Instalog

Instalog is an AI-driven developer tool that simplifies and automates the process of adding effective, contextual logs to your code. Designed specifically for developers and DevOps teams, it ensures your application has comprehensive, meaningful logs—without the need for manual instrumentation.

With just one command, Instalog scans your codebase, understands its context, and suggests or inserts production-grade log statements where they’re most needed. This improves observability, debugging, and monitoring while saving time and enforcing consistency across teams.

Features

• AI-Generated Logs: Automatically adds logs with meaningful context in code hotspots like conditionals, loops, and error handlers.

• Language Support: Currently supports Python, JavaScript, TypeScript, Go, with more languages on the roadmap.

• Smart Code Analysis: Understands function purpose, parameters, and control flow for relevant log placement.

• One-Command CLI Tool: Start with instalog scan and apply logs with instalog apply.

• Structured Logging: Outputs logs in JSON or human-readable formats, compatible with tools like Datadog, Sentry, Logstash.

• Customizable Templates: Aligns with your log style guide or existing observability stack.

• Review & Control: Approve, edit, or reject suggested logs before applying changes to your codebase.

• IDE & CI/CD Integration: Available as a CLI tool and soon as a VS Code extension; can also be added to pre-commit or CI/CD flows.

How It Works

1. Install Instalog: Use npm, brew, or the provided binary to install Instalog locally.

2. Run instalog scan: The tool analyzes your codebase and identifies where logs should be inserted.

3. Review Suggestions: You receive a list of AI-generated logs tied to specific lines of code.

4. Apply Logs with instalog apply: Instalog modifies your files to include the selected logs.

5. Deploy and Monitor: Use your existing observability platform to view logs in real time.

Instalog requires no backend setup, making it suitable for teams looking for fast adoption with low overhead.

Use Cases

• Legacy Codebases: Add logs to large, uninstrumented codebases to boost observability.

• Incident Response: Improve logging in critical paths for faster post-mortem analysis.

• New Feature Deployment: Ensure new code is traceable and easy to debug.

• Standardizing Logs: Enforce uniform log structure across developers and services.

• Faster Debugging: Get relevant context in logs during development and production troubleshooting.

Pricing

As of May 2025, Instalog offers the following pricing tiers:

Free Plan

• Up to 3 users

• CLI access

• Support for small repos

• Community support via Discord or GitHub

Pro Plan – $19/user/month

• Unlimited users

• Larger repositories

• Advanced CLI and upcoming IDE features

• Priority support

• Custom log formats

Team Plan – $49/user/month

• Team collaboration features

• Custom templates and organization-wide settings

• Integration with Sentry, Datadog, Loggly, and others

• Role-based access and usage dashboards

Enterprise Plan – Custom Pricing

• SSO & SCIM provisioning

• On-premise or VPC deployment

• Dedicated support & onboarding

• Audit logs and compliance features (SOC 2, ISO 27001)

• SLA-backed uptime

Strengths

• Saves hours of manual log writing

• Smart, contextual logs improve observability immediately

• Seamless CLI integration—easy for developers to adopt

• Compatible with modern observability tools

• Customizable to fit any logging format or standard

• Scalable for teams of all sizes

Drawbacks

• Limited to supported languages (Python, JS/TS, Go)

• Doesn’t store or visualize logs—requires external logging tools

• AI-generated logs may occasionally need manual refinement

• Advanced integrations and team features are gated behind paid plans

• Lacks automatic log pruning or aging features

Comparison with Other Tools

Instalog vs. Manual Logging

Manual logging is time-consuming and often inconsistent. Instalog provides consistent, automated, and context-aware logging with less effort.

Instalog vs. GitHub Copilot

While Copilot can suggest logs, Instalog scans the whole codebase and generates logs contextually at scale, not just line-by-line.

Instalog vs. Sentry or Datadog

Sentry and Datadog handle log ingestion and analysis. Instalog automates log creation, complementing these tools.

Instalog vs. Tailscale Observability Tools

Tailscale tools are infrastructure-focused. Instalog is code-focused, ideal for developers during coding and CI/CD.

Customer Reviews and Testimonials

“Instalog helped us reduce incident response times by making logs more actionable.”

“Perfect for legacy microservices that never had proper logs.”

“It’s like an AI-powered observability assistant that knows what matters in your code.”

Developers and SREs report saving significant time and gaining visibility across previously opaque code paths.

Conclusion

Instalog solves a widespread developer problem—effective and consistent logging—using the power of AI. By scanning your codebase and intelligently inserting logs where they matter most, it saves time, improves system transparency, and aligns with modern observability practices.

If you’re tired of writing and maintaining logs manually, or if your team struggles with debugging due to poor instrumentation, Instalog offers a fast, scalable, and intelligent solution. Add it to your toolchain to make your logs—and your codebase—smarter.