🚀 pgHawk v2.0 — Deploy + monitor + optimize. Your AI-powered PostgreSQL platform. See the agent → See plans →
PostgreSQL deployment & AI agent — production-proven

PostgreSQL clusters.
Deployed in 25 minutes.

Stop spending 3 days on manual cluster setup. pgHawk deploys production-ready clusters in 25 minutes, then keeps them healthy with a 24/7 AI agent — across any cloud or bare metal.

Start free trial See how it works
pgHawk — cluster deploy
pghawk deploy --cluster prod-eu --cloud aws --region eu-west-1 --nodes 3 --ha
pgHawk v2.0 · PostgreSQL Automation Platform · Datacomware © 2026
→ [1/8] Validating cluster configuration...
✓ Config valid: 3-node HA · PostgreSQL 16 · Patroni 3.3
→ [2/8] Provisioning EC2 instances (eu-west-1a / b / c)...
✓ 3 × t3.xlarge nodes online · Private VPC configured
→ [3/8] Installing PostgreSQL 16 + Patroni + etcd...
→ [4/8] Configuring HA replication · Leader election...
✓ Primary elected · 2 synchronous standbys · lag: 0ms
→ [5/8] Setting up pgBouncer connection pooling...
→ [6/8] Applying hardware-tuned postgresql.conf...
→ [7/8] Configuring automated backups → S3...
→ [8/8] Running cluster health checks...
✓ Cluster "prod-eu" is LIVE · 23 min 41 sec · 3/3 nodes healthy

Production-ready cluster

in 25 minutes, not 3 days

Your infrastructure

AWS, GCP, Azure, Hetzner or bare metal

No vendor lock-in

5–20× cheaper than managed databases

🗄️
⚙️
📋
🔧
📜
🗄️
⚠️
🔥
Inconsistent setup across environments
3+ days of manual configuration per cluster
Architecture knowledge locked in one engineer
The Problem

PostgreSQL is not the problem.
Everything around it is.

Companies are not afraid of PostgreSQL. They're afraid of the consequences: downtime, performance degradation, and months of DevOps time spent on repetitive cluster setup that varies every time.

Every cloud has different conventions. Every engineer has different habits. Without a system behind it, your PostgreSQL infrastructure is as unpredictable as the people who built it.

Infrastructure without a system becomes a liability.

See pgHawk in action

From chaos to controlled system

Three capabilities. One platform. Zero manual steps.

How a cluster is deployed — automated, repeatable, cloud-agnostic

pgHawk — cluster:deploy · GCP / europe-west4
pghawk cluster deploy --name analytics-db --cloud gcp --ha --nodes 3 --version 16
Platform: Google Cloud · Region: europe-west4 · Nodes: 3
→ Generating deployment plan...
✓ Plan: primary + 2 synchronous standbys
→ Provisioning n2-standard-4 instances in separate AZs...
✓ 3 instances online · Private VPC · Firewall rules applied
→ Installing PostgreSQL 16 + Patroni + etcd cluster...
✓ Packages pinned · Services configured
→ Configuring streaming replication + automatic failover...
✓ Leader elected · Replication lag: 0ms · DCS healthy
→ Applying hardware-tuned postgresql.conf profile...
→ Enabling pgBouncer connection pooling · Configuring SSL...
→ Configuring automated backups → GCS bucket...
✓ Cluster "analytics-db" READY · 22 min 17 sec · All checks passed

How architecture is standardized — proven, documented, reproducible

Application your service pgBouncer Connection Pooling · SSL PRIMARY PostgreSQL 16 · Patroni 3.3 10.0.1.10 · Leader · R/W Streaming Streaming STANDBY-1 Sync replica · lag: 0ms 10.0.1.11 · Follower STANDBY-2 Sync replica · lag: 0ms 10.0.1.12 · Follower etcd · DCS (distributed consensus) Automatic failover via Patroni — RTO < 30s S3 / GCS / ABS Automated backups

How control is established — real-time cluster health at a glance

pgHawk Control Panel · cluster: prod-eu · 3/3 nodes healthy · uptime: 99.98%
Replication Lag
0ms
Active Connections
142
CPU (primary)
23%
What is pgHawk

Not just a tool.
A system for PostgreSQL.

  • Defines a clear, repeatable cluster architecture
  • Deploys multi-node HA clusters automatically — any cloud
  • Standardizes configuration and performance tuning
  • Eliminates manual operations and configuration drift
  • Built on 7+ years of production PostgreSQL experience

Manual management does not scale. PostgreSQL needs a system behind it — not a runbook, not a hero engineer. pgHawk is that system, encoded from real production workloads.

HA AWS GCP AUTO
What you gain

PostgreSQL stops being a risk.
It becomes a controlled system.

