Originally reported by devops.com. Published August 2018.

Overview

SnapLogic announced a set of updates to its Enterprise Integration Cloud platform aimed at bringing enterprise data integration workflows directly into DevOps pipelines. The headline change is native GitHub support, allowing teams to store, share, and version-control Snap connector integrations alongside application code. Additional announcements included Mesosphere DC/OS platform integration, a new service catalog, enhancements to the Iris AI recommendation engine, and improved API monitoring and pipeline search tooling.

GitHub Support: Integrations as Code

The most significant DevOps-facing addition is the ability to store preconfigured integrations—built with SnapLogic’s Snap connectors—directly in GitHub repositories. According to Craig Stewart, Vice President of Product Management at SnapLogic, this change has two main benefits:

• Collaboration across skill levels: Developers at any experience level can share preconfigured integrations via the same GitHub repositories they already use for application code, lowering the barrier to reuse.
• CI/CD pipeline inclusion: DevOps teams can incorporate Snap connectors into continuous integration and continuous delivery (CI/CD) workflows, treating integration configurations as versioned artifacts rather than one-off configurations.

SnapLogic also introduced a Patterns Catalog to make it easier for developers to discover and reuse existing integration patterns. The catalog acts as a searchable library, reducing duplicated effort and encouraging standardization across teams.

Mesosphere DC/OS Integration and the Road to Kubernetes

SnapLogic added support for the Mesosphere DC/OS container orchestration platform, a feature driven by direct customer demand. Stewart noted that this is the first step in a broader container orchestration strategy, with planned support for Kubernetes to follow. At the time of the announcement, SnapLogic characterized Kubernetes as the emerging de facto standard for container orchestration—a prediction that has since proven accurate.

Iris AI Engine Updates: Bidirectional Pipeline Construction

SnapLogic’s Iris AI recommendation engine, which suggests Snap connectors as developers build integration pipelines, received a meaningful update to how it can be invoked:

• Previously: Iris started recommendations from the first Snap connector in the pipeline, working forward.
• New: Start from the last Snap. When a developer places the final Snap on the canvas first, the Integration Assistant now works backward, suggesting preceding Snaps until the pipeline is complete.
• New: Outside-in construction. Developers can place both the first and last Snaps on the canvas, and the Integration Assistant fills in the middle, working from both ends toward the center.

These options give teams more flexibility in how they design pipelines, particularly when the destination system or the source system is well-defined before the intermediate steps are determined.

API Monitoring and Pipeline Search Improvements

Alongside the major feature announcements, SnapLogic enhanced its tooling for operational visibility:

• API monitoring: Updated tools for tracking the health and performance of APIs managed through the platform.
• Pipeline search: Improved search capabilities to help teams locate broken or misconfigured integration pipelines more quickly, reducing mean time to resolution for integration failures.

The Citizen Integrator Model and Enterprise Data Utilization

Stewart framed these updates within a broader SnapLogic strategy around self-service integration. The goal is to enable so-called citizen integrators—non-developer business users within lines of business—to leverage prebuilt integration patterns created by central IT teams, without requiring deep technical expertise.

SnapLogic cited a survey of 500 IT decision-makers conducted by Vanson Bourne on its behalf, which found that organizations were, on average, using only about half the data they collect, and that data influenced fewer than half of business decisions. The survey projected significant spending increases to operationalize data over the following five years.

The practical implication for DevOps teams is that integration is no longer solely an IT concern. As citizen integrators take on more responsibility, the need for reusable, version-controlled, and pipeline-compatible integration patterns becomes a genuine DevOps challenge—one that the GitHub support and Patterns Catalog are directly designed to address.

Key Takeaways

• Snap connector integrations can now be stored and versioned in GitHub, enabling them to participate in standard CI/CD workflows.
• A new Patterns Catalog supports discovery and reuse of preconfigured integration patterns.
• DC/OS support has been added, with Kubernetes support planned as a follow-on.
• The Iris AI engine now supports backward and outside-in pipeline construction, in addition to the original forward-only approach.
• Enhanced API monitoring and pipeline search tools improve operational observability.

