Deployment models

Devo is a cloud-based application, but there are two other models available to suit your needs: 

  • Cloud model - Collection, analytics, and storage all in the cloud. It provides the best solutions in terms of price and scalability.
  • On-premises modelCollection, analytics, and storage all on-premises. Useful when dealing with extremely high volumes of data, in order to avoid a lower system performance due to potential network latency.
  • Hybrid modelCollection and storage on-premises, analytics processed in the cloud. Suitable when the data requires special protection (for example, security and governance rules).

                   


 All these models share the following attributes:

  • Rigorously real-time data collection, data mining, and correlation.
  • Web-based administration tool for accessing and working with data, from anywhere in the world.
  • No limit on the amount of data that can be integrated.

See below a description of the three current models to use our services.

Cloud model

Our main deployment model is 100% cloud-based and provides the best solution in terms of price and scalability. It is a pure cloud SaaS platform with dynamic automatic scaling capable of integrating data from any location worldwide.

  • Easy, fast and automatic.
  • No costs for administrative personnel, licenses, or maintenance.
  • Unlimited GB/day of data collection.
  • Unlimited total data storage.
  • Limited time of retention according to your deletion policy.
  • Multiple Devo nodes worldwide.
  • High automatic scalability.
  • Access and data correlation from all over the world.

On-premises model

This option is appropriate for companies that need to manage extremely high volumes of data. By hosting the entire platform on-premise, the impact of network latency is eliminated. 

  • A scalable platform to manage extremely high volumes of data, including sensitive data.
  • Control the level of storage and performance needed.
  • Total control of the hardware performance.
  • Data storage capacity is limited to the hardware available. 

Considerations when using the on-premises model

  • Hardware support/maintenance.
  • Storage backups are not automatic.
  • Scalability is not automatic –initial scaling calculations.
  • Updates are not automatic.

Hybrid model

This option is appropriate if you need to keep all the data in your data center, but want to enjoy the advantages of a cloud-based service. In this case, data that has to meet stricter security rules can be stored on-premise, while the rest of the platform data is stored in the cloud. 

  • Full control of your data availability.
  • The data access and the correlation engine are cloud-based.
  • Control of the hardware used.
  • Limited total data storage according to your disk capacity.

Considerations when using the hybrid model

  • Hardware support/maintenance.
  • Storage backups are not automatic.
  • Scalability is not automatic.
  • Internet access problems could prevent the data access and analysis, but not the data collection process.

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