Page Comparison

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Every Snaplex has a name, for example ground-dev or ground-prod. In the SnapLogic Designer,you can choose which Snaplex pipelines are executed on. The Snaplex configuration has an environment associated with it, for example dev or prod. When the nodes are configured for the Snaplex, the jcc.environment has to be set to the environment value as configured for the Snaplex.

After the Snaplex service is started on a node, the service connects to the SnapLogic cloud service. Runtime logs from the Snaplex are written to the /opt/snaplogic/run/log (or c:\opt\snaplogic\run\log) directory. The Dashboard shows the nodes that are currently connected for each Snaplex.

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• Anaplan: Upload, Write

• Binary: Sort, Join

• Box: Read, Write

• Confluent Kafka: All Snaps that use either Kerberos and SSL accounts

• Database: When using local disk staging for read-type Snaps

• Email: Sender

• Hadoop: Read, Write (Parquet and ORC formats)

• JMS: When the user provides a JAR file

• Salesforce: Bulk Query, Snaps that process CSV data

• Script: PySpark

• Snowflake: When using internal staging

• Teradata: TPT FastExport

• Transform: Aggregate, Avro Parser, Excel Parser, Join, Unique, Sort

• Vertica: Bulk Load

• Workday Prism Analytics: Bulk Load

• Data Science (Machine Learning) Snaps: Profile, AutoML, Sample, Shuffle, Deduplicate, Match

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• Snaplex-triggered Pipeline executions—Since the Control Plane triggering mechanism imposes additional Org level API limits, we recommend using the Snaplex triggering mechanism for high-volume API usage. 

• REST requests to Ultra Task Pipelines—For direct API calls to the Snaplex, the requests must pass through a load balancer. Without a load balancer, request failures occur, and the Snaplex eventually goes offline during Snaplex maintenance or upgrades.

• API Policies—To apply API policies to APIs or Triggered and Ultra Tasks on a Cloudplex, you must have a load balancer, which SnapLogic provisions. 

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