Op-Ed: Shortening transit outages with network observability

The morning rush hour on Friday, May 9, became a commuter’s nightmare in San Francisco as trains across Bay Area Rapid Transit (BART) lines came to a halt. The cause wasn’t an engine problem or a broken switch, but a faulty network component that failed to restart after a power outage. This resulted in intermittent visibility loss, where engineers could not see or communicate with the track circuits and train positions, leading to trains being held for nearly seven hours.  

The issue isn’t a one-off. A similar halt occurred in September after an overnight upgrade triggered a problem that prevented its communication systems from functioning properly. This is not unique to BART. Chicago’s Metra faced a similar outage on Oct. 14 when a telecommunications failure caused devices to revert their clocks to the year 2006, preventing Positive Train Control (PTC) devices from syncing with the trains as required by federal law.

Unfortunately, the cost of these technical issues is painfully real. For an agency like BART, a full day of lost ridership can result in a loss of almost $1 million in fare revenue, based on the average fare of $4.72 and October weekday ridership. That is before accounting for the reputation damage or federal fines, which can hit $25,000 per violation for safety interruptions.

Network and application issues can be difficult to diagnose, leading to lengthy troubleshooting processes that can extend delays. Synthetic monitoring and end-to-end network observability, such as that enabled through deep packet inspection (DPI), can offer relief by revealing where and how communications break down, providing a comprehensive picture for rapid and accurate root cause analysis. 

The network as a key vantage point  

Traditional network monitoring oftentimes cannot diagnose the why behind complex network-induced outages, as seen with Metra and BART. The key to unlocking this type of network observability is with packet data, specifically through DPI. 

Packet data represents raw, unbiased, real-time network traffic flowing throughout the system. If traditional monitoring is like looking at the outside of an envelope to see where it’s going, DPI is the X-ray that sees what’s inside. It is the ultimate source of truth for understanding system behavior, application performance and user experience. Consequently, utilizing DPI technology at scale to analyze traffic as it traverses the network allows for faster recognition of potential issues with the network or mission-critical applications.  

Consider a few scenarios where this could be the case: 

• Faulty software patch: A software update for a centralized traffic control system is attempting to communicate with databases but contains a malformed query. DPI can detect that. Following the update, the system experiences latency when it is attempting to send commands, so IT can reset the system. 
• Lost connection: Suddenly, technicians lose the ability to track sensors or cameras. Instead of sending a crew to check every wire, DPI pinpoints exactly which remote aggregation device is not sending any data, dramatically cutting troubleshooting time. 
• DNS failure: The network dashboard says everything is green, but passenger information displays are showing blank screens. A hidden DNS failure can cripple real-time mobile ticketing and station displays even when the network is technically up. Packet data reveals this disconnect immediately. 

Synthetic monitoring complements DPI by simulating user activity, such as buying a ticket or syncing a signal to detect emerging problems before they actually impact operations. This capability serves as an early warning system, identifying performance dips or connectivity issues in safety-critical environments before they snowball into an outage. By combining these early alerts with granular forensic data from DPI, IT teams gain a holistic view that pinpoints the true source of communication breakdowns, resulting in less finger-pointing when an outage strikes and improved average repair times.  

Getting back up and running 

While loss of fare revenue may be a short-term pain, recurring and prolonged outages can significantly damage an agency’s reputation. With millions of riders relying on public transit daily, it is essential that IT teams are equipped with the tools to enhance operational resilience.

Meeting the critical demands of rider safety, regulatory compliance and fiscal responsibility necessitates that safety-critical systems, such as PTC, are supported by end-to-end network observability. Without this capability, transit authorities remain vulnerable to the multimillion-dollar costs of extended outages and cumulative reputational damage. Therefore, adopting advanced network observability systems that leverage packet-level intelligence is a crucial step in mitigating risk and enhancing operational resilience.