Kotlin error tracking
Know when your Kotlin app breaks, before your users do
ForgeOps connects the errors your Kotlin app reports to the deploys, traces, and changes around them, so when production breaks, the incident already says who's affected, what changed, and where to look.
A typed, coroutine-backed rewrite of the Java client, for JVM server-side apps. Running on ForgeOps' own dedicated infrastructure, so nothing about a Kotlin app's errors or its users' data gets routed through a third-party error-tracking vendor. See an incident investigated →
Install
<dependency>
<groupId>io.github.luke-popwell</groupId>
<artifactId>tracker-kt</artifactId>
<version>0.12.0</version>
</dependency>
import io.github.lukepopwell.tracker.ForgeOpsTracker
ForgeOpsTracker.init { config -> config.dsn = "https://<api_key>@getforgeops.net/api/v1/events" }
A typed, coroutine-backed rewrite of the Java client, for JVM server-side apps.
Every client reports the same shape
Wherever it comes from, an event arrives with an exception class, a message, and a backtrace, plus whatever environment/release/server context that client can gather on its own. ForgeOps fingerprints and groups on the first three, so a Kotlin app's issues list works exactly the same way every other language's does: report the same bug a thousand times and it's still one row, not a thousand.
No agent, no sidecar: it's a plain HTTPS POST to ForgeOps' own ingestion API, so nothing about a Kotlin app's traffic gets routed through a third-party pipeline first.
Works with your framework
The Kotlin client hooks in at the framework level, not by wrapping individual calls, so nothing about how you already write Kotlin code has to change.
Servlet 5+ / Spring MVC / Boot
The same JVM integrations as sdks/java apply here too, since a servlet filter or a @ControllerAdvice bean is still a real JVM type underneath.
Plain JVM apps
captureException reports directly from a catch block, with optional context. Errors and recorded changes still queued when a program exits are sent by a shutdown hook (waiting at most 5 seconds); call ForgeOpsTracker.flush() before Runtime.halt.
What it looks like
The issue list
Every Kotlin issue reported into a project shows up here: title, status, assignee, event count, and when it was last seen, the same columns as any other language's project.
The issue detail
Every occurrence keeps its own timestamp, environment, release, and server, plus the backtrace exactly as Kotlin reported it, expandable per occurrence rather than flattened into one generic stack.
Alerting
A new Kotlin issue, a regression, or a spike past a threshold you set can reach Slack, Microsoft Teams, email, PagerDuty, Opsgenie, or a generic webhook, configured per project, per trigger.
Heartbeats
For the failure mode error tracking can't see on its own: a Kotlin cron job or recurring task that's supposed to run but silently stopped. Each heartbeat gets its own ping URL and its own grace period before it alerts.
Performance monitoring
Times whatever you wrap and reports one small aggregate per transaction, flushed on performanceFlushInterval, never one network call per timed call. This client has no web framework integration, so nothing is timed automatically: you choose what to wrap. Keep transaction names low-cardinality ("GET /users/:id", not "GET /users/42"), since every distinct name is its own row. timeTransaction records even if the block throws. Turn it off with trackPerformance = false. A JVM shutdown hook flushes the last partial window on a normal exit; flushPerformance() sends it sooner. Each report also carries a small latency histogram, so ForgeOps shows an approximate p50/p95/p99 per transaction, not just an average, accurate to the width of the latency bucket a duration falls into. Requires a plan that includes performance monitoring; on a plan that doesn't, the periodic reports are accepted but not recorded (the response says why), so a working setup never looks broken.
// Wrap a whole request handler, or any block you want on the Performance page:
val response = ForgeOpsTracker.timeTransaction("GET /users/:id") { handleRequest(request) }
// Or record a duration you measured yourself:
ForgeOpsTracker.recordPerformance("nightly-export", elapsed.toMillis().toDouble())
Distributed tracing
This client has no web framework integration, so you choose the unit of work to trace: wrap it in trace, and anything inside it can add spans. Only a slow call's trace is ever sent: whether it crossed the threshold (one second by default, configurable) is decided entirely inside your process, so a fast call costs nothing over the wire. Requires a plan that includes distributed tracing.
val response = ForgeOpsTracker.trace("GET /checkout") {
val order = ForgeOpsTracker.span("load order", "database", mapOf("orderId" to id)) { repo.find(id) }
ForgeOpsTracker.span("charge card") { gateway.charge(order) } // kind defaults to "service"
render(order)
}
// Something you timed yourself (kind is one of controller/service/database/redis/http/job/other):
ForgeOpsTracker.recordSpan("SELECT orders", "database", startedAt, durationMs)
Continue the caller's trace by passing a request's own traceparent header to trace, and pass it on by wrapping an outbound call in httpSpan, which records it and hands you the headers to add. An error captured inside the trace carries its trace id, so once the projects are linked in ForgeOps it shows next to the errors the other side raised in the same request. Needs tracker-kt 0.8.0.
