pick the right bucket name for your region.

3. Below Function code settings you will find a section called Environment variables. You need to use these environment variables to configure some additional settings for the relay, such as the the API key and filters.
   • 3.1 Setting up the API key: In the first row, first column (the key) type INDICATIVE_API_KEY. In the second column (the value) paste your API Key obtained in the beginning of this guide.
   • 3.2 Setting up filters: The relay lets you configure the following filters:
     • UNUSED_EVENTS: events that will not be relayed to Indicative;
     • UNUSED_ATOMIC_FIELDS: fields of the canonical Snowplow event that will not be relayed to Indicative;
     • UNUSED_CONTEXTS: contexts whose fields will not be relayed to Indicative.

Out of the box, the relay is configured to use the following defaults:

Unused events	Unused atomic fields	Unused contexts
app_heartbeat	etl_tstamp	application_context
app_initialized	collector_tstamp	application_error
app_shutdown	dvce_created_tstamp	duplicate
app_warning	event	geolocation_context
create_event	txn_id	instance_identity_document
emr_job_failed	name_tracker	java_context
emr_job_started	v_tracker	jobflow_step_status
emr_job_status	v_collector	parent_event
emr_job_succeeded	v_etl	performance_timing
incident	user_fingerprint	timing
incident_assign	geo_latitude
incident_notify_of_close	geo_longitude
incident_notify_user	ip_isp
job_update	ip_organization
load_failed	ip_domain
load_succeeded	ip_netspeed
page_ping	page_urlscheme
s3_notification_event	page_urlport
send_email	page_urlquery
send_message	page_urlfragment
storage_write_failed	refr_urlscheme
stream_write_failed	refr_urlport
task_update	refr_urlquery
wd_access_log	refr_urlfragment
	pp_xoffset_min
	pp_xoffset_max
	pp_yoffset_min
	pp_yoffset_max
	br_features_pdf
	br_features_flash
	br_features_java
	br_features_director
	br_features_quicktime
	br_features_realplayer
	br_features_windowsmedia
	br_features_gears
	br_features_silverlight
	br_cookies
	br_colordepth
	br_viewwidth
	br_viewheight
	dvce_ismobile
	dvce_screenwidth
	dvce_screenheight
	doc_charset
	doc_width
	doc_height
	tr_currency
	mkt_clickid
	etl_tags
	dvce_sent_tstamp
	refr_domain_userid
	refr_device_tstamp
	derived_tstamp
	event_vendor
	event_name
	event_format
	event_version
	event_fingerprint
	true_tstamp

To change the defaults, you can pass in your own lists of events, atomic fields or contexts to be filtered out. For example:

Environment variable key	Environment variable value
UNUSED_EVENTS	page_ping,file_download
UNUSED_ATOMIC_FIELDS	name_tracker,event_vendor
UNUSED_CONTEXTS	performance_timing,client_context

Similarly to setting up the API key, the first column (key) needs to be set to the specified environment variable name in ALLCAPS. The second column (value) is your own list as a comma-separated string with no spaces.

If you only specify the environment variable name but do not provide a list of values, then nothing will be filtered out.

If you do not set any of the environment variables, the defaults will be used.

• 3.3. Setting up the Indicative API URI: By default, the relay uses the standard URI. To change that, you can set the INDICATIVE_URI environment variable.
• 3.4. Setting up the field whose value should be used as the event name for struct events: In Snowplow’s canonical event model, there’s a legacy type of custom structured event, which is known as a struct or ‘structured event’. These are still fairly popular with users, however the value of the event_name field for those events (which is simply event) can be confusing. To help group similar events, Snowplow users often designate one of their special fields (most commonly se_action) to be the ‘event name field’. Since version 0.5.0 by default se_action is used as the event name field for structured events. But you can override that by setting the Lambda environment variable STRUCTURED_EVENT_NAME_FIELD to the field whose value you’d rather use, eg se_category.

4. Scroll down a bit and take a look at the Basic settings box. There you can set memory and timeout limits for the Lambda. We recommend setting 256 MB of memory or higher (on AWS Lambda the CPU performance scales linearly with the amount of memory). The timeout should be set quite high – we recommend one and half minute – because of so-called JVM cold starts. The cold starts happen when the Lambda function is invoked for the first time on a new instance and it can take a significant amount of time.

5. Now let’s add our enriched Kinesis stream as an event source for the function. From the list of triggers in the Designer configuration up top, choose Kinesis.

Take a look at the Configure triggers section which just appeared below. Choose your Kinesis stream that contains Snowplow enriched events. Set the batch size to your liking – 100 is a reasonable setting. Note that this a maximum batch size, the function can be triggered with less records. For the starting position we recommend Trim horizon, which starts processing the stream from an observable start. Click Add button to finish the trigger configuration. Make sure Enable trigger is selected.

6. Save the changes by clicking the Save button in the top-right part of the page.

5. Observe the events in Indicative

After a while the events should start flowing into Indicative. You can go Settings -> Events and Properties to see incoming event types, change their labels, descriptions and categories.