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Changelog

Latest updates and improvements

Groundcover Integration

eBPF-based Kubernetes observability with automated cluster monitoring and incident investigation

We’ve integrated Groundcover, an eBPF-based Kubernetes observability platform, enabling automated cluster monitoring and incident investigation.

What’s new

  • List clusters and namespaces - Query your Kubernetes infrastructure
  • Query workloads with metrics - Analyze resource usage and performance
  • Automatic error analysis - When alerts fire, agents automatically investigate common issues like resource exhaustion and configuration errors

No more switching between multiple dashboards to diagnose Kubernetes problems.

Learn more about Groundcover integration →

Render Webhook Triggers

Automated workflow responses to Render deployment and service events

Render webhooks can now trigger Cased workflows automatically.

What’s new

  • Deployment event triggers - Automatically investigate deployment failures
  • Service event monitoring - Respond to outages and scaling events
  • Enhanced metrics querying - Query CPU, memory, HTTP latency, and database health

Connect your Render account and let agents handle deployment issues automatically.

Learn more about Render integration →

Honeycomb Integration

Query traces, metrics, and deployment data from Honeycomb during incident investigation

We’ve integrated Honeycomb observability data into Cased, enabling agents to analyze incidents with full trace and metric context.

What’s new

  • Natural language queries - Ask about error rates, latency, and system performance
  • Deployment correlation - Automatically correlate issues with recent deployments
  • Alert visibility - See configured alerts and notification channels to identify monitoring gaps

Learn more about Honeycomb integration →

CloudWatch Alarms Configuration

Configure CloudWatch alarms through natural language without opening the AWS console

Configure AWS CloudWatch alarms through Cased without navigating the AWS console.

What’s new

  • Natural language alarm creation - Describe what you want to monitor
  • Automatic metric selection - Agent finds the right metrics and thresholds
  • SNS integration - Set up notifications to Slack, email, or PagerDuty

Skip the AWS console clicks and let the agent handle alarm configuration.

PagerDuty Incident Triggers

Trigger workflows automatically from PagerDuty incidents

PagerDuty incidents can now trigger Cased workflows automatically.

What’s new

  • Zero config setup - Automatic webhook subscription creation
  • Multiple trigger types - Incident creation, acknowledgment, and resolution
  • Automated response - Run diagnostics, execute remediation, create post-mortems

Connect PagerDuty and let agents start investigating before you even look at the alert.

Learn more about PagerDuty integration →

PostHog Analytics Integration

Query product analytics and user behavior data from PostHog

We’ve integrated PostHog product analytics, giving agents access to user behavior and feature usage data.

What’s new

  • Query user behavior - Understand how users interact with features
  • Analyze feature adoption - Track rollout success and usage patterns
  • Correlate with infrastructure - Connect product metrics to system performance

Learn more about PostHog integration →

Render Integration

Monitor and manage Render deployments through AI agents

We’ve launched a Render integration for teams deploying on Render’s cloud platform.

What’s new

  • Automatic deployment tracking - Monitor builds and service health
  • Natural language queries - Ask about your infrastructure in plain English
  • Automatic issue detection - Watch for deployment failures and performance problems
  • Suggested responses - Get recommendations for rollbacks or scaling adjustments

Learn more about Render integration →

ArgoCD Integration

Monitor Kubernetes deployments with ArgoCD sync status and health tracking

We’ve integrated ArgoCD for teams using GitOps-based Kubernetes deployments.

What’s new

  • Automatic deployment tracking - Sync status changes, application health, resource metadata
  • Slack/email notifications - Get notified of deployment changes
  • AI-powered issue response - Agents investigate sync failures and health issues
  • Complete audit trail - Full history of all deployment events

Learn more about ArgoCD integration →

CloudFormation Support

Infrastructure management for AWS CloudFormation stacks

Cased now supports AWS CloudFormation alongside Terraform and Pulumi.

What’s new

  • Automated stack scanning - Detect configuration drift in your stacks
  • Drift remediation - Generate fixes through pull requests
  • Unified monitoring - Single view across Terraform, Pulumi, and CloudFormation

Teams using AWS’s native IaC tool can now get the same automated management as Terraform users.