ForgeOpsTracker.trace("POST /orders", request.getHeader("traceparent")) {
val response = ForgeOpsTracker.httpSpan("POST", paymentsUri) { headers ->
val call = HttpRequest.newBuilder(paymentsUri).POST(BodyPublishers.ofString(body))
headers.forEach { (name, value) -> call.header(name, value) }
httpClient.send(call.build(), HttpResponse.BodyHandlers.ofString())
}
}
SQL in a request
When the request an issue failed in was traced, the issue opens with its slowest query: how long it took, its share of the request's time, how many queries the request ran, and a likely N+1 warning when the same statement ran five or more times. This client doesn't instrument a database driver, so pass a query's SQL as statement on a database span. The statement is masked before it leaves your process, every string and number replaced with a question mark, and the same SQL shows under that span's bar in the trace's waterfall. Needs tracker-kt 0.10.0, on a plan that includes distributed tracing.
val sql = "SELECT * FROM orders WHERE customer_id = 42 AND status = 'open'"
ForgeOpsTracker.trace("GET /orders") {
val orders = ForgeOpsTracker.span("Load orders", "database", statement = sql, dbSystem = "postgresql") {
connection.createStatement().use { it.executeQuery(sql).toOrders() }
}
render(orders)
}
// Sent as "SELECT * FROM orders WHERE customer_id = ? AND status = ?"
What changed
When a feature flag flips or a remote config value changes, record it from your flag client's callback, and it shows under What changed on any issue that starts in the next two hours, and on the project's Changes page beside your deploys, labeled potentially relevant, never as the cause. "Errors started right after new_checkout turned on" becomes one glance. recordChange returns immediately: a background coroutine sends it, never the calling thread, and it never throws. Every change is one you record. Needs tracker-kt 0.9.0, on a plan that includes change tracking.
import io.github.lukepopwell.tracker.ForgeOpsTracker
// Your flag client's change listener, with the key and the old and new values
flagClient.addFlagChangeListener { key: String, oldValue: Boolean, newValue: Boolean ->
ForgeOpsTracker.recordChange(
"feature_flag",
"$key turned ${if (newValue) "on" else "off"}",
details = mapOf("key" to key, "from" to oldValue, "to" to newValue),
actor = "flag-service",
)
}
Custom metrics and infrastructure monitoring
Track a business event you name yourself (a signup, a payment) or a reading from one of your own hosts, with one explicit call each; nothing is automatic. The value defaults to 1, so a bare call is a counter; pass a real amount for anything else (it can be negative, for a refund). A captured value is stored as its own row, so counts and sums you compute later are exact. Calls are buffered and flushed as one batch in the background, so they are safe to make inside a request, and flushMetrics sends whatever is buffered right now. The hostname of an infrastructure reading defaults to the configured server name. Requires a plan that includes custom metrics and infrastructure monitoring.
ForgeOpsTracker.captureMetric("signup") // value defaults to 1.0: a bare counter
ForgeOpsTracker.captureMetric("payment", 49.0) // a real magnitude; it may be negative (a refund)
ForgeOpsTracker.captureInfrastructureMetric("cpu", 0.42) // hostname defaults to serverName
ForgeOpsTracker.captureInfrastructureMetric("disk", 0.81, hostname = "db-1")
ForgeOpsTracker.flushMetrics() // optional: send right now
Database errors
When an error comes from a database call, the issue shows which stored procedure, table or view its SQL touched, so you know where to start looking. Hibernate's JDBCException and Spring's BadSqlGrammarException expose the statement through getSQL() or getSql(), read by reflection, and SQLite's while-compiling error text is recognized too. The names are sent by default and are identifiers, never values. The SQL statement itself is opt-in, with every string and number replaced by a question mark before it leaves your app, and a project setting can stop ForgeOps storing the statement at all.
ForgeOpsTracker.init { config ->
config.dsn = "..."
config.captureSqlStatement = true // default false
// config.captureSqlObjects = false // default true; false stops even the names
}
Questions
Do I need to change how I already handle errors?
Almost never. Every client hooks the framework's own exception handling directly, the same way the install snippet above shows, so your own logs, error pages, and rescue blocks keep working exactly as they did before, and ForgeOps just also finds out about it. The one common exception is a background-job runner that doesn't forward through that same mechanism on its own; that needs one small hook added instead, not a change to anything already there.
Where does the data actually go?
Straight to ForgeOps' own ingestion API over plain HTTPS. No agent, no sidecar, and no third-party ingestion service in between, so nothing about your app's traffic or its users' data gets routed through anyone else's pipeline first.
What happens if the same bug fires a thousand times?
It's fingerprinted from its exception class, message, and backtrace, so a thousand reports of the same bug still show up as one issue with an event count of 1,000, not a thousand separate rows to dig through. And a runaway loop can't use up your monthly event quota: once one issue repeats faster than your plan's hourly limit (50 an hour on Free), further repeats are still counted, and still count toward spike alerts, but they aren't stored or charged to your quota.
Is anything scrubbed before it's stored?
Yes. Emails, credit card numbers, and known API key/token formats are redacted out of every event before it's even written, on every plan, with room for per-project custom field names on top of the defaults.
Try it with your own Kotlin app
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