Cloud-Native, Open Source, Event-Driven Integration Platform

As cloud services grow, integration complexity grows exponentially, stressing legacy iPaaS tools. TriggerMesh is the leading Kubernetes-based integration platform to connect all your systems and data using industry-standard, open source technology.

Integrate, Automate, and Accelerate

Modern Integration

Proprietary integration is slow and expensive. The TriggerMesh open source API and integration as code automate the combination of on-premises systems and cloud services so you can manage integrations declaratively.

Enable Cloud Native Developers

As the leading Kubernetes-based integration platform, TriggerMesh accelerates the move to an event-driven architecture. Our Knative-powered platform provides an easy, standard way to create cloud native applications.

Real-time Data Flows

For enterprises seeking to modernize applications and take action in real time, adding TriggerMesh to Apache Kafka simplifies the creation and maintenance of data integrations. The TriggerMesh API is much simpler than Kafka Connect.

How it works

Create integration as code using our declarative API. Combine with your existing CI/CD pipeline for a fully-automated GitOps approach to cloud native integration

Kubernetes native
1
Kubernetes native API

Our API is exposed as Kubernetes objects. Incorporate existing Kubernetes objects like Secrets and ConfigMaps when defining your integrations

Integrate components as code
2
Integrate components as code

Declarative and API-driven integration sources and targets. Manage integrations declaratively from the command line, CI/CD pipeline or integrated in code

Declaratively Event driven
3
Declaratively event driven

As a full Event-driven platform, TriggerMesh integrations inherit a strong sense of loose coupling, allowing for unlimited extensibility

more about Integration as code

For less complex use cases, and less technical users, our low-code UI lets you quickly create new application flows (called Bridges)

1
Choose a Source

Events are changes that happen within a system. These changes are captured via a message and forward as event sources

2
Choose a Target

Targets are the serverless infrastructures that consume events and trigger the functions

3
Configure the Bridge

Use the TriggerMesh Controller to configure the Bridge

CHECK OUT OUR BRIDGE CATALOG

Cloud Native EDAs and Data Syncs

Automate integrations using our Kubernetes-based platform

Build Event-Driven Systems

Sync Data and Events Across Any Platform

Sync data and events between any systems running on any platform. Event transformation and filtering separate signal from noise.

Applications You Can Integrate with TriggerMesh

UiPath
Google PubSub
AWS SQS
Twilio
OCIMetrics
OpenShift Serverless
InfraJS
Azure Blob Storage
Azure
Google Cloud IoT
Bitbucket
Kubernetes
AWS CloudWatch Logs
JIra
AWS Comprehend
Azure Queue Storage
Hasura
AWS EventBridge
Apache Kafka
Zendesk
Google Cloud Firestore
Amazon SNS
VMware Vsphere
Tekton
Google Cloud Billing
Knative
Logz Metrics
Target
IBM MQ
Amazon Kinesis
Confluent
AWS Cognito Identity
Azure IoT Hub
Google Cloud Workflows
Azure EventGrid
Webhooks
Google Sheets
AWS Code Commint
AWS lambda
Alibaba OSS
AWS Dynamo DB
AWS Kinesis
Google Cloud Source Repositories
AWS S3
AWS Cognito User Pool
Amazon SQS
Slack
Azure Service Bus Topic
AWS SNS
SendGrid
Microsoft Active Directory
AWS CloudWatch
Azure Activity Logs
Zendesk
Splunk
OracleDB
AWS Performance Insights
Azure Service Bus Queue
Azure Event Hubs
Google Cloud Audit Logs
GCP
Schedule Functions
AWS EventBridge
Amazon Lambda
GitHub
Google Storage
Elasticsearch
GitLab
Confluence
Salesforce
Datadog
Logz.io

Popular Use Cases

Cloud Providers

Trigger Serverless Functions

Publish and trigger functions and/or Kubernetes workloads from other clouds or your data center apps

Cloud Services

Salesforce To Kafka

Read Salesforce Events, transform them into Kafka Events, and publish them using the generic Kafka proxy

Kubernetes Services

Flood a Data Lake

Send Azure Activity Logs as CloudEvents to Splunk, where they can be further analyzed and visualized

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