Deploy Monitoring in Slack

Real-time deployment updates and monitoring directly in Slack

Deploy monitoring now posts updates directly to your Slack channels.

What’s new

  • Real-time updates - See deployment progress as it happens
  • Error alerts - Get notified of failures with Sentry links
  • Post-deploy monitoring - 30-minute health check after deployment completes
  • Rollback suggestions - Automatic recommendations when issues are detected

Keep your team informed without leaving Slack.

Custom Workflows

Create your own automated workflows tailored to your infrastructure needs

You can now create custom workflows tailored to your organization’s specific needs.

What’s new

  • Custom prompts - Write instructions for exactly what you want automated
  • Flexible triggers - Schedule, webhook, or API triggers
  • Integration access - Use any connected integration in your workflows
  • Parameter templates - Make workflows reusable across environments

Start with our default workflows or build your own from scratch.

Learn more about custom workflows →

Pulumi Support

Infrastructure management for Pulumi stacks with drift detection and code generation

Cased now supports Pulumi alongside Terraform for infrastructure-as-code management.

What’s new

  • Drift detection - Scan Pulumi stacks for configuration drift
  • Automatic fixes - Generate pull requests with remediation
  • Code generation - Write new Pulumi code in TypeScript, Python, or Go
  • Resource management - Query and manage Pulumi resources

One agent for all your IaC needs, regardless of which tool you use.

Agent API

Programmatic access to Cased agents for custom integrations and automation

We’ve launched the Cased Agent API for programmatic access to agents.

What’s new

  • Start sessions - Create agent sessions via API
  • Trigger workflows - Run workflows programmatically
  • Query status - Check session and workflow run status
  • Integrate anywhere - Build Cased into your existing tools and scripts

View API documentation →

Infrastructure Cost Analysis Workflow

Automated AWS cost analysis that identifies optimization opportunities and tracks spending patterns

The Infrastructure Cost Analysis workflow monitors your AWS spending and identifies cost optimization opportunities with specific dollar savings potential.

This workflow examines actual cloud usage to find oversized instances, unused resources, inefficient storage, and opportunities for Reserved Instances. Each finding includes current monthly costs, potential savings, implementation steps, and risk assessment.

Configure daily analysis for active cost management or weekly for standard monitoring. Results can be delivered to Slack channels or viewed in your dashboard.

Key findings:

  • Right-sizing: Identifies oversized EC2 instances and over-provisioned databases
  • Waste elimination: Finds idle resources, orphaned volumes, and redundant snapshots
  • Storage optimization: Recommends lifecycle policies and storage class changes
  • Reserved capacity: Highlights opportunities for Reserved Instances and Savings Plans

Learn more about the workflow →

Introducing Workflows

Automated AI workflows that continuously monitor your infrastructure and codebase for issues

We’re excited to introduce Workflows - automated AI processes that provide 24/7 monitoring and analysis for your infrastructure operations.

Workflows run on schedules you define (daily, weekly, monthly) or trigger automatically from external events like Sentry errors or deployments. Each workflow uses AI to analyze your systems, identify issues, and can start other workflows to fix problems.

Launch workflows

  • SOC2 Compliance: Automated compliance scanning 🛡️
  • Infrastructure Cost Analysis: Cost optimization opportunities 💰
  • Terraform Security Analysis: Security vulnerability detection 🔒
  • Terraform Best Practices: Code quality and maintainability 📋
  • Sentry Error Analyzer: Automatic error resolution 🚨
  • Deploy Monitor: Deployment health tracking 🚀

Configure workflows in your dashboard to run autonomously while you focus on building.

Learn more about workflows →

Sentry Error Analyzer Workflow

Automatically analyze Sentry errors and start resolution sessions with AI-powered root cause analysis

The Sentry Error Analyzer workflow automatically analyzes new Sentry issues and works to solve problems in separate sessions.

When Sentry webhooks notify of new errors, this workflow immediately examines the error message, stack trace, and relevant code to identify root causes and create actionable resolution steps. It handles runtime errors, import failures, configuration issues, database problems, and API integration failures.

Key features:

  • Automatic triggering: No setup required beyond Sentry integration
  • Repository mapping: Links errors to correct codebases intelligently
  • Priority assessment: Assigns critical/high/medium/low based on impact
  • Action items: Specific steps for developers to resolve issues

Install the public “cased” Sentry integration to enable automatic error analysis.

