Nightingale
Industries Use Cases Platform Technology Team

Automated Decisions for a Streaming World

Developments in technology have allowed businesses to scale further and to adapt faster than ever before. However, these same technologies have introduced a new set of challenges. The rising complexity of business critical systems imposes a tremendous pressure on businesses: the pressure to automate. Founded by an accomplished team from Stanford and Ayasdi, Nightingale is bringing to market a new, proprietary technology that automates system decision making from streaming big data, enabling a new Management Intelligence. Nightingale is working with companies in the enterprise IoT, networking, and IT markets and has demonstrated the performance and value of this technology in each of these areas.

Industries

Nightingale's technology and platform address pressing management challenges across a wide range of markets. Nightingale's platform represents an automated Managment Intelligence solution for industries overwhelmed by big streaming data and tightening decision loops. In the following industries, recent trends have made Management Intelligence imperative:

Enterprise IoT

Comprehensive instrumentation and monitoring has overloaded manual operator decision-making. Mangement Intelligence makes automated data-driven decisions based on millions of sensor values per second possible.

Software Defined Networking

As virtualization penetrates all layers of the datacenter, abstraction introduces complexity. Management Intelligence is necessary to maintain performance and reliability in a constantly changing system.

IT Admin & DevOps

Business demands require shifting to a hybrid cloud model and custom applications with countless interacting systems and people. Only Management Intelligence ensures availability in complex environments.
In asset intensive businesses, revenue is tied directly to equipment uptime. With compehensive monitoring, operators are subject to more equipment alarms than ever before. Each alarm requires substantial manual triage, inspection, and resolution. However, standard monitoring techniques are vulnerable to false alarms, which expend operator resources and result in unplanned downtime. Nightingale's Managment Intelligence has demonstrated over 40% improvement in false alarm rates.
Application Delivery Controllers (ADCs) shape network traffic for performance, reliability, and security. However, they require extensive configuration based on the characteristics of the application, current load, and network topology. In a Software Defined Network, all of these factors change rapidly, making manual reconfiguration prohibitively expensive. Nightingale's Managemenent Intelligence can reconfigure ADCs in response to changing system conditions much faster than humans, reducing the burden for IT administrators.
When custom applications directly impact revenue, keeping them online is essential. However, they are difficult to maintain because documentation is scarce, and knowledge is distributed between developers who may no longer be available. Nightingale's Management Intelligence is able to learn the characteristics of custom applications without examining or modifying the code. With this automatic centralized understanding, triaging and resolving issues becomes orders of magnitude more efficient.

Use Cases

System Automation

Dramatically reduced human intervention in complex systems

Rapid Issue Resolution

Reduced mean time to resolution keeps businesses running smoothly

Accurate and Early Warnings

Early warning and forecasting prevents costly downtime

Optimized Performance

Automated tuning based on system characteristics and load

Increased System Reliability

Automatic issue resolution learned from operator actions

Knowledge Standardization

Standardized knowledge across operators maximizes efficiency

Platform

Nightingale's Management Intelligence works with business critical systems and users at all levels in the organization. Administrators and operators effortlessly apply automated decision policies. Managers evaluate the performance of these policies over time, enabling steady operational improvement. Executives obtain a comprehensive and immediate understanding of how the critical elements of their businesses behave, allowing timely response to changing business demands.

Business Agility

Operational Excellence

Pervasive Automation

Nightingale Management Intelligence
Nightingale Management Intelligence
Infrastructure Monitoring Platform
Business Infrastructure and Applications

Nightingale's Management Intelligence sits on top of monitoring platforms, tying together machines and operators with adaptive intelligence that learns rapidly over time. Nightingale's platform is built to handle growing complexity and deploy effortlessly regardless of the customer's configuration with its modern stack: Apache Spark, Node.js, HTML5.

Technology

Nightingale's proprietary technology was developed at Stanford. It rapidly condenses large quantities of complex streaming data into succinct summaries without manual data science. These summaries provide the robust system representation necessary for automated decision making. For a detailed discussion of Nightingale's technology and its relationship to existing techniques click here.

Streaming Data

State Summary

Automated Action

Founding Team

Dan O'Neill

CEO & CTO
Assistant Professor Research Stanford
Sr. Director SUN Microsystems
GM and Director Texas Instruments
Ph.D./MBA Stanford/Berkeley

Sachin Adlakha

Data Scientist
Sr. Data Scientist Ayasdi
Software Engineer Texas Instuments
Ph.D. Stanford

Peter Pham

Software Architect
Sr. Algorithms Developer Ayasdi
M.S. Stanford

Technical Advisory Board

Steven Boyd

Samsung Professor of Electrical Engineering and Computer Science Stanford
Optimization
National Academy of Engineering
Fellow IEEE
Fellow SIAM
Director Information Systems Lab Stanford University

Trevor Hastie

Overdeck Professor of Statistics Stanford
Statistical Learning
National Academy of Sciences
Fellow American Statistical Society

Sanjay Lall

Professor of Electrical Engineering Stanford
Control
Fellow IEEE