Dyalog APL Development Environment
dyalog.comDevelop APL programs in an integrated environment with a Windows IDE and the cross-platform RIDE interface.
Develop APL programs in an integrated environment with a Windows IDE and the cross-platform RIDE interface.
An integrated development environment for building desktop, web, and mobile applications with the Xojo language.
A free B4X development tool for desktop, server, and IoT programs, with an IDE and visual designer.
A cross-platform IDE for building Qt applications for desktop, embedded, and mobile targets.
A YAML-based CLI for asserting the installed packages, services, files, ports, and other state of a system.
A coverage-guided fuzzer that mutates input corpora to find crashes and hangs in instrumented programs.
Combine talent assessments and screening information for recruitment, mobility and development discussions.
Use role-specific assessment information for hiring conversations and employee development.
An environment-neutral Python API for font-development objects.
A cloud development workspace with browser and virtual-machine sandboxes plus a VS Code-based editor.
Promote application configuration through GitOps stages so a GitOps agent can deploy each stage.
Deploy supported application code to managed dynos without administering the host servers.
Query and update YAML, JSON, XML, and other structured data from the command line.
Run GitHub Actions-compatible workflows on Depot compute with local-run and job-debugging tools.
Automate dependency and lockfile updates through reviewable pull requests across many repository platforms.
Show estimated cloud-cost changes and FinOps checks alongside infrastructure code reviews.
A Go library for verifying infrastructure code by deploying it, checking behavior, and cleaning up resources.
Provision Kubernetes clusters and node pools with Vultr-managed control-plane and worker-node operations.
An agent-based monitoring pipeline that turns checks and metrics into routed, actionable events.
Combine Python expressions and shell commands in one Python-based command prompt.
Collect and inspect distributed traces from instrumented applications with a self-managed tracing platform.
Monitor system resources and processes from a terminal or web interface.
Collect, process, and route logs, metrics, and traces with a lightweight telemetry agent.
Advance application releases through configured deployment targets.