25m
Production-ready cluster from zero
vs. 3 days manually
HA
High-availability, always
Primary + standbys + auto-failover
Cheaper than managed cloud databases
Your infra, no vendor markup
0
Manual operations for daily ops
Fully automated lifecycle
How it works

Three steps to a production cluster

01

Configure

Define your cluster spec: cloud provider, region, node count, PostgreSQL version, and replication mode. pgHawk validates and generates the full deployment plan.

02

Deploy

pgHawk provisions infrastructure, installs PostgreSQL and Patroni, configures HA replication, tunes performance settings, and sets up backups — fully automated, no shell access needed.

03

Operate

Your cluster is live and self-managing. pgHawk handles failover, configuration drift, and scaling. You operate through a unified control layer — direct server access is rarely required.

Capability
Managed (RDS / Cloud SQL)
DIY / Manual
pgHawk
Deployment speed
⚡ Fast
🐢 3+ days
⚡ 25 minutes
Infrastructure cost
💸 High premium
⚠ Variable
✓ 5–20× lower
Vendor lock-in
✗ Yes
✓ None
✓ None
HA + auto-failover
✓ Yes
✗ Manual
✓ Yes
Multi-cloud support
✗ No
⚠ Complex
✓ Yes
Performance tuning
⚠ Limited
⚠ Manual
✓ Automated
Full infrastructure access
✗ Restricted
✓ Full
✓ Full
What you actually get

You're not getting a tool.
You're getting certainty.

  • PostgreSQL is no longer a failure point

    Proven HA architecture with automatic failover. Your database keeps running — even when individual nodes don't.

  • Predictable system behavior

    Every cluster is built the same way, every time. No more "it worked on staging" incidents or configuration drift.

  • Issues don't turn into incidents

    Automated health checks, failover, and backup validation catch problems before they reach production.

  • 7+ years of DBA expertise, encoded

    Production knowledge baked into every deployment. You don't need a senior DBA on call around the clock.

Start your free trial →
pgHawk · All clusters healthy
prod-eu
AWS · eu-west-1 · 3 nodes
● HEALTHY
analytics-db
GCP · europe-west4 · 3 nodes
● HEALTHY
staging
Hetzner · fsn1 · 2 nodes
● HEALTHY
8
Clusters
100%
Uptime
0
Incidents
Deployment targets

Your cloud. Your choice.

Deploy across any major cloud provider or your own hardware. pgHawk normalizes the complexity — you get the same production cluster, anywhere.

AWS
Google Cloud
Azure
DigitalOcean
Hetzner
Bare Metal
AI-Powered Agent

Your always-on
PostgreSQL expert

pgHawk doesn't just deploy your clusters — it watches over them. An AI reasoning engine with access to your metrics, logs, active queries, and configuration. It diagnoses issues, recommends fixes, and follows structured runbooks — 24/7, without waiting for a ticket.

pgHawk Agent · prod-eu · 3/3 nodes · monitoring
Query latency on analytics-db spiked since 14:30 UTC. What happened?
PH

Root cause identified. Sequential scan on events table (avg 872ms, was 12ms before 14:22 UTC).

↑ 73× Table grew from 2.1M → 18.7M rows during migration at 14:22 UTC. Existing index idx_events_user_id is no longer selective.
FIX Create composite index: idx_events_user_ts ON events(user_id, created_at DESC) — estimated 98% improvement. Use CONCURRENTLY to avoid lock.
+3 Also found degraded plans on orders and sessions tables — details in full report.
Can you run ANALYZE on that table?
PH

ANALYZE modifies planner statistics — I never run write or potentially disruptive commands. Here's the command for you to execute:

ANALYZE VERBOSE events;

Once you run it, I'll monitor the query plan shift and confirm the improvement. Alert threshold is set to 50ms — I'll notify you if the fix doesn't hold.

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Continuous Monitoring

Tracks metrics, logs, active queries, lock chains, autovacuum activity, and configuration drift — across every node, every minute.

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Autonomous Diagnosis

Detects slow queries, deadlocks, CPU spikes, memory pressure, index bloat, connection saturation, and replication lag automatically.

Query & Schema Optimization

Reads execution plans, identifies missing indexes, finds redundant statistics, and recommends schema changes — with estimated impact.

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Structured Runbooks

Follows pre-defined playbooks for every common DBA scenario — slow query investigation, CPU spikes, connection storms, tuning, replication issues.

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Read-Only by Design

The agent uses safe, pre-approved SQL commands only. It never executes write, DDL, or potentially disruptive statements without explicit approval.

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Cloud & Tool Integrations

Connects to AWS CloudWatch, GCP Monitoring, Prometheus. Sends alerts to Slack or PagerDuty. Supports AWS RDS, Aurora, Cloud SQL, and self-hosted.

Built-in runbooks
SLOW_QUERIES GENERAL_MONITORING PERFORMANCE_TUNING HIGH_CPU_INVESTIGATION CONNECTION_STORM LOW_MEMORY REPLICATION_LAG AUTOVACUUM_ANALYSIS LOCK_INVESTIGATION INDEX_ADVISOR