Kratos Runs Lambda On Multiple Clouds
Written by Kay Ewbank   
Wednesday, 24 February 2016

A new project is underway that will let companies run AWS Lambda functions on non-Amazon clouds.

The project has been developed by Iron.io, best known for its job processing system that manages the distribution of tasks across public or private clouds. The announcement of Project Kratos extends this ability to enable the running of AWS Lambda functions on multiple clouds.

AWS Lambda is a service that developers can use to run Java, Node.js and Python code on Amazon's public cloud. The code consists of functions, and when events such as database updates happen, AWS launches the instance required to run the code. The developer is completely shielded from the operational details.

The advantage Kratos offers is that it offers an alternative to AWS, so you can run the Lambda functions (moved into Docker containers) on Azure, Google, or your own data center. Support for the recently announced Google Functions is also to be added.

By running Project Kratos on the Iron platform, users also have access to features including intelligent workload distribution, auto-scaling, reporting and dashboards. However, the main benefit is that of being free to choose which cloud provider you want to use - though only by tying in to the Iron.io platform.

Alongside the announcement of Project Kratos, Iron.io released details of improvements to its job processing system, with the addition of role-based control and autoscaling. The role-based control adds support for multiple users, while the autoscaling continuously monitors queue sizes and makes sure enough computing capacity is made available when spikes occur.

Project Kratos is currently being developed, and the company is inviting interested developers to become project members, who will provide input and feedback as the project is developed. Project members will have the option of becoming beta users.

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More Information

Project Kratos Beta Program

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Last Updated ( Wednesday, 24 February 2016 )