Azure Functions
azure.microsoft.comBuild event-driven serverless applications with triggers, bindings, and several hosting plans.
Build event-driven serverless applications with triggers, bindings, and several hosting plans.
A managed GridDB service for collecting and querying time-series data from applications and devices.
Deploy automatically scaling functions with HTTP, scheduled, and event-driven triggers on Scaleway.
Write JavaScript load tests and run them locally or send performance tests to Grafana Cloud.
Run your existing automated browser tests on BrowserStack's hosted browser grid.
A hosted server-monitoring service for host metrics, cloud integrations, containers, alerts, and dashboards.
Show estimated cloud-cost changes and FinOps checks alongside infrastructure code reviews.
Copy and synchronize files between a local machine and configured cloud-storage remotes.
A persistent cloud VS Code workspace with a Linux container, terminal, debugger, and ready-made project templates.
A Go library for verifying infrastructure code by deploying it, checking behavior, and cleaning up resources.
Correlates logs, metrics, traces, and user-experience telemetry for application and infrastructure troubleshooting.
A private diary app with mood, media, local-first writing, and optional cloud sync.
A managed SQL service that provisions database resources by instance.
Access Microsoft cloud data and services through one REST endpoint and SDKs.
A privacy-oriented notes app with Markdown import and user-managed cloud-sync options.
AI-guided cloud-native observability for telemetry, service health, and cost control.
Run repository builds, tests, and deployments from a bitbucket-pipelines.yml file in Bitbucket Cloud.
Collect logs, metrics, and traces through OpenTelemetry or cloud integrations, then investigate alert signals in a shared telemetry workspace.
Draft, review, and publish documentation collaboratively from a cloud workspace.
Open-source tracing and production evaluation for LLM applications and agents.
Attribute Kubernetes spend to clusters, teams, namespaces, and workloads, then surface savings opportunities.
Test configuration policies, then converge managed systems to their declared state.
Run event handlers, HTTP workloads, or isolated compute without managing servers.
Deploy app services from GitHub or templates, then manage them from a shared project dashboard.