Fills the gaps
to detect
production issues
| 1 | async function processOrder(order: Order) { | |
| 2 | const user = await getUser(order.userId); | |
| 3 | const payment = await chargeCard(user, order.total); | |
| 4 | + | Foam.setAttributes({ |
| 5 | + | "order.id": order.id, |
| 6 | + | "payment.status": payment.status, |
| 7 | + | }) |
| 8 | await sendConfirmation(user, order); | |
| 9 | return payment; | |
| 10 | } |
“Their CEO joined our alerts channel and never left. So when I asked for a feature on Friday night, it was live Saturday morning.”
“We were getting forty alerts a day. Now we get three a week, and the ones we get are real. Foam sits in our team channel instead.”
“Before our users even get to ping us, Foam has already debugged the error and pointed us to the cause in our team channel.”
“I used to lose a day or two triaging Sentry bugs per week. With Foam, I see them the moment they matter, already root-caused.”
Enter your site (or any site) to see what Foam would do for you
Automatically monitors what matters
Scans your codebase and online presence to understand what you care about, then automatically creates monitors around business outcomes and reliability.
Monitors Foam would create automatically for stripe.com
Product
Reliability
Errors
Fills telemetry gaps continuously
Ensures context is always added through its OpenTelemetry-based libraries so root causes and notifications are always high-accuracy and not noisy.
async function processOrder(order: Order) { const user = await getUser(order.userId); const payment = await chargeCard(user, order.total); Foam.setAttributes({ "order.id": order.id, "payment.status": payment.status, }) await sendConfirmation(user, order); return payment;}The right person, notified instantly
When it finds an issue that is novel or spiking, it pings the responsible engineer (not the git-blamed engineer) directly in their channel with root cause and fix links.
Root Cause & Fix Ready For Review
Every alert comes with a full investigation: the root cause, evidence from logs, traces, and code, and a PR ready to ship.
Payment success rate degradation
Payment success rate dropped from 99.7% to 94.2% after a config change to the retry policy in chargeCard().
PR #412 changed the retry backoff from exponential to fixed 50ms, causing connection pool exhaustion under load. The card network rate-limits kick in after 3 rapid retries.
Revert retry policy to exponential backoff with jitter. Cap max retries at 3 with 200ms base delay.