Activepieces 0.79.2: Google Vertex AI Integration Now Available

Here at industry sources, we tracked the latest Activepieces release and found a targeted addition: the new Google Vertex AI piece enables builders to integrate Google's LLM capabilities directly into automation workflows. This is a straightforward integration that adds Vertex AI as a connectable service alongside Activepieces' existing 800+ integrations.

The Google Vertex AI piece functions as a building block within Activepieces flows, allowing you to invoke Vertex AI models, process responses, and chain them with other automation steps. This matters specifically if you're already running infrastructure on Google Cloud or need to keep LLM calls within the Google ecosystem for compliance or performance reasons.

The update also signals ongoing work on the secret manager infrastructure. The team is refactoring this component, which handles credential storage and rotation. This is backend-focused work that doesn't directly impact workflows today, but it's important context for your upgrade planning.

• Google Vertex AI piece now available as native integration
• Enables LLM model invocation within Activepieces workflows
• Secret manager refactoring continues - not urgent but monitor for 0.80.0

If you're building on Activepieces and need LLM capabilities, Vertex AI integration removes a manual step. Previously, you'd need to call external APIs or use generic HTTP requests to reach Vertex AI. Now it's a native piece - meaning built-in authentication, parameter handling, and error management specific to Vertex AI's API shape.

The practical difference: less friction to prototype LLM-powered automation. You can now combine Vertex AI with Activepieces' trigger ecosystem - run Vertex AI inference when webhooks fire, when schedules trigger, or when other services post data. This is particularly useful if you're building document processing, content generation, or classification workflows that need to live in automation rather than custom code.

The secret manager refactoring is a separate concern but worth tracking. The recommendation to upgrade to 0.80.0 suggests credential handling may change. If your flows rely on stored secrets (API keys, database passwords), test 0.80.0 in a non-production environment first to catch any breaking changes in how secrets are retrieved or refreshed.

• Native Vertex AI reduces authentication and error-handling overhead
• Unlocks LLM inference within trigger-based workflows
• Secret manager changes coming in 0.80.0 - plan testing ahead

0.79.2 is a point release, not a major version bump, which signals a low-risk update. The Google Vertex AI piece is additive - it doesn't change existing pieces or core functionality. If you're running Activepieces in production, you can upgrade without expecting workflow disruption.

However, the refactoring work on secret management creates a fork in your upgrade decisions. The Activepieces team is explicitly recommending a jump to 0.80.0 rather than staying on 0.79.2 long-term. This suggests they're consolidating work on secrets in the next minor version. Staying on 0.79.2 isn't blocked, but you're choosing not to receive the finalized secret manager changes.

Your move: If you have active Vertex AI use cases or plan to add them, upgrade to 0.79.2 now and schedule 0.80.0 testing for the next sprint. If you don't use Vertex AI and your current secret handling is stable, wait for 0.80.0 release notes before upgrading. The momentum in this space continues to accelerate.

• 0.79.2 is low-risk, additive - safe for production upgrade
• 0.80.0 will contain finalized secret manager changes
• Plan testing of 0.80.0 before production rollout