Pipekit
A scalable control plane for managing and optimizing Argo Workflows on Kubernetes, enabling efficient data and CI pipeline operations.
Community:
Product Overview
What is Pipekit?
Pipekit is a self-serve platform designed to simplify the deployment, scaling, and management of data and continuous integration pipelines using Argo Workflows on Kubernetes infrastructure. It provides enterprise-grade features such as multi-cluster management, unified logging, and role-based access control (RBAC), allowing platform teams to reduce maintenance overhead while improving developer experience. Pipekit integrates seamlessly with existing cloud providers and supports flexible deployment models, giving teams control over compute resources and data privacy. The platform also offers professional support from Argo contributors to optimize pipeline performance and accelerate technical decisions.
Key Features
Managed Argo Workflows
Provides a control plane that configures and manages Argo Workflows, enabling rapid setup and scaling of complex data and CI pipelines.
Multi-Cluster Workflow Management
Allows running and monitoring workflows across multiple Kubernetes clusters from a single unified interface.
Enterprise-Grade Security
Includes robust role-based access control (RBAC) and customizable namespace management to secure pipeline operations.
Unified Logging and Monitoring
Offers integrated logging views and optional self-hosted log storage to enhance observability and troubleshooting.
Cloud Provider Agnostic
Supports major cloud platforms such as AWS, Google Cloud, and Microsoft Azure, enabling flexible infrastructure choices.
Expert Support and Collaboration
Access to Argo Workflow maintainers and Kubernetes experts through dedicated support channels and regular consultation.
Use Cases
- Data Pipeline Scalability : Scale complex data processing workflows efficiently, reducing cloud costs and operational overhead.
- Continuous Integration/Continuous Deployment (CI/CD) : Manage and automate CI/CD pipelines across multiple clusters with enhanced reliability and speed.
- Infrastructure Automation : Automate infrastructure tasks and workflows to improve operational efficiency and consistency.
- Developer Self-Service : Empower development teams with self-serve access to workflow management, improving agility and reducing platform team load.
- Enterprise Data Governance : Enforce security policies and access controls across pipelines to meet enterprise compliance requirements.
FAQs
Pipekit Alternatives
Release
Platform for creating and managing on-demand, ephemeral environments that accelerate development workflows and optimize DevOps costs.
Brainboard
A collaborative platform for visually designing, generating, and managing cloud infrastructure with automated Terraform code generation.
UbiOps
A flexible platform for deploying, managing, and orchestrating AI and ML models across cloud, on-premise, and hybrid environments.
Modelbit
Infrastructure-as-code platform for seamless deployment, scaling, and management of machine learning models in production.
Tensorfuse
Serverless GPU runtime enabling seamless deployment, fine-tuning, and autoscaling of AI models on private cloud infrastructure.
Union AI
Unified AI orchestration platform that streamlines AI/ML workflow development, execution, and scaling across multi-cloud and multi-cluster environments.
dstack
Open-source container orchestration platform tailored for AI workloads, enabling seamless GPU resource management across cloud and on-premises environments.
Defang
A streamlined platform that transforms Docker Compose projects into secure, scalable cloud deployments with minimal effort.
Analytics of Pipekit Website
🇺🇸 US: 44.9%
🇮🇳 IN: 24.79%
🇨🇦 CA: 11.5%
🇹🇼 TW: 5.72%
🇩🇪 DE: 4.8%
Others: 8.29%