Learn more about the workflow →

Terraform Best Practices Workflow

Automated Terraform code quality analysis for maintainability, module design, and best practices

The Terraform Best Practices workflow reviews your infrastructure-as-code for quality, maintainability, and adherence to Terraform best practices.

This workflow analyzes code organization, naming conventions, module design, documentation quality, and version management. It identifies opportunities to improve code reusability, consistency, and long-term maintainability of your infrastructure definitions.

Schedule weekly reviews for standard development or configure custom directories for targeted analysis. Integrate with GitHub to automatically review pull requests.

Key areas analyzed:

  • Code organization: Module structure and file organization improvements
  • Naming conventions: Consistent resource naming and tagging strategies
  • Documentation: Missing variable descriptions and module documentation
  • Version management: Provider constraints and module versioning best practices

Learn more about the workflow →

Terraform Cost Optimization Workflow

Automated analysis of Terraform code for cost optimization opportunities and financial efficiency

The Terraform Cost Optimization workflow analyzes your infrastructure-as-code to identify cost optimization opportunities before resources are deployed.

This workflow examines Terraform configurations for oversized resources, expensive storage configurations, inefficient networking setups, and missed opportunities for Reserved Instances or Savings Plans. It provides cost estimates and specific recommendations to reduce spending.

Configure weekly analysis to catch cost issues during development or run on-demand before major deployments. Target specific directories containing your most expensive infrastructure.

Key optimizations identified:

  • Resource sizing: Oversized EC2 instances, RDS databases, and storage allocations
  • Storage efficiency: Expensive storage classes and redundant backup configurations
  • Network costs: Data transfer optimization and NAT Gateway efficiency
  • Reserved capacity: Opportunities to use Reserved Instances and Savings Plans

Learn more about the workflow →

Terraform Operational Excellence Workflow

Automated analysis of Terraform code for monitoring, disaster recovery, and operational reliability

The Terraform Operational Excellence workflow analyzes your infrastructure-as-code for operational reliability, monitoring coverage, and disaster recovery preparedness.

This workflow examines Terraform configurations to ensure proper CloudWatch alarms, backup strategies, multi-AZ deployments, and monitoring setups. It identifies gaps in operational readiness and provides specific recommendations for improved reliability.

Schedule weekly analysis to maintain operational standards or run before major infrastructure changes. Configure specific directories to focus on critical production systems.

Key areas analyzed:

  • Monitoring setup: Missing CloudWatch alarms and logging configurations
  • High availability: Single-AZ deployments and missing failover mechanisms
  • Backup strategies: Inadequate backup configurations and retention policies
  • Disaster recovery: Missing cross-region replication and recovery procedures

Learn more about the workflow →

Terraform Security Analysis Workflow

Automated security analysis of Terraform code for vulnerabilities, authentication issues, and data protection

The Terraform Security Analysis workflow scans your infrastructure-as-code for security vulnerabilities before they reach production.

This workflow examines Terraform configurations to identify overly permissive IAM policies, unencrypted resources, public exposures, weak authentication, and network security gaps. It provides exact file locations, risk assessments, and specific remediation code for each finding.

Schedule it daily for active development or weekly for standard security reviews. Configure specific directories to analyze and integrate with GitHub for automatic scanning.

Key capabilities:

  • Access control analysis: Identifies overprivileged resources and policies
  • Encryption gaps: Finds unencrypted storage and data transfer vulnerabilities
  • Network security: Detects VPC misconfigurations and firewall gaps
  • Compliance mapping: Links findings to SOC2 and ISO27001 requirements

Learn more about the workflow →

SOC2 Compliance Workflow

Automated SOC2 compliance analysis workflow that scans Terraform code and AWS resources for violations

The SOC2 Compliance workflow automatically scans your infrastructure to identify SOC2 compliance violations in both your Terraform code and live AWS resources.

