Building an Incident Response Agent That Remembers with Hindsight

How I Built RecallOps: Connecting Incident Response with Hindsight Memory

Introduction

In software engineering, production incidents are unavoidable. Applications can fail, servers can become unavailable, databases can experience unexpected issues, and services can behave differently after deployment. However, one problem that engineering teams repeatedly face is not just fixing incidents but remembering how similar problems were solved in the past.

When an incident occurs, engineers often spend valuable time searching through old logs, messages, documentation, and previous troubleshooting records. Sometim
es, the same problem has already occurred, but its solution is difficult to find.

This is the problem I wanted to address with RecallOps, an incident response assistant that combines incident management with Hindsight agent memory to make previous engineering knowledge easier to retrieve and reuse.

What Is RecallOps?

RecallOps is designed to help engineering and DevOps teams investigate recurring production incidents more efficiently.

Instead of treating every incident as a completely new problem, RecallOps maintains a structured record of previous incidents, their root causes, resolutions, and related runbooks.

The main idea is simple: when an engineer encounters a problem, they should be able to search previous incidents and discover relevant solutions rather than starting troubleshooting from scratch.

RecallOps provides the following capabilities:

• Create and Track Incidents: Engineers can create incident records and maintain information about production issues.
• Record Root Causes: Each incident can contain information about what caused the problem.
• Store Resolutions: Engineers can document the steps used to resolve incidents.
• Mark Incidents as Resolved: Incident status can be updated after successful resolution.
• Dashboard Statistics: A dashboard provides an overview of incident-related statistics.
• Keyword-Based Search: Engineers can search previously recorded incidents using relevant keywords.
• Runbook Recommendations: The system can recommend relevant runbooks to support troubleshooting.

These features help organize incident knowledge in one place and make it easier for teams to refer to previous solutions.

Technology Stack

RecallOps uses a modern web development stack that separates the frontend, backend, and database responsibilities.

Frontend – React and Vite

React is used to develop the user interface, while Vite provides the frontend development environment. Together, they support a responsive interface for creating incidents, viewing dashboard statistics, and searching previous records.

Backend – Node.js and Express.js

Node.js provides the server-side runtime, and Express.js handles API requests between the frontend and database. The backend manages incident-related operations and database communication.

Database – MySQL

MySQL stores structured incident information, including incident details, root causes, resolutions, and status information.

Memory Integration – Hindsight Cloud

Hindsight provides the agent memory component. Its purpose is to help the system retain useful information from previous incidents and recall relevant information when similar problems occur.

Why Hindsight Memory Matters

One of the most interesting aspects of RecallOps is its integration with Hindsight.

Traditional incident management systems primarily store information for engineers to search manually. However, storing information and making that information useful during future incidents are two different challenges.

This is where agent memory becomes important.

Hindsight is designed to provide memory capabilities that allow AI agents to retain and recall information across interactions.

In RecallOps, this creates an opportunity to connect previous incident knowledge with future troubleshooting activities.

Consider an example.

An engineering team previously experienced a database connection failure. The team investigated the issue, identified its root cause, documented the resolution, and marked the incident as resolved.

A few weeks later, another engineer encounters a similar database connection problem.

Without a memory-based approach, the engineer may need to manually search old incident records and documentation.

With Hindsight integration, the intended workflow is to retain useful information from the previous incident and recall relevant information when a similar problem appears.

This can help engineers identify potentially related incidents and review their previous resolutions.

The key advantage is that the system can make historical engineering knowledge more accessible during future investigations.

Developers interested in understanding this technology can explore the "Hindsight GitHub repository" (https://github.com/vectorize-io/hindsight) and the "Hindsight documentation" (https://hindsight.vectorize.io/).

More information about the concept is also available through "Vectorize's explanation of agent memory" (https://vectorize.io/what-is-agent-memory).

System Architecture

RecallOps follows a three-layer application architecture with a separate memory integration.

1. Frontend Layer

The React application provides the interface through which engineers interact with the system. Users can create incidents, view existing records, check statistics, and search for previous incidents.

1. Backend Layer

The Express.js backend acts as the communication layer. It receives requests from the frontend, processes incident-related operations, and communicates with MySQL.

1. Database Layer

MySQL maintains the structured incident records. This allows incident information to remain organized and available for future reference.

1. Memory Layer

Hindsight Cloud provides the memory integration. It is intended to support retaining and recalling useful incident knowledge.

Together, these components form the foundation of RecallOps.

A Practical Incident Investigation Scenario

Imagine that an application suddenly starts experiencing repeated service failures.

An engineer opens RecallOps and creates a new incident record. The engineer adds the incident description, records the suspected root cause, and documents the resolution after investigating the issue.

Once the problem is fixed, the incident is marked as resolved.

Later, another engineer encounters a similar service failure.

Instead of relying entirely on personal experience, the engineer can search previous incidents using relevant keywords and review their recorded root causes and resolutions. Relevant runbooks can also help guide the investigation.

With working Hindsight Cloud access, the intended memory workflow can additionally retain and recall useful information from previous incidents.

This illustrates the central idea behind RecallOps: engineering knowledge should remain useful even after the original incident has been resolved.

Challenges and Important Considerations

Building an incident response assistant involves more than creating forms and storing records.

One important consideration is maintaining accurate incident information. Incorrect root causes or incomplete resolutions can make historical records less useful.

Another challenge is making previous incidents easy to discover. Keyword-based search provides a starting point, while memory-based retrieval introduces another way to access relevant historical knowledge.

The Hindsight Cloud integration also introduces an important dependency. Although the integration is configured in the project, live retain and recall operations require working Cloud access. Therefore, successful configuration should not be confused with verified live memory functionality.

This distinction is important when evaluating the complete system.

Lessons Learned

Working on RecallOps highlights several important engineering lessons:

1. Documentation matters: Recording root causes and resolutions helps preserve technical knowledge.
2. Incident history is valuable: Previous incidents can provide useful context during future investigations.
3. Memory adds another dimension: Agent memory creates opportunities to retrieve knowledge beyond manually searching records.
4. Separation of responsibilities helps: Keeping frontend, backend, and database components separate makes the application easier to organize and maintain.
5. Integration must be verified: Configuring an external service is only one step; its actual functionality must also be tested.

Future Scope

RecallOps can be extended with additional capabilities to improve incident investigation.

Potential improvements include AI-assisted root cause analysis, semantic incident search, automated incident classification, intelligent runbook recommendations, and integration with monitoring and alerting platforms.

Further improvements to the Hindsight integration could also help make historical incident knowledge more accessible through automated retain and recall workflows.

These enhancements could make RecallOps more useful for engineering teams managing complex production environments.

Conclusion

RecallOps explores an important problem in software engineering: how to make previous incident knowledge useful when new problems occur.

By combining incident tracking, root cause documentation, resolution management, dashboard statistics, keyword search, runbook recommendations, and Hindsight memory integration, the project provides a foundation for more organized incident investigation.

The biggest takeaway is that solving an incident should not be the end of its value. The knowledge gained from resolving one problem can become useful when another engineer faces a similar challenge.

With reliable memory integration and further development, RecallOps aims to make incident response more consistent, knowledge-driven, and efficient.