Automation Technology at Boston University

Higher education leaders are directing their institutions to incorporate the strategies of business school academics to increase operation efficiency and maintain a high level of service to administration, faculty and student “customers.” Ensuring the reliability of an institution’s Information Technology (IT) systems, which today underpin nearly all facets of campus life, is critical to achieving these objectives. Increasingly, advanced automation technology is enabling universities such as Boston University (BU) to achieve tight control over the performance of their technology infrastructures, with greater consistency and fewer resources.

BU’s Administrative Computing Services (ACS) team has taken an active role to assure a high level of systems uptime and automation in support of the university’s administrative computing requirements. ACS plays a key role in supporting the university’s population of more than 30,000 students, who come from all 50 states and 135 countries. Additional international student federal registration and reporting mandates enacted after September 11, 2001, make performance and availability critically important to serving BU’s foreign student population, nearly 5,000 students, each semester.

In the late 1980s, ACS’s mission was to establish an unattended data center that would improve the overall availability and reliability of its computing environment and better serve its user community. Automation of BU’s performance monitoring and service management operation in the early 1990s was a fundamental requirement for achieving this objective. To support its unattended data center initiative, automation systems were required to:

  • Ensure a high level of systems availability;
  • Reduce the potential for human error by enabling automation routines for specialized and complex system requirements;
  • Notify university staff immediately in the event that a system issue could not be corrected automatically.

After reviewing its options, the ACS team selected the AF/OPERATOR automation system from Candle Corporation to build a set of automation rules and routines for its mainframe and distributed environments. AF/OPERATOR is a performance and console automation system that addresses a critical data-center need to reduce human error and respond as quickly as possible to system events displayed on the console.

The Administrative Computing Services’ automation capabilities manage all system alert activity for zSeries mainframe, Unix, and Windows servers hosted by ACS. Automation is the backbone of the ACS operational environment and so new technologies deployed in the data center are integrated with the automation system.

Without automation capabilities, BU would be required to add staff to deliver these same quality services. A critical use of automation technology at BU is monitoring the 2,500 batch jobs—relating to student accounting, registration, housing and federal reporting requirements, along with all the usual business functions—that the university’s ACS runs daily. BU is thus able to build automatic responses to conditions that occur during processing, which leads to a more consistent level of systems performance and management.

The systems threshold management capabilities allow ACS to monitor for fluctuations in critical system resource metrics and automatically react and/or notify appropriate personnel to take action before a serious problem occurs. Suppose, for example, a non-interruptible power supply generates an event indicating that the ACS department has lost building power and is operating on batteries. The automation tool notifies active online users and support staff of the outage, and then starts the process of executing a managed shutdown of the university’s administrative business systems, rather than risking database integrity waiting for an abrupt crash when battery power would be exhausted.

BU’s automation system simplifies remote data center management and increases staff productivity and system availability, while at the same time minimizing manual intervention in the data center. Given that AF/REMOTE is the primary means of automated notification, BU operates both a primary and a hot-standby version of AF/REMOTE, which are networked and synchronized.

Since deploying systems management automation technology, BU achieved its goal of an unattended data center, while enhancing quality of services, increasing system availability, reducing operating expenses, and improving the quality of life for the support staff.

Featured

  • glowing digital brain-shaped neural network surrounded by charts, graphs, and data visualizations

    Google Releases Advanced AI Model for Complex Reasoning Tasks

    Google has released Gemini 2.5 Deep Think, an advanced artificial intelligence model designed for complex reasoning tasks.

  • abstract pattern of cybersecurity, ai and cloud imagery

    OpenAI Report Identifies Malicious Use of AI in Cloud-Based Cyber Threats

    A report from OpenAI identifies the misuse of artificial intelligence in cybercrime, social engineering, and influence operations, particularly those targeting or operating through cloud infrastructure. In "Disrupting Malicious Uses of AI: June 2025," the company outlines how threat actors are weaponizing large language models for malicious ends — and how OpenAI is pushing back.

  • cybersecurity book with a shield and padlock

    NIST Proposes New Cybersecurity Guidelines for AI Systems

    The National Institute of Standards and Technology has unveiled plans to issue a new set of cybersecurity guidelines aimed at safeguarding artificial intelligence systems, citing rising concerns over risks tied to generative models, predictive analytics, and autonomous agents.

  • magnifying glass highlighting a human profile silhouette, set over a collage of framed icons including landscapes, charts, and education symbols

    AWS, DeepBrain AI Launch AI-Generated Multimedia Content Detector

    Amazon Web Services (AWS) and DeepBrain AI have introduced AI Detector, an enterprise-grade solution designed to identify and manage AI-generated content across multiple media types. The collaboration targets organizations in government, finance, media, law, and education sectors that need to validate content authenticity at scale.