Trace every request across your distributed systems.
Service-centric APM built from tracing data and RED metrics. Compare latency, throughput, error rate, and dependencies, then drill into the trace and logs behind any slowdown.
APM breaks down when teams can see an unhealthy service but can’t quickly reach the dependency, trace, or span that caused it.
KloudMate keeps service-level health, dependency analysis, trace detail, and request logs in one connected workflow so engineers can move from symptom to evidence without switching tools.
What teams can do with KloudMate APM
Ground service health in tracing data, then move from an outlier to the exact request path behind it.
Compare service health in one APM view
See requests, throughput, error rate, and P99, P95, and P50 latency for every instrumented service so regressions stand out quickly.
Monitor every API endpoint
Track rate, errors, and latency for each HTTP and RPC endpoint, then drill from a failing endpoint straight into its traces.
Search traces by span attribute
Filter traces by method, status, database, or any span attribute you tag yourself, and reuse saved queries to isolate a single request path.
Inspect dependencies with a live service map
Understand topology and traffic flow from tracing data, then inspect nodes and edges to find high-latency or erroring dependencies.
Pivot from APM to traces and logs
Open a service dashboard, inspect recent traces, and move into request logs without copying trace IDs between disconnected tools.
Instrument the way your stack needs
Start with eBPF-based observability, use the KloudMate Agent in Kubernetes, or connect manual OpenTelemetry instrumentation for deeper spans.
From service health to request evidence in one investigation path.
Start in APM Views when you need service health and dependency analysis. Move to Trace Explorer when you need request-level detail.
Spot the unhealthy service
Start in APM Views to compare request volume, error rate, and latency percentiles across services in the selected time range.
Narrow to the failing endpoint
Open API Monitoring to compare rate, errors, and latency for every HTTP and RPC endpoint on that service, and sort to the one that is actually failing.
Check the dependency graph
Use Service Map to see which node or edge is carrying the traffic path and whether any dependency is surfacing errors.
Drill into a representative trace
Move into Trace Explorer, choose the trace that matches the incident, and inspect span timing, attributes, and the request waterfall.
Read the request logs in context
Open the request logs linked to that trace to confirm the failure mode and gather the evidence needed for the next investigation step.
Get traces without changing your application code
Pick what fits your stack. Both run alongside your services, no code changes required.
Kernel-level visibility. Zero SDK.
Captures service calls, network I/O, and system calls at the kernel level. No library to add, no application restart, no code changes. Works across any language or runtime on Linux.
- No SDK to install or maintain
- Any language: Go, Java, Python, Node, Ruby, PHP
- Works on bare metal, VMs, and containers
Auto-instrument every workload in your cluster
Deploy the KloudMate Agent once as a DaemonSet. It auto-instruments every pod in the cluster and generates OpenTelemetry-compatible spans, no annotations, no sidecars, no per-service work.
- Deploy once, covers every workload
- Spans appear in APM and Trace Explorer immediately
- Add manual OTel instrumentation for custom spans and attributes
Already using OpenTelemetry SDKs? Manual instrumentation works alongside both. Add custom spans and attributes for business logic the auto-instrumentation can't see.
Spot the slow or failing service
The Services overview puts requests, error rate, and latency percentiles for every instrumented service on one screen, so a slow or failing service stands out instead of hiding in an average.
- Compare requests, throughput, and error rate across all services in the selected time range
- Use p99, p95, and p50 latency to spot outliers instead of relying on averages alone
- Correlate a performance shift with the service version that introduced it
See which endpoints are slow, failing, or busy
API Monitoring breaks each service down to its individual HTTP and RPC endpoints and reports rate, errors, and latency for every route, built entirely from the spans your services already send.
- Sort endpoints by throughput, error rate, or p95 to surface the worst offenders first
- Covers HTTP and RPC alike: gRPC and Connect endpoints get an error rate even without HTTP status codes
- Open an endpoint for its request, error, and latency trends, then jump to its recent or failed traces
Inspect dependency flow with the live Service Map
Service Map is generated from tracing data, so topology stays tied to real traffic. Inspect a service node, inspect an edge, and follow the path that is carrying the incident.
- See request rate and average latency on service nodes and dependency edges
- Highlight erroring services and dependencies instead of reading a static architecture diagram
- Open the source or target service page directly from the dependency you are investigating
Search traces by any span attribute
When you need one specific request, Trace Explorer searches every trace by span attributes like http.status_code, db.statement, or your own tags, then opens the full waterfall behind it.
- Filter on any span attribute, not just service or status, and save the queries you rerun
- Open the request waterfall to read span timing, errors, and the slowest path
- See the entry point, services involved, span count, and total duration for a trace in one place
Move from a trace to request logs without losing context
When a slow request or error span needs more evidence, open the request logs already scoped to that trace. Filter by service, severity, or text and confirm the failure mode without copying IDs across tools.
- Keep log evidence tied to the exact trace under investigation
- Use service and severity filters to isolate noisy request streams quickly
- Validate what happened with structured log metadata next to span and trace identifiers
Use KloudMate Assistant to shorten the path to the right trace
KloudMate Assistant works across metrics, logs, traces, profiles, and connected data sources. In APM workflows, it can help teams summarize a regression, surface likely bottlenecks, and point engineers toward the next useful trace or log search.
- Summarize Explain a service-level regression before engineers read every chart
- Highlight Call out the spans or dependencies most likely contributing to latency
- Correlate Connect traces, logs, and related telemetry with less manual query work
Related Features
APM works best when traces, logs, alerts, and incident workflows stay connected.
Log Management
Search and analyze logs with the same service, span, and request context used in APM investigations.
Learn moreDatabase Monitoring
Correlate slow queries and database latency with application traces and downstream service impact.
Learn moreIncident Management
Turn trace evidence, service health, and alert context into one coordinated incident workflow.
Learn moreAlerting
Trigger alerts from latency or error symptoms and route responders into the right service or trace context.
Learn moreGet started
From telemetry to root cause,
in one platform.
Connect your OpenTelemetry pipeline, AWS integrations, or eBPF agent. Distributed tracing, log management, alerting, and AI-assisted investigation: unified, with predictable pricing.