Scott O.

SnapLogic MCP Support (published September 16, 2025 by Tim Fan) explains how SnapLogic is integrating the Model Context Protocol (MCP) into its platform and outlines what that support looks like, how it works, and why it matters for customers building AI-driven workflows.

Automated Deployment (CICD) of SnapLogic assets with GitHub This guide is a reference document for the deployment of SnapLogic assets to a GitHub repository. It also includes sample YAML code for a GitHub Actions workflow which can be used to automate the deployment of assets across orgs (Dev -> Stg / Stg -> Prod, etc.) This guide is targeted towards SnapLogic Environment Administrators (Org Administrators) and users who are responsible for the deployment of SnapLogic assets / Release management operations. Section B covers automated deployment with GitHub Actions, and Section A illustrates a manual deployment flow using the Manager interface. Author: Ram Bysani SnapLogic Enterprise Architecture team

AWS SageMaker Model Integration I am using Snaplogic to create a data set that I then write as a CSV to S3. My next step is to make a call to the SageMaker model that reads the data and writes an output file to S3. I am currently not able to execute the SageMaker model. I am attempting to use

Is there anything special that you did to the user account or SageMaker?

SnapLogic Test Automation with Robot Framework: A Complete Testing Solution By Sriswapna Pothana In today’s fast-paced integration landscape, ensuring the reliability and performance of your SnapLogic pipelines is crucial. We’re excited to introduce a comprehensive test automation framework that combines the power of Robot Framework with SnapLogic’s APIs to deliver a robust, scalable, and easy-to-use testing solution. This approach leverages the snaplogic-common-robot [PyPI-published library] to provide prebuilt Robot Framework keywords for interacting with SnapLogic Public APIs, integrated within a Docker-based environment.. This lets teams spin up full SnapLogic environments on demand—including Groundplex, databases, and messaging services—so tests run the same way everywhere This blog post explores two key components of our testing ecosystem:

Read more details in this SnapLogic Technical Blog >>

We’re excited to share that Integration Nation is moving to a new home — a Slack-based community designed to make it easier, faster, and more natural for you to connect with peers and the SnapLogic team. This transition will give you:

What’s changing

Why we’re making this move Members have told us they want a faster, more conversational way to engage, and Slack is already where many of you collaborate day to day. Moving to Slack allows Integration Nation to become a truly real-time, high-value community—where insights spread faster, questions get answered quicker, and connections happen more naturally. What you need to do Just click the link to join the new Integration Nation Slack community. Once inside, you’ll be able to explore channels, meet other members, and jump into discussions immediately. We can’t wait for you to experience this new chapter of Integration Nation. If you have any questions, feel free to reach out - we’re here to help.

API Key Authenticator token validation By: Kishore Surendra Hello everyone, I have a query with respect to the API key authenticator configured for an API created by me. After setting the API key to '1234', I expect to receive the API response upon auth_token=1234 in the request parameter. However, I notice that I receive a valid API response for any token value except 1234. The expected functionality is opposite to what is being observed. My expectation is to receive a response only when auth_token is present AND equals the value set in the API key of the policy (Eg:1234). How do I achieve this in Snaplogic? The corresponding screenshots have been attached. Thanks.