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Description
Edka streamlines the establishment of a production-ready Platform as a Service (PaaS) using standard cloud virtual machines and Kubernetes, significantly minimizing the manual labor needed to manage applications on Kubernetes by offering preconfigured open-source add-ons that effectively transform a Kubernetes cluster into a comprehensive PaaS solution.
To enhance Kubernetes operations, Edka organizes them into distinct layers:
Layer 1: Cluster provisioning – A user-friendly interface that allows for the effortless creation of a k3s-based cluster with just one click and default settings.
Layer 2: Add-ons – A convenient one-click deployment option for essential components like metrics-server, cert-manager, and various operators, all preconfigured for use with Hetzner, requiring no additional setup.
Layer 3: Applications – User interfaces with minimal configurations tailored for applications that utilize the aforementioned add-ons.
Layer 4: Deployments – Edka ensures automatic updates to deployments in accordance with semantic versioning rules, offering features such as instant rollbacks, autoscaling capabilities, persistent volume management, secret/environment imports, and quick public accessibility for applications. Furthermore, this structure allows developers to focus on building their applications rather than managing the underlying infrastructure.
Description
dstack simplifies GPU infrastructure management for machine learning teams by offering a single orchestration layer across multiple environments. Its declarative, container-native interface allows teams to manage clusters, development environments, and distributed tasks without deep DevOps expertise. The platform integrates natively with leading GPU cloud providers to provision and manage VM clusters while also supporting on-prem clusters through Kubernetes or SSH fleets. Developers can connect their desktop IDEs to powerful GPUs, enabling faster experimentation, debugging, and iteration. dstack ensures that scaling from single-instance workloads to multi-node distributed training is seamless, with efficient scheduling to maximize GPU utilization. For deployment, it supports secure, auto-scaling endpoints using custom code and Docker images, making model serving simple and flexible. Customers like Electronic Arts, Mobius Labs, and Argilla praise dstack for accelerating research while lowering costs and reducing infrastructure overhead. Whether for rapid prototyping or production workloads, dstack provides a unified, cost-efficient solution for AI development and deployment.
API Access
Has API
API Access
Has API
Integrations
Amazon Elastic Container Registry (ECR)
Amazon Web Services (AWS)
Docker
GitHub
Google Cloud Artifact Registry
Google Cloud Platform
Hetzner
Microsoft Azure
Python
Integrations
Amazon Elastic Container Registry (ECR)
Amazon Web Services (AWS)
Docker
GitHub
Google Cloud Artifact Registry
Google Cloud Platform
Hetzner
Microsoft Azure
Python
Pricing Details
€0
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Edka
Founded
2013
Country
Spain
Website
edka.io
Vendor Details
Company Name
dstack
Founded
2022
Country
Germany
Website
dstack.ai/
Product Features
DevOps
Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports