Graylog
graylog.orgCentralize application and infrastructure logs for search, routing, dashboards, and alerts.
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Ask SI to compare Developer Tools toolsCentralize application and infrastructure logs for search, routing, dashboards, and alerts.
Explore traces and wide events from instrumented applications to investigate production behavior.
Build, test, and deploy code through visual or YAML-defined CI/CD pipelines.
Turn address text into OpenStreetMap place results, or look up an address from coordinates.
Load test websites, applications, and APIs with scripted browser or protocol bots, then inspect performance reports.
Read, update, and append spreadsheet cell values from an application.
Create standalone Spring applications with auto-configuration and an executable application package.
Build, run, debug, test, and profile Android applications in Google’s Android-focused IDE.
Generate Java unit-test code from IntelliJ classes and methods, with CLI and CI options in paid editions.
Compose file-processing jobs from import, conversion, and export tasks.
A C++ test framework for unit tests, behavior-driven cases, and basic micro-benchmarks.
Navigate files in a terminal with tabs, previews, multi-selection, and optional shell integration.
Orchestrate Terraform and OpenTofu projects while reusing configuration across infrastructure units.
A YAML-based CLI for asserting the installed packages, services, files, ports, and other state of a system.
A reactive Python notebook editor that saves notebooks as ordinary Python files.
Lint and format Python projects with one configurable command-line tool.
Write statically typed Nim programs and compile them with a toolchain designed for systems and application work.
Measure how well JavaScript and TypeScript tests detect deliberately introduced code changes.
Define JavaScript and TypeScript schemas that validate data and infer its types.
Run DuckDB-based analytics in a managed cloud warehouse and share results with a team.
A composable pipeline for collecting, transforming, and routing logs and metrics.
Run analytical SQL in an embedded database from a local process or Python program.
Keep Kubernetes applications in sync with their declared configuration in Git.
Run source-built or containerized web services on managed, autoscaling infrastructure.