{"id":34162,"date":"2026-06-18T02:50:49","date_gmt":"2026-06-18T02:50:49","guid":{"rendered":"https:\/\/www.dotcom-monitor.com\/blog\/?p=34162"},"modified":"2026-09-21T23:35:29","modified_gmt":"2026-09-21T23:35:29","slug":"concurrent-vs-round-robin-monitoring","status":"publish","type":"post","link":"https:\/\/www.dotcom-monitor.com\/blog\/concurrent-vs-round-robin-monitoring\/","title":{"rendered":"Concurrent vs Round-Robin Monitoring Explained"},"content":{"rendered":"
\"Diagram
Round-robin rotates through locations one at a time; concurrent checks them all on every cycle.<\/figcaption><\/figure>\n

You’re setting up synthetic checks from eight locations. Should every location run on every cycle, or one location at a time in rotation? That one setting decides how fast you catch a regional outage and how many checks you burn doing it.<\/p>\n

Most monitoring platforms pick a default and hide the choice. Dotcom-Monitor exposes it, and the two options behave differently enough that the wrong pick either floods you with redundant checks or lets a regional failure sit unnoticed for a full rotation. Here’s how round-robin and concurrent monitoring actually work, where they diverge, and how to choose.<\/p>\n

One thing to clear up first. This is not round-robin load balancing. Load balancers use round-robin to spread incoming user traffic across backend servers. Here, round-robin describes how a monitoring platform schedules its own outbound checks across geographic locations. Same name, opposite direction of traffic.<\/p>\n

What Round-Robin and Concurrent Monitoring Mean<\/h2>\n

Two terms make the rest of this easier to follow. A monitoring session<\/strong> is a single check run from one location. A monitoring cycle<\/strong> is one full pass across all the locations you’ve selected.<\/p>\n

Round-robin and concurrent describe how sessions get spread across a cycle. Round-robin runs one location per cycle and rotates to the next location next time. Concurrent runs every location on every cycle. The gap between those two patterns is where detection speed, cost, and data quality all get decided.<\/p>\n

How Round-Robin Monitoring Works<\/h2>\n

Round-robin is the default, and it’s built to be economical. At your configured frequency, the platform fires a session from one location, then the next location on the next interval, cycling through your list. As long as every check agrees that the site is up, you get broad geographic coverage without paying to test all eight locations at once.<\/p>\n

The clever part is what happens on disagreement. The moment one location reports a state that differs from the rest, say an error while the others succeed, round-robin stops rotating and runs sessions from all<\/em> locations. It does the same thing right after you create, edit, or restart a device, when it has no baseline to trust yet.<\/p>\n

So round-robin isn’t blind to regional problems. It’s adaptive. It stays cheap while everything looks healthy and escalates to full coverage the instant something looks off. The cost of that thrift is timing, which the next sections get into.<\/p>\n

How Concurrent Monitoring Works<\/h2>\n

Concurrent monitoring drops the rotation. Every selected location runs its session on every cycle, no matter what the previous cycle reported. Eight locations at a one-minute frequency means eight checks a minute, every minute.<\/p>\n

That gives you a complete geographic snapshot on each interval. If your CDN edge in Frankfurt slows down while everywhere else stays fast, you see it on the next cycle instead of waiting for the rotation to land on Frankfurt. On Dotcom-Monitor, concurrent monitoring is an add-on that needs to be activated, and because it multiplies your check volume, it can raise your package price.<\/p>\n

Detection Speed Versus Monitoring Cost<\/h2>\n

The whole decision comes down to a trade between how fast you spot a location-specific failure and how many checks you’re willing to spend.<\/p>\n

\n\n\n\n\n\n\n\n\n\n\n
Factor<\/th>\nRound-Robin<\/th>\nConcurrent<\/th>\n<\/tr>\n<\/thead>\n
Locations per cycle<\/td>\nOne, then escalates to all on an anomaly<\/td>\nAll, every cycle<\/td>\n<\/tr>\n
Regional outage detection<\/td>\nUp to one rotation of delay<\/td>\nImmediate<\/td>\n<\/tr>\n
Check volume<\/td>\nLow while healthy<\/td>\nHigh and constant<\/td>\n<\/tr>\n
Per-location SLA data<\/td>\nSparse and uneven<\/td>\nContinuous and comparable<\/td>\n<\/tr>\n
Cost<\/td>\nIncluded default<\/td>\nPaid add-on<\/td>\n<\/tr>\n
Best fit<\/td>\nBroad uptime coverage<\/td>\nGeo-sensitive apps and strict SLAs<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Detection delay is the figure people underestimate. With round-robin, a failure that only hits one region waits until the rotation reaches that region before the error fires and triggers full escalation. Across eight locations on a five-minute frequency, that’s up to 40 minutes of a regional outage before the platform reacts. Concurrent closes that gap to a single cycle.<\/p>\n

The flip side is data. Because concurrent tests every location continuously, it produces an even, comparable record per location, which is exactly what you need to prove a regional SLA or chase down a slow CDN edge. Round-robin’s record is sparser and harder to compare location against location. If you’re tracking the cost of downtime<\/a> by region, that difference matters.<\/p>\n

Why Browser-Based Checks Run One at a Time<\/h2>\n

There’s a wrinkle that catches people configuring real-browser checks. Dotcom-Monitor has an Allow Simultaneous Checks<\/strong> setting that controls whether all-location runs fire at the same moment or one after another. For HTTP-based checks (ServerView and WebView) it’s on by default, because each request is stateless and independent, so firing them at once is safe. For browser-based checks (BrowserView and UserView) it’s off and can’t be changed.<\/p>\n

The reason is state. A lot of web apps tie a logged-in session to one set of credentials. Sign in from a second location and the first session gets kicked out. Run a multi-step EveryStep transaction<\/a> from five locations at once and they’ll trip over each other, producing false failures that have nothing to do with your app’s real health.<\/p>\n

Shared state breaks under parallel access. A cart, a booking record, or an inventory count updated by five simultaneous sessions returns results that don’t reflect what a single user would see.<\/p><\/blockquote>\n

So even under concurrent monitoring, browser-based sessions run sequentially by design. You still get every location on every cycle. They just don’t fire at the same instant, which keeps credential conflicts and shared test data from poisoning your results.<\/p>\n

When Round-Robin Is the Right Default<\/h2>\n

Round-robin is the right call more often than its modest reputation suggests. Reach for it when:<\/p>\n