alertsift 0.1.0

Turn an alert storm into the few incidents that actually matter — dedupe, correlate, rank, and (optionally) AI-explain alerts from any source, with Slack digests.

alertsift

Turn an alert storm into the few incidents that actually matter — dedupe, correlate, rank, and (optionally) AI-explain alerts from any source, then push a clean digest to Slack.

It's 2 a.m., you're on-call, and 214 alerts are firing. Your real question isn't "what fired?" — it's "what's actually broken, and where do I start?" Studies show 40–60% of alerts never even get investigated because the signal drowns in noise.

alertsift does that triage for you, in one command:

🔔 214 alert(s) → 3 incident(s)  (deduped to 60, suppressed 22)

  ● checkout-svc (critical, 47 alerts) ← start here
     types: HighLatency, High5xxRate, PodRestart
     checkout-svc is crash-looping and timing out payment calls.
     likely cause: a bad deploy or failing dependency in checkout-svc.

  ● node-7 (medium, 1 alerts)
     types: DiskUsage

Source-agnostic by design. It normalizes alerts from Prometheus/Alertmanager, generic JSON, or plain logs into one shape, then dedupes, groups related alerts into incidents, ranks them, and (optionally) has an LLM explain the likely root cause. Adding a new platform (Datadog, CloudWatch, PagerDuty…) is just one new parser.

Why alertsift

	Raw alert channel	alertsift
Collapses duplicate alerts	❌	✅
Groups related alerts into incidents	❌	✅
Ranks "what to look at first"	❌	✅
Suppresses known noise	❌	✅ .alertsiftignore
Plain-English likely cause	❌	✅ (optional LLM)
Works with no API key	—	✅ --no-ai / mock / local Ollama
Posts a clean digest to Slack	❌	✅

Install

git clone https://github.com/jay-tank/alertsift.git
cd alertsift
pip install .
# optional LLM providers:
pip install '.[claude]'   # or '.[openai]'

Usage

# Triage a file (auto-detects Alertmanager / JSON / logs)
alertsift alerts.json

# From a pipe — e.g. Alertmanager, kubectl, a log tail
amtool alert -o json | alertsift --stdin

# Pure/offline — no LLM, no key (dedupe + correlate + rank only)
alertsift alerts.json --no-ai

# Post a digest to Slack (webhook from env; preview first with --dry-run)
export ALERTSIFT_SLACK_WEBHOOK="https://hooks.slack.com/services/..."
alertsift alerts.json --slack --dry-run     # preview the payload
alertsift alerts.json --slack               # actually post

# Machine-readable
alertsift alerts.json --json

Exit codes: 0 = nothing actionable, 1 = actionable incident(s) found, 2 = usage/parse error — so it slots into cron or CI (only pages you when it matters).

How it works

INPUT ──► parse (pluggable) ──► normalize ──► dedupe ──► suppress ──►
correlate ──► rank ──► [AI enrich] ──► render / --json / Slack

Steps up to rank are pure and fully offline; the LLM only writes the plain-English explanation (and is skippable with --no-ai). See docs/USAGE.md and docs/PROVIDERS.md.

Safety

• Secrets never leave your machine. Alert summaries are run through best-effort redaction before being sent to an LLM or posted to Slack.
• Read-only. alertsift never mutates your systems; it reads alerts and reports.
• Slack webhook comes from the environment ($ALERTSIFT_SLACK_WEBHOOK), never a flag literal, never logged.

Supported sources

Prometheus/Alertmanager, generic JSON, and plain logs today. The core is source-agnostic — Datadog, CloudWatch, and PagerDuty are drop-in parsers on the roadmap.

Limitations

• Correlation in v1 is heuristic (groups by service/namespace) — solid and explainable, but not a full dependency-graph. Treat "likely cause" as an assist to your judgment, not gospel.
• Log parsing is best-effort.

License

MIT — see LICENSE.