Autonomous Site Reliability

Resolve incidents before
they escalate.

Seren connects to your telemetry, analyzes distributed traces, and delivers actionable root cause analysis with confidence scores in seconds. Calm the chaos.

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STEP 01 — INGEST

Connect your telemetry stack.

Seren attaches to your existing observability pipeline — OpenTelemetry collectors, Prometheus exporters, Datadog agents, or raw Kafka topics. No re-instrumentation required. Data is streamed in real time over gRPC with back-pressure handling.

yaml
# seren.yaml
sources:
  - type: opentelemetry
    endpoint: otel-collector:4317
  - type: prometheus
    scrape_interval: 15s
    targets: ["*:9090"]

Seren attaches to your existing observability pipeline — OpenTelemetry collectors, Prometheus exporters, Datadog agents, or raw Kafka topics. No re-instrumentation required. Data is streamed in real time over gRPC with back-pressure handling. Seren attaches to your existing observability pipeline — OpenTelemetry collectors, Prometheus exporters, Datadog agents, or raw Kafka topics. No re-instrumentation required. Data is streamed in real time over gRPC with back-pressure handling. Seren attaches to your existing observability pipeline — OpenTelemetry collectors, Prometheus exporters, Datadog agents, or raw Kafka topics. No re-instrumentation required. Data is streamed in real time over gRPC with back-pressure handling.

01Telemetry Ingestion02Trace Analysis03Root Cause Engine04Action Planner05Autonomous Execution
SEV-1● ACTIVE INCIDENTT-MINUS

Database Latency Spike in us-east-1

⊡ db-cluster-primary↑ P99 > 2500msIMPACT: Checkout API
Live Telemetry FeedAUTO-SCROLL: ON
14:02:11↑PagerDuty alert triggered for service checkout-api.PD-WEBHOOK
14:02:15⚠Datadog monitor "High API Latency" transitioned to ALERT. Value: 2640ms.DATADOG
14:03:01⚡CPU utilization on db-cluster-primary-node-1 exceeded 95% threshold.AWS-CLOUDWATCH
14:04:12⛓Connection pool exhaustion reported by 4 instances in checkout-api deployment.KUBERNETES
14:05:33⊡Slow query log rate increased by 4000%. Active queries > 60s detected.POSTGRES
14:06:45$Auto-scaling group provisioning 3 new replicas for checkout-api.AWS-ASG
Related Recent IncidentsView All
IDSEVTITLEAGE
INC-089SEV-2DB IOPS limit reached during ETL2d ago
INC-074SEV-2Checkout API timeout due to slow downstream5d ago
INC-042SEV-1Primary DB failover caused split brain14d ago
INC-018SEV-3Reporting worker consuming excessive memory21d ago
⊙ AI Root Cause Verdict
94%
Confidence Score

A rogue analytics cron job (worker-analytics-04) initiated a massive unoptimized table scan on the transactions table — missing a composite index on status, created_at. This caused CPU to spike to 99% and exhausted the connection pool for the checkout-api.

≫ Autonomous Reasoning Trace
SYNTHESIZING
✓

Analyze initial alert parameters

Action:Querying Datadog Metrics API14:02:22
Result:checkout-api P99 latency > 2500ms. Error rate normal. Dependency 'db-cluster-primary' shows response times > 10s. Focus shifted to database layer.
✓

Inspect Database Telemetry

Action:Fetch Postgres system views14:03:15
Result:CPU utilization at 99.2%. pg_stat_activity shows 450 active connections (limit 500). 90% stuck in 'active' state executing long-running SELECT.
✓

Identify Offending Queries & Source

Action:Analyze pg_stat_activity long queries14:04:40
Result:Top query: full sequential scan on transactions (42M rows). Traced to cron job worker-analytics-04. No index on (status, created_at).
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Generating remediation plan...

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Awaiting approval to execute