This workflow analyzes your infrastructure for common compliance issues including:

  • Encryption gaps: Unencrypted S3 buckets, EBS volumes, and RDS instances
  • Excessive permissions: Overly broad IAM policies and public access configurations
  • Missing logging: Lack of CloudTrail, VPC Flow Logs, or application logging
  • Backup failures: Missing backup configurations for critical data
  • Public access: Resources exposed to the internet without proper controls
  • Configuration drift: Differences between Terraform definitions and actual AWS state

The workflow examines Terraform files in your repositories using GitHub integration, then validates actual AWS resource configurations through your connected AWS accounts. It identifies specific violations with exact file paths, line numbers, and AWS resource ARNs.

Each finding includes:

  • SOC2 control mapping (CC6, CC7, CC8, CC9)
  • Severity level (critical, high, medium, low)
  • Remediation steps with corrected Terraform code
  • Audit-ready documentation for compliance reviews

Configure the workflow to run weekly, daily, or on infrastructure changes. Results can be delivered to designated Slack channels with customizable severity thresholds.

Infrastructure Graph Visualization

Visualize your AWS infrastructure with interactive dependency graphs

Understanding complex infrastructure relationships is easier with our new infrastructure graph visualization.

What’s New

Interactive Infrastructure Graphs

  • Visual Topology: See your entire AWS infrastructure as an interactive graph
  • Resource Relationships: Understand dependencies between resources at a glance
  • Zoom & Pan: Navigate large infrastructure deployments with ease
  • Dark Mode Support: Graphs adapt to your theme preference

Smart Filtering

  • Filter by resource type (EC2, RDS, Lambda, etc.)
  • Show/hide specific relationships
  • Focus on particular availability zones or regions

Real-time Updates

  • Graphs update automatically as infrastructure changes
  • See deployment impacts visually
  • Track drift between desired and actual state

Integration with Agents

  • Ask agents to explain specific parts of your infrastructure
  • Get recommendations based on graph analysis
  • Identify potential issues through visual inspection

Use Cases

  • Architecture Reviews: Quickly understand system design
  • Troubleshooting: Trace dependencies when debugging issues
  • Cost Analysis: Identify resource clusters and optimization opportunities
  • Security Audits: Visualize network boundaries and access patterns

Dynamic Data Visualization

Agents can now create custom, interactive data visualizations to better communicate insights

We’ve enhanced our agents with powerful data visualization capabilities. Agents can now generate custom, interactive charts and graphs on-the-fly to help you better understand your data.

What’s New

  • Custom Visualizations: Agents dynamically create React components with D3.js for tailored visualizations
  • Interactive Charts: Full interactivity including hover tooltips, zoom, and pan capabilities
  • Multiple Chart Types: Support for line charts, bar charts, scatter plots, and more
  • Real-time Rendering: Visualizations render instantly within agent responses
  • Data-Driven Insights: Agents choose the best visualization type based on your data

How It Works

When analyzing data, agents can now create visualizations that best represent the insights they discover.

This feature is automatically available in all agent sessions - just ask your agent to visualize any data.

Enhanced Agent List View

New table view for agents with advanced filtering, status indicators, and improved organization

We’ve redesigned the agent list view to make it easier to manage and track your AI agents.

Key Improvements

Organized Views

  • Inbox Tab: Active agents (Running, Paused, Failed)
  • Archived Tab: Completed and archived agent sessions
  • Smart Filtering: Filter by status to focus on what matters

Visual Status Indicators

  • 🟢 Running: Active agents with pulsing green indicator
  • 🟡 Paused: Agents waiting for input with yellow indicator
  • 🔴 Failed: Agents that encountered errors with red indicator
  • ⚪ Archived: Completed sessions with gray indicator

Enhanced Information Display

  • User Avatars: See who started each agent session
  • Workflow Badges: Easily identify workflow-triggered agents
  • Last Activity: Real-time updates showing when agents were last active
  • Quick Actions: Archive or manage agents directly from the list

Performance

  • Optimized for handling hundreds of agent sessions
  • Real-time updates without page refreshes
  • Smooth animations and transitions

Changelog Started

This is the start of the changelog.

Going forward, we’ll use this space to share:

  • New features - The latest capabilities and integrations we’ve added to Cased
  • Improvements - Enhancements to existing functionality based on your feedback
  • Bug fixes - Important fixes that improve stability and reliability
  • Performance updates - Optimizations that make Cased faster and more efficient

Check back regularly to stay up to date with everything new in Cased!