TECHNICAL ARCHITECTURE

Designed for the most complex decisioning implementations

  • Cloud-native, flexible deployment, and open standards
  • Built-in security, governance, and audit/system monitoring
  • High performance, high availability, and scalability
SMARTS™ Technical Architecture

See SMARTS™ Technical Architecture in Action

CLOUD-NATIVE, FLEXIBLE DEPLOYMENT, AND OPEN STANDARDS

Technical architecture built from the ground-up for the cloud

  • Install on AWS, GCP, Azure, Aliyun or on-prem
  • Redeploy in a different environment without needing to recode
  • Use all modern enterprise application standards for decision management
    • Decision Model and Notation (DMN) for decision modeling
    • PMML for predictive modeling
    • .NET or Java for deployment in both real-time and batch modes
    • Other standards include OpenAPI, OpenMetrics, CloudEvents, JSON-RPC, OAuth, and OpenID
SMARTS™ technical architecture allows you easily integrate data, models, and operations into your business process

Integrate SMARTS™ into your business process through an API call

OpenMetrics dashboard example

Example Technical Monitoring through OpenMetrics

BUILT-IN SECURITY, GOVERNANCE, AND AUDIT/SYSTEM MONITORING

Manage users, changes, and system health at multiple levels

AUTHENTICATION

  • Use our authentication system or integrate with your own
  • Includes Microsoft AD LDS, Microsoft and Google accounts, LDAP, WS-Federation, and OAuth2 protocols

ACCESS CONTROL

  • Assign roles for each user that has been authenticated
  • Control what users can access and what tasks they can perform

CHANGE CONTROL

  • Track changes through versioning and alerts
  • Easily identify when a change is made, what was changed, and by whom

RELEASE MANAGEMENT

  • Create read-only releases that can be published in your staging and production environments for testing and deployment
  • Quickly rollback a release when necessary

SECURITY MONITORING

  • Protect against malicious interactions
  • Monitor data and programmatic calls in real-time

TECHNICAL MONITORING

  • Manage SMARTS™ like the rest of your IT system
  • Use your system monitoring tool of choice (ex. Docker Logging, Prometheus, and OpenMetrics)

HIGH PERFORMANCE, HIGH AVAILABILITY, AND SCALABILITY

Execute high-volume, complex decisions fast

  • Bytecode-level (AOT / JIT) expressions, indexing, and algorithms
  • Manage thousands of complex data sets, rules and models
  • Process millions of transactions a day
  • Adapt to your evolving enterprise architecture and governance model

Ensure your application is always up and running

REPLICATION

  • Create multiple instances of the same application
  • Replicate specific code, data, and user repositories

LOAD BALANCER

  • Distribute the work of your application through our built-in load balancer
  • Meet your desired uptime and response time requirements
Diagram shows how the technical architecture supports auto-scaling in production

Replication and load balancing ensure that there is no single point of failure. Achieve high availability in development and auto-scaling in production.

FEATURED BLOG POSTS

Technical Series:  Business Performance

Technical Series: Business Performance

In our last two blog posts in this series we discussed decision engine performance and how performance is impacted by deployment architecture choices. In addition to those considerations, you should also focus on business decision performance, the topic of this post....

Technical Series: Deployment Architecture and Performance

Technical Series: Deployment Architecture and Performance

In our last post we discussed Decision Engine Performance and how SMARTS provides different engines that are optimized to their specific application. In this post we will cover how deployment architecture choices impact performance. SMARTS provides you higher level...

Technical Series: Decision Engine Performance

Technical Series: Decision Engine Performance

One of the subjects that frequently comes up when considering decision engines is performance, and, more broadly, the performance characterization of decisions: how do decision engines cope with high throughput, low response, high concurrency scenarios? In fact, the...