Every signal your
system whispers,
captured.
AstraLog transforms raw operational signals into structured knowledge. From user clicks to infrastructure events — observe, analyze, and understand your systems in real time.
4.2k
Events / sec
<1ms
Ingest latency
99.98%
Uptime SLA
4,219
Events/s
0.8ms
P99 lat
0
Errors
Ingestion rate · 60s window
14:22:31
page_view
/dashboard · session:a8f2c · 340ms
12ms
14:22:31
api_request
GET /events · 200 OK · 142 results
8ms
14:22:32
memory
heap_used: 68% · gc_pause: 2ms
—
14:22:33
api_request
POST /ingest · 202 Accepted
4ms
Trusted by engineering teams at
Stripe
Vercel
Linear
Supabase
Grafana Labs
Planetscale
Core capabilities
Built for the signal,
not the noise
Every component of AstraLog is designed to extract meaning from operational data — from the first event captured to the last insight surfaced.
01
Recursive Self-Observability
AstraLog monitors its own infrastructure in real time — ingestion latency, queue depths, write times, memory utilization. The platform observes itself as rigorously as it observes your application.
02
High-Resolution Temporal Tracking
Nanosecond-precision timestamps on every event. Detect micro-latency spikes, performance regressions, and bottlenecks with granularity that conventional logging simply cannot offer.
03
Structured Event Model
Every signal is a typed, queryable record — not a log line. Event types, source identifiers, session metadata, and contextual attributes are first-class fields, not text to parse.
04
Distributed Event Tracing
Correlate events across services, sessions, and requests using trace IDs. Reconstruct the complete lifecycle of any user interaction or system transaction across your entire architecture.
05
Intelligent Anomaly Detection
Machine learning models trained on your event streams surface unusual patterns before they escalate. Adaptive alerting adjusts thresholds dynamically based on observed system behavior.
06
Adaptive Instrumentation
Logging intensity changes automatically with system conditions. Normal operation records essential signals. Detected anomalies trigger deep-capture mode for maximum diagnostic resolution.
Architecture
From signal to insight,
in milliseconds
01
Instrumentation Layer
Lightweight SDKs and APIs emit structured events directly from your application code with minimal overhead. Every event is typed, validated, and enriched with contextual metadata at the source.
02
Ingestion Pipeline
A high-throughput message queue decouples producers from consumers, providing resilience during traffic spikes. Schema validation and timestamp normalization happen before events touch storage.
03
Time-Series Storage
Events land in databases optimized for temporal queries — indexed by time range, event type, source, and custom metadata. Query any slice of your system's history at any granularity.
04
Analytics & Visualization
Interactive dashboards, statistical analyses, and ML-powered anomaly detection transform event streams into operational intelligence. Surface trends, investigate outliers, understand your system.
Event payload · ingestion schema
{
"id": "evt_9kXa2mPq7R",
"type": "api_request",
"timestamp": 1748387543829,
"source": "api-gateway-prod-3",
"latency_ms": 8.4,
"status": 200,
"trace_id": "tr_mK8bXqP"
}
"id": "evt_9kXa2mPq7R",
"type": "api_request",
"timestamp": 1748387543829,
"source": "api-gateway-prod-3",
"latency_ms": 8.4,
"status": 200,
"trace_id": "tr_mK8bXqP"
}
Validation pipeline
✓ schema
Event shape validated against registry
✓ enriched
Region, service version, env injected
✓ indexed
Written to time-series store · 0.9ms
⚑ p99
Latency above baseline · anomaly flagged
Recursive observability
The platform that
watches itself
AstraLog is its own most demanding customer. Every internal component — the ingestion pipeline, the storage layer, the analytics engine — emits structured events back into the system. Transparent by design.
Ingestion latency
Queue depth
DB write times
Memory utilization
Component health
GC pause duration
Platform internals · live
ingest_queue_depth
142
heap_utilization
68%
db_write_latency
0.9ms
pipeline_throughput
4.2k/s
gc_pause_avg
2.1ms
anomaly_detector
0.03
All systems operational
·
Last updated 0.8s ago
Applications
One platform,
every signal
AstraLog adapts to the complexity of your system — whether you are debugging a single service or orchestrating a distributed architecture across regions.
Web Application Monitoring
Track user navigation, interaction patterns, session behavior, and rendering performance. Understand exactly how users experience your interface with quantitative precision.
Distributed Systems Tracing
Follow a single request as it propagates across microservices, queues, and databases. Reconstruct complete transaction lifecycles and pinpoint failure origins with trace correlation.
Performance Engineering
Measure request latency, database query times, and service reliability with sub-millisecond granularity. Identify regressions before your users notice them.
Research & Education
AstraLog's architecture intentionally exposes concepts from operating systems, computer architecture, and AI. A living laboratory for studying complex systems under real workloads.
Your system has stories
it hasn't told you yet.
Start capturing every signal. Understand every event. Build systems that explain themselves.