- What is CREODIAS?
- Computing & Cloud
- Data & Processing
- Pricing Plans
- Fight with COVID-19
- Examples of usage
- Enabling AI / ML workflows with CREODIAS vGPUs
- Satellite remote sensing analyses of the forest
- Satellite-based Urban Heat Island Mapping on CREODIAS
- Old but gold - historical EO data immediately available and widely used on CREODIAS
- CREODIAS for emergency fire management
- AgroTech project as an example of how CREODIAS can be used for food and environmental research
- Monitoring Air Quality of Germany in Pre vs During COVID Lockdown Period
- EO4UA
- Common Agricultural Policy monitoring with Earth Observation
- Applications of CREODIAS data
- Meteorological data usage on the CREODIAS platform
- Building added value under Horizon Europe with CREODIAS
- CREODIAS: Introduction to SAR Sentinel-1 data
- Land subsidence and landslides monitoring based on satellite data
- Satellite imagery in support of the Common Agriculture Policy (CAP) and crop statistics
- Useful tools for data processing, available on CREODIAS platform
- CREODIAS for hydrological drought modelling
- CREODIAS for managing Urban Heat Islands
- CREODIAS for Digitising Green Spaces
- CREODIAS for Air Quality
- Advanced data processors on CREODIAS
- CREODIAS for your application
- Solutions for agriculture with CREODIAS
- Earth Observation data for Emergency response
- Security Applications with Satellite Data
- Climate Monitoring with Satellite Data
- Water Analysis on CREODIAS
- CREODIAS for land and agriculture monitoring
- Solutions for atmospheric analysis
- Example of tool usage
- Processing EO Data and Serving www services
- Processing and Storing EO
- Embedding OGC WMS Services into Your website
- GPU Use Case
- Using the EO Browser
- EO Data Finder API Manual
- Use of SNAP and QGIS on a CREODIAS Virtual Machine
- Use of WMS Configurator
- DNS as a Service - user documentation
- Use of Sinergise Sentinel Hub on the CREODIAS EO Data Hub
- Load Balancer as a Service
- Jupyter Hub
- Use of CREODIAS Finder for ordering data
- ESRI ArcGIS on CREODIAS
- Use of CEMS data through CREODIAS
- Searching, processing and analysis of Sentinel-5P data on CREODIAS
- ASAR data available on CREODIAS
- Satellite remote sensing analyses of the forest
- Public Reporting Dashboards
- Sentinel Hub Documentation
- Legal Matters
- FAQ
- News
- Partner Services
- About Us
- Forum
- Knowledgebase
Computing & Cloud
Powerful and secure Dedicated Server Virtual Machines
Dedicated Server Virtual Machines (VM.DS) are a special kind of Virtual Machines that use an entire physical server in order to create a Virtual Server intended for one Client. Thanks to this, the VM.DS guarantees to the owner the power of the whole processor, RAM and a network bandwidth. Additionally, the solution is equipped with very efficient NVMe/SSD disks installed in a pass-through mode.
VM.DS offers the lowest cost of computing power in the cloud of all available solutions. Allowing long-term savings up to 78% compared to other configurations, it ensures a greater physical security, dedicated resources and very fast local NVMe disks.
This option combines the advantages of Virtual Machines cloud environment access with the advantages of physical servers – the separation of resources, a direct access to graphics cards, very fast local disks, an increased security and an easy licensing. VM.DS are therefore an ideal solution for clients expecting efficiency as well as the independence of bare metal solutions and a wide functionality of OpenStack.
Advantages:
- One physical server dedicated to one client
- No sharing of resources
- Configuration optimized for various applications
- Possibility to start at any given moment
- A unique solution combining the advantages of physical servers and a cloud
- Possibility to purchase a unique configuration adapted to the Client’s needs
- Optimized for long runs
Dedicated Server Virtual Machine is the best solution that guarantees a long-term processing power combining the advantages of a cloud solution and a physical server.
| Dedicated Servers* | Pay per use | Monthly | Half yearly | Yearly | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Available DSs | #vCores | RAM (GB) | SSD NVMe Local Storage (GB) | per hour | per month | per month | per month | ||||
| ds | |||||||||||
| ds.medium | 40 (20 cores) | 48 | 2 x 500 | 1,618 | 689,99 | 429,79 | 244,86 | ||||
| ds.large | 40 (20 cores) | 112 | 2x 1000 | 1,965 | 837,45 | 519,53 | 294,21 | ||||
| ds.2xlarge | 40 (20 cores) | 368 | 2x 1920 | 2,968 | 1 266,00 | 787,50 | 450,00 | ||||
| ds.3xlarge | 48 (24 cores) | 496 | 2x 1920 | 3,641 | 1 552,96 | 966,00 | 552,00 | ||||
| ds.large.gpu** | 40 (20 cores) | 112 | 2x 1000 | 3,287 | 1 400,75 | 860,92 | 481,98 | ||||
| ds.large.gpu(old)*** | 40 (20 cores) | 118 | 2x 1000 | 3,242 | 2 101,12 | 860,92 | 481,98 | ||||
| ds.3xlarge.4gpu**** | 48 (24 cores) | 496 | 2x 1920 | 10,974 | 6 321,00 | 3 870,00 | 2 580,00 | ||||
* If the above configurations do not fit your project, please contact our sales team (sales@creodias.eu) to design a custom solution.
** ds.large.gpu is equipped with GeForce RTX 2080Ti (4352 CUDA Cores, 11GB GDDR6).
*** ds.large.gpu(old) previous ds.gpu configuration with GeForce GTX 1080 Ti and is still supported.
**** ds.3xlarge.4gpu is equipped with 4x GeForce RTX 2080Ti (4352 CUDA Cores, 11GB GDDR6).