Use Case · Cloud Architects

Multi-Cloud Cron Scheduling

One scheduler across AWS, GCP, Azure, and your private clouds. Stop maintaining three job catalogs and start orchestrating workflows the way they actually run — across clouds, with one source of truth.

AWS · GCP · AzureCross-Cloud DependenciesUnified Audit Trail
01 / The Sprawl

Per-Cloud Schedulers Don't Compose

Each cloud ships its own scheduler. Teams running on more than one end up with one of these problems.

Three clouds, three schedulers

EventBridge for AWS, Cloud Scheduler for GCP, Azure Logic Apps. Each has its own UI, IAM, and pricing model. Engineers context-switch all day.

Cross-cloud jobs are hacks

Sync data from S3 to BigQuery? You glue together a Lambda, a Function, and a workflow. No single owner, no single log.

Drift between environments

Your prod schedule lives in five places. Staging is missing two jobs. No one can answer “what runs at 02:00 UTC” without grep-ing five consoles.

Compliance audits are painful

Pulling execution history across clouds for SOC 2 evidence means CSV exports, timestamp normalization, and a lot of pivot tables.

02 / The Platform

Cloud-Agnostic by Design

One schedule, every cloud

Define jobs once. Target any compute that accepts SSH or HTTP — EC2, GCE, Azure VMs, on-prem boxes — through the same dashboard.

Cross-cloud dependency chains

Trigger a BigQuery export job only after the upstream RDS dump succeeds, regardless of which cloud each runs on.

Unified execution history

Every run, every cloud, one timeline. Filter by tag, environment, status. Export audit-ready evidence with one click.

Single IAM, single secret store

Manage credentials for all clouds in one encrypted vault. RBAC scoped per workspace, per environment, per cloud.

Cloud-agnostic alerting

Slack, email, webhook alerts that don't care whether the failing job ran in AWS or your Mumbai data center.

No per-cloud lock-in

Migrate workloads between clouds without rewriting schedules. The control plane stays the same.

03 / In Production

What Cloud Teams Run on Krons24

Cross-cloud data sync

RDS → S3 → BigQuery → Snowflake pipelines orchestrated as a single workflow with proper failure isolation and retry policy.

Multi-region disaster recovery

Coordinate snapshot, replication, and failover drills across us-east-1, eu-west-2, and ap-south-1 from one runbook.

Cost optimization sweeps

Scheduled audits that scan idle resources across AWS, GCP, and Azure — flag, alert, and auto-tag anything matching cleanup policy.

Hybrid on-prem + cloud workflows

Trigger an on-prem ETL after a cloud pipeline finishes — and vice versa. No glue Lambdas, no homegrown queue.

Get Started

One Scheduler. Every Cloud.

Self-deploy in five minutes. Connect your first cloud target in another two. Free 14-day trial — no per-cloud markup.