IONOS Cloud Developer

Developer certification for engineers who interact with IONOS Cloud programmatically: Infrastructure as Code with Terraform, API and SDK integration, container workflows, CI/CD pipelines, and production operations. Rebuilt around DevOps workflows with IONOS-specific constraints and code patterns throughout.

Course Details

How to Use This Course

1. Complete all units sequentially - content builds progressively through the TaskBoard application scenario.
2. Run the Code Lab in each unit - hands-on coding is essential for developer certification.
3. Keep a terminal open alongside the course material for trying commands and code snippets.
4. Pay attention to IONOS-specific constraints highlighted in each unit - these prevent production debugging frustration.
5. Use the API Reference Quick Cards as cheat sheets during development.
6. The Common Pitfalls sections contain real-world debugging knowledge specific to IONOS.

Module 1: Programmatic Foundations (12%)

Core skills for programmatic interaction with IONOS Cloud: API authentication, the async provisioning model, SDKs, CLI, and Infrastructure as Code with Terraform. TaskBoard scenario introduced.

Duration: ~36 min

Topics Covered:

• IONOS Cloud REST API, versioning, content types, and the TaskBoard build scenario
• Authentication with Bearer tokens (Token Manager) and Basic auth, token rotation, and least-privilege scoping
• The async provisioning model: 202 responses, request IDs, and polling for completion
• IONOS SDKs (Python, Go, Java, JavaScript) and the ionosctl CLI
• Rate limiting with exponential backoff, pagination, and error handling
• The IONOS Terraform provider: installation, authentication, and version pinning
• Core Terraform resources, plan/apply/destroy lifecycle, state backends, data sources, and resource import
• Cost awareness and ephemeral environment patterns

Module 2: Infrastructure as Code (26%)

Provisioning complete IONOS infrastructure stacks via Terraform and API: compute with auto-scaling, networking with security groups and load balancers, storage tiers, managed databases, and event streams.

Duration: ~80 min

Topics Covered:

• Server automation: Dedicated Core vs vCPU, cloud-init bootstrap, public IP allocation, images and snapshots
• VM Auto Scaling (horizontal-only; replica config applies to new replicas) and Cubes (mandatory direct-attached NVMe storage, plus up to 23 additional HDD/SSD Block Storage volumes)
• Network as code: LANs, NICs, NAT gateways, IPsec VPN, and Cloud DNS for multi-tier topologies
• Load balancing with Managed ALB and NLB, and where NSG rules apply (server-NIC level only)
• Storage provisioning: Block Storage, S3-compatible Object Storage, and NFS, with availability-zone constraints
• Managed database and streaming provisioning: PostgreSQL, MongoDB, MariaDB, In-Memory DB, and Kafka
• Extracting connection strings and credentials from Terraform state as sensitive outputs

Module 3: Container Workflows and CI/CD (22%)

Building container image pipelines, deploying to Managed Kubernetes, and automating the full build-test-deploy cycle with CI/CD.

Duration: ~46 min

Topics Covered:

• IONOS Container Registry provisioning and token-based docker login (no RBAC, no per-team repos)
• Multi-stage Dockerfiles and the build, tag, push image pipeline pattern
• Provisioning Managed Kubernetes via Terraform and retrieving kubeconfig
• Deployments, Services, ConfigMaps, Secrets, and the separately provisioned ingress load balancer model
• Pulling images with imagePullSecrets and debugging on MKS with kubectl
• CI/CD pipeline design with GitHub Actions and GitLab CI, Terraform plan-on-PR and apply-on-merge
• Secret management in pipelines, deployment strategies, rollback, and reusable Terraform modules

Module 4: Application Service Integration (22%)

Integrating IONOS managed services into application code: database connections and caching patterns, S3-compatible Object Storage, Kafka producers/consumers, and AI Model Hub inference API.

Duration: ~65 min

Topics Covered:

• Connecting to PostgreSQL, MariaDB, and MongoDB with required TLS and application-level connection pooling
• In-Memory DB (Redis) caching patterns as the IONOS-native read-scaling solution (no DB read replicas)
• PITR via API and dump/restore scheduling, since Backup Service does not back up managed DBaaS
• S3-compatible Object Storage with boto3, Access Key and Secret Key auth, and presigned URLs
• Multipart uploads, lifecycle policies, and S3 compatibility gotchas
• Kafka producers and consumers, consumer groups, dead-letter handling, schema management, and reliability tuning
• AI Model Hub inference API integration, error handling, cost awareness, and result caching

Module 5: Production Operations (18%)

Operating applications in production on IONOS Cloud: monitoring and debugging with platform observability tools, security automation for tokens and network access, and GitOps for declarative deployments.

Duration: ~52 min

Topics Covered:

• IONOS Monitoring Service metrics and alerts, Logging Service collection and forwarding
• Activity Logs and Flow Logs for audit and network-level debugging
• The Kubernetes debugging workflow and the control-plane log-forwarding constraint
• API token lifecycle automation with Token Manager and IAM automation via API and Terraform
• Kubernetes secrets from Terraform outputs, NSG automation, and SSH Key Manager
• GitOps principles, ArgoCD on MKS, repository topology, and environment promotion
• Ephemeral environment cleanup and reconciling Terraform-managed infrastructure with GitOps-managed applications

Learning Outcomes

By the end of this course, you will be able to:

• Authenticate and interact with the IONOS Cloud API using the async provisioning model, SDKs, and ionosctl CLI.
• Provision and manage complete infrastructure stacks (compute, networking, storage, databases) using Terraform with the IONOS provider.
• Build container image pipelines with IONOS Container Registry and deploy to Managed Kubernetes.
• Design and implement CI/CD pipelines that build, test, and deploy to IONOS Cloud.
• Integrate IONOS managed databases, Object Storage, Kafka, and AI Model Hub into application code.
• Monitor, debug, and secure applications running on IONOS Cloud using platform observability and IAM tools.
• Apply IONOS-specific constraints and auth patterns correctly in automated workflows.

Next Steps

Build a Production Project

• Deploy a full-stack web application with CI/CD to IONOS Managed Kubernetes.
• Build a data processing pipeline with Kafka and managed databases.
• Create a Terraform module library for your team's common IONOS patterns.
• Set up a GitOps workflow with ArgoCD on IONOS Managed Kubernetes.
• Build an AI-powered feature using IONOS AI Model Hub API.

Level Up

• IONOS Cloud Expert certification for architecture and design strategy.
• IONOS Kubernetes Deep Dive for advanced container orchestration.
• IONOS AI Specialty for building ML/AI applications on IONOS.

Join the Developer Community

• Contribute to IONOS Terraform provider or SDK open-source projects.
• Share your deployment patterns and IaC modules.
• Attend IONOS developer meetups and hackathons.

Resources