Furnace allows you to spend less time designing and managing infrastructure, leaving you more time to focus on doing great things with your data.
A platform that Dev, Sec and Ops love.
Furnace makes it easy to build highly effective teams that can respond to a continuously changing landscape, using best practices and a modern technology stack.Get Started Now
A single deployment experience across multiple platforms
Furnace utilises native infrastructure and functionality to maximise efficiency
By scaling services as required Furnace ensures you're only using what you need
Describe your entire data pipeline in code and have Furnace handle the deployment into multiple environments
Furnace aligns itself with the emerging GitOps methodology, where Git is the single source of truth bringing many benefits to modern development teams.
Providing huge efficiency wins, no longer do you need to stand up stacks of infrastructure that costs even whilst idle.
Furnace provides a set of simple contructs that are the building blocks of your data pipeline.
Defines source of data, usually this is stream from Apache Kafka or AWS Kinesis but can be anything you define. We provide some standard sources out of the box.
Taps connect to a source. Their job is to parse and normalise data into a common format. A default set of Taps are provided and new Taps can be created by simply writing a serverless function.
Pipelines create a linear path for data to flow through a chosen set of functions. Pipelines are connected to Taps and a Tap can feed multiple Pipelines.
A Sink is where your data arrives after it exits a Pipeline. A sink could be a data lake or storage bucket. Multiple Pipelines can feed into a Sink and a Pipeline can feed into multiple Sinks.
Resources are used to initiate resources native to the environment in which Furnace is being deployed.
Once data has been processed by your pipelines, Actions make use of the structured data react and automate tasks in real-time.
A Stack is comprised of one or more end to end data flows into a logical container. A Stack can have multiple environments (Dev, Staging, Production).
Furnace targets a number of uses cases across Security, IoT and many other streaming data needs. Over the coming months we'll be releasing more exmples of how to use Furnace, starting with a popular use on Amazon Web Services.
Our AWS reference application makes use of VPC Flow Logs via CloudWatch Logs to anaylse traffic flowing over a Virtual Provide Cloud.
The Tap decodes the data, normalises it into a common format, and pushes it into AWS Kinesis for further processing by the Pipeline
As the Pipeline receives events from the Tap, they are sent through a series of steps, adding further AWS metadata and Geo Location of IP addresses.
AWS provides various managed Big Data storage and analysis services including ElasticSearch, RedShift and even S3. Furnace integrates into many of the AWS services.
Back in 2016, our team began researching the technologies in which Security Operations Center’s were using to protect the broad range of customers they monitor. Security Information and Event Management (SIEM)...
Follow this guide for step by step guidance on building a Furnace stack on AWS from a CloudWatch Logs Stream thought a processing Pipeline and into an ElasticSearch Sink.
Furnace aims to add native support for all major Cloud Providers, we'll be adding more in the coming months.
We mean business and are following an aggressive roadmap into 2019
We're launching with support for the AWS Cloud and GitHub as a Source Repository with tight integrations into both.
We're going to add support for writing modules in Python and Go as well as the ability to run Furnace on Microsoft Azure and Google Cloud Platform.
Constructs to connect cloud based applications to legacy on premise platforms.