SnapLogic Brings Enterprise Integration into the DevOps Toolchain

SnapLogic announced several updates to its Enterprise Integration Cloud platform that move the product closer to standard DevOps practices. The headline addition is GitHub support, which allows integrations built with Snap connectors to be stored, versioned, and shared through GitHub repositories alongside existing application code.

The release also included integration with the Mesosphere DC/OS container platform, a new service catalog, enhancements to the Iris AI recommendation engine, and improvements to API monitoring and broken-pipeline search tooling.

GitHub Support: Sharing and Reusing Snap Connectors in CI/CD Pipelines

Craig Stewart, Vice President of Product Management at SnapLogic, explained that GitHub support lowers the barrier for developers of all skill levels to share preconfigured integrations. Because the integrations live in the same GitHub repositories developers already use for application code, they become first-class citizens in CI/CD workflows.

Practical benefits of the GitHub integration include:

• Version control for integration pipelines: Teams can track changes to Snap connector configurations just as they track source code changes.
• Discoverability through a Patterns Catalog: Preconfigured connectors are surfaced in a central catalog, making it easier for developers to find and reuse existing integration patterns rather than rebuilding them from scratch.
• CI/CD inclusion: Integration pipelines can be embedded directly into automated build and deployment workflows.

This is particularly relevant for organizations pursuing a self-service integration model, where developers across teams need to consume pre-approved integration patterns without requiring deep platform expertise.

Mesosphere DC/OS and Kubernetes Support

SnapLogic added support for the Mesosphere DC/OS platform in direct response to customer demand. At the time of the announcement, the company stated that Kubernetes support was also planned, with the expectation that Kubernetes would become the dominant container orchestration standard.

Container orchestration support signals SnapLogic’s intention to run integration workloads alongside containerized microservices, which is a natural fit as enterprise architectures increasingly rely on distributed, container-based deployments.

Iris AI Enhancements: Building Pipelines from Both Ends

SnapLogic updated its Iris AI-powered Integration Assistant with new ways to construct pipelines. Previously, Iris only offered recommendations starting from the first Snap connector in a pipeline. The update introduced two new construction modes:

• Last-Snap-first mode: A user places the final Snap connector on the canvas, and the Integration Assistant recommends preceding Snaps in reverse order until the full pipeline is complete.
• Outside-in mode: A user defines both the first and last Snaps, and the Integration Assistant fills in the intermediate steps, working inward from both ends simultaneously.

These modes are designed to accommodate different developer mental models — some teams design integrations by starting with the desired output, making the reverse-construction approach more intuitive.

The Business Context: Citizen Integrators and Data Utilization

SnapLogic cited survey results from a Vanson Bourne study of 500 IT decision-makers, conducted on behalf of SnapLogic, to frame the business urgency behind these updates. According to that survey:

• Organizations expected an average 547% return on data investments.
• Revenue increases of an average $5.2 million were anticipated from more effective data use.
• Despite this, organizations were using only about 51% of the data they collected or generated.
• Data influenced fewer than 48% of business decisions.
• Organizations planned to spend an average of $1.7 million over five years to operationalize data — more than double current spending.

SnapLogic’s response to this gap is to enable what it calls citizen integrators — non-IT staff within lines of business who can work with prebuilt integration patterns created by central IT teams. The GitHub-based Patterns Catalog is a direct enabler of this model: IT developers publish vetted integration patterns once, and business-side users discover and deploy them independently.

Why This Matters for DevOps Teams

The core theme across these updates is the convergence of enterprise integration with DevOps discipline. By storing integration pipelines in GitHub, applying AI-assisted construction, and supporting container orchestration platforms, SnapLogic is positioning its platform as a component in modern DevOps pipelines rather than a standalone IT tool.

For DevOps engineers, the practical takeaway is that integration artifacts can now participate in the same version control, code review, and CI/CD workflows as application code — reducing the gap between application development velocity and integration delivery.

As organizations scale DevOps practices beyond software engineering teams into broader enterprise functions, tools that bridge the integration and automation gap without requiring specialist knowledge become increasingly valuable.