May is all about automation, AI-powered workflows, and deeper database observability. This month, we expanded OpsAI capabilities with automated investigations and AI-driven alert creation, while significantly enhancing PostgreSQL monitoring with new metrics, insights, and dedicated database analysis screens.

Here’s everything new this month 👇

🤖 OpsAI – Automated Investigations & Smarter Alerting

Auto Investigation

OpsAI can now automatically investigate issues without requiring manual intervention.

Users can enable Auto Investigation from:

  • Home screen
  • Settings → OpsAI Settings

Currently supported for:

  • Kubernetes issues
  • APM errors
  • RUM errors

Once enabled, OpsAI will automatically perform RCA and provide investigation results whenever an issue occurs.

Auto Investigation

Notification Controls

Users can configure:

  • Notification channels
  • Notification frequency

to receive updates whenever OpsAI automatically investigates an issue.

Notification Controls

Granular Scope Selection

You can now choose exactly where Auto Investigation should run:

  • Kubernetes clusters
  • APM services
  • RUM applications

This provides more control over which environments are monitored by OpsAI automation.

🚨 Create Alerts with OpsAI

Alert creation is now powered by AI.

Simply describe what you want to monitor, and OpsAI will generate the alert configuration automatically.

Examples:

  • “Create an alert when API latency exceeds 500ms”
  • “Alert me when PostgreSQL connections are unusually high”

Smart Alert Recommendations

OpsAI can also determine the right metrics and thresholds automatically.

Instead of specifying exact values, you can describe the use case and OpsAI will:

  • Analyze your metrics
  • Review logs and traces
  • Identify appropriate thresholds
  • Configure alerts automatically

This makes alert setup significantly faster, especially for new services and environments.

☁️ Azure Integration

Azure Container Apps Support

We added support for Azure Container Apps monitoring.

The integration now collects:

  • 31 performance metrics
  • Resource utilization metrics
  • Service-level operational metrics

This expands visibility into containerized workloads running on Azure.

🐘 Database Monitoring – Major Upgrade

We’ve significantly expanded PostgreSQL observability across all deployment models.

Supported Environments

PostgreSQL monitoring now supports:

  • Self-hosted Linux environments
  • Kubernetes deployments
  • AWS
  • Azure
  • Google Cloud Platform

New Performance Metrics

Added deeper visibility into database activity with metrics including:

  • Throughput
  • Execution duration
  • Commits
  • Rollbacks
  • Connections
  • Transaction time
  • Rows modified by operation type

Lock Monitoring

Track locks with detailed breakdowns by:

  • Relation
  • Lock type
  • Lock mode

This helps identify contention and query bottlenecks faster.

Replication Insights

Added replication monitoring including:

  • Write-Ahead Log (WAL) size
  • Replication-related metrics

Index Performance Monitoring

Gain visibility into index effectiveness through metrics such as:

  • Index block hits
  • Index block reads
  • Index scans
  • Row reads per table

Additional PostgreSQL Insights

Added monitoring for:

  • Blocks
  • Vacuum operations
  • Database functions

for deeper database performance analysis.

📊 New PostgreSQL Monitoring Screens

To complement the new metrics, we’ve introduced dedicated PostgreSQL analysis views.

Query Metrics

View queries in both:

  • Full query format
  • Normalized query format

Along with key metrics such as:

  • Execution count
  • Average duration
  • Wait events

Query Detail Panel

Drill into individual queries and view:

  • Related APM services
  • Traces
  • Performance metrics
  • Blocking activity

Blocking Queries

Identify and troubleshoot database contention.

View:

  • Blocked queries
  • Full query statements
  • Affected tables
  • Maximum block time
  • Total block duration
  • Occurrence count

You can also inspect blocking query samples and execution duration.

Query Samples

Analyze real query executions with:

  • Full SQL statements
  • Execution details
  • Duration graphs
  • Associated attributes
  • Related traces

Schema Explorer

Explore database structure directly from Middleware.

View:

  • All schemas
  • Host information
  • Columns
  • Indexes
  • Foreign keys

Along with:

  • Schema-level metrics
  • Variants
  • Related queries

https://youtu.be/YytqlggEcs8

⚡ Improvements

Azure Integration

  • Added Azure Container App metrics collection support.

Linux Auto Instrumentation

  • Added support for RPM-based Linux distributions.

This enables easier auto-instrumentation across a wider range of enterprise Linux environments.