IBMCloud Tutorials

IBM Cloud Tutorials Roadmap

Section 1: IBM Cloud Fundamentals and Getting Started

  • Introduction to Cloud Computing:
    • What is Cloud Computing? (IaaS, PaaS, SaaS).
    • Benefits of Cloud Computing (Scalability, Elasticity, Cost Savings, Agility).
    • Public, Private, and Hybrid Cloud models.
  • Introduction to IBM Cloud:
    • What is IBM Cloud? (IBM's comprehensive cloud platform).
    • Overview of IBM Cloud's offerings and services.
    • Key differentiators of IBM Cloud (Enterprise-grade, Hybrid Cloud focus, AI/Data/Security services).
  • Getting Started with IBM Cloud:
    • Creating an IBM Cloud Account (Lite account for free access).
    • Navigating the IBM Cloud Console.
    • Understanding IBM Cloud Regions and Availability Zones.
    • Understanding Resource Groups and IAM (Identity and Access Management).
  • Understanding IBM Cloud Pricing:
    • Introduction to IBM Cloud pricing models (Pay-as-you-go, Subscription).
    • Estimating costs for various services.
    • Monitoring your spending.

Section 2: Core Compute Services

  • Virtual Servers (IaaS):
    • Introduction to IBM Cloud Virtual Servers (Classic and VPC).
    • Creating and managing Virtual Server Instances (VSIs).
    • Understanding different VSI profiles and specifications.
    • Connecting to VSIs (SSH).
    • Managing storage for VSIs (Block Storage, File Storage).
    • Understanding Networking for VSIs (Public vs. Private IPs, Security Groups, ACLs).
  • IBM Cloud Kubernetes Service (IKS) and Red Hat OpenShift on IBM Cloud (ROKS):
    • Introduction to Containers and Container Orchestration (Docker, Kubernetes).
    • Understanding the benefits of IKS/ROKS.
    • Creating and managing IKS/ROKS clusters.
    • Deploying applications to Kubernetes/OpenShift.
    • Managing deployments, services, and ingress.
    • Understanding worker pools and scaling.
    • Integrating with other IBM Cloud services.
  • Serverless Computing (IBM Cloud Functions):
    • Introduction to Serverless Computing (Functions as a Service - FaaS).
    • Understanding IBM Cloud Functions (based on Apache OpenWhisk).
    • Creating and deploying functions (using various languages).
    • Understanding triggers and actions.
    • Integrating with other services (e.g., Cloudant, Kafka).

Section 3: Storage Services

  • IBM Cloud Object Storage (COS):
    • Introduction to Object Storage.
    • Understanding IBM Cloud Object Storage (S3-compatible).
    • Creating and managing buckets.
    • Uploading and downloading objects.
    • Understanding storage classes (Standard, Vault, Cold Vault, Flex).
    • Managing access control (IAM, ACLs).
    • Using the COS API and SDKs.
  • Block Storage:
    • Introduction to Block Storage.
    • Creating and attaching Block Storage volumes to VSIs.
    • Understanding different performance tiers.
    • Managing snapshots and backups.
  • File Storage:
    • Introduction to File Storage (NFS-based).
    • Creating and mounting File Storage volumes to VSIs.
    • Understanding different performance tiers.

Section 4: Database Services

  • Introduction to IBM Cloud Databases:
    • Overview of the IBM Cloud Databases portfolio (relational, NoSQL, key-value).
    • Understanding the benefits of managed database services.
  • IBM Cloud Databases for PostgreSQL:
    • Creating and managing a PostgreSQL instance.
    • Connecting to the database.
    • Basic database operations.
    • Scaling and monitoring.
  • IBM Cloud Databases for MongoDB:
    • Creating and managing a MongoDB instance.
    • Connecting to the database.
    • Basic database operations.
    • Scaling and monitoring.
  • IBM Cloudant (NoSQL Database):
    • Introduction to Cloudant (JSON document database).
    • Creating and managing a Cloudant instance.
    • Creating databases and documents.
    • Querying data (MapReduce, Cloudant Query).
    • Understanding synchronization and offline access.
  • Other Database Services (Optional):
    • IBM Cloud Databases for Redis.
    • IBM Cloud Databases for etcd.
    • IBM Cloud Databases for Elasticsearch.
    • IBM Db2 on Cloud (Managed relational database).

Section 5: Networking Services

  • IBM Cloud Virtual Private Cloud (VPC):
    • Introduction to VPC concepts (Subnets, Security Groups, ACLs).
    • Creating and configuring a VPC.
    • Deploying VSIs within a VPC.
    • Understanding public gateways and floating IPs.
  • IBM Cloud Classic Infrastructure Networking (Optional):
    • Understanding VLANs, subnets, and routing in Classic infrastructure.
    • Public and private network configurations.
  • Load Balancing:
    • Introduction to Load Balancers (Application Load Balancer, Network Load Balancer).
    • Creating and configuring Load Balancers.
    • Distributing traffic to backend servers.
  • DNS Services:
    • Introduction to DNS (Domain Name System).
    • Using IBM Cloud Internet Services (CIS) for DNS management (based on Cloudflare).
  • VPN and Direct Link:
    • Connecting your on-premises network to IBM Cloud (VPN, Direct Link).
    • Understanding hybrid connectivity options.

Section 6: Security and Identity Management

  • IBM Cloud Identity and Access Management (IAM):
    • Understanding IAM roles and policies.
    • Managing users, service IDs, and access groups.
    • Assigning fine-grained access to resources.
  • Security Groups and Network ACLs (VPC):
    • Configuring ingress and egress rules to control network traffic.
  • IBM Cloud Certificate Manager:
    • Managing SSL/TLS certificates.
  • IBM Cloud Security Advisor (Optional):
    • Understanding security posture and recommendations.
  • Key Management Services (Optional):
    • IBM Cloud Key Protect (Managed encryption key service).
    • IBM Cloud Hyper Protect Crypto Services (Dedicated hardware security module).

Section 7: AI and Machine Learning Services

  • IBM Watson Services:
    • Introduction to IBM Watson (IBM's suite of AI services).
    • Exploring key Watson services (e.g., Assistant, Natural Language Understanding, Speech to Text, Text to Speech, Visual Recognition).
    • Using Watson APIs and SDKs.
  • IBM Cloud Pak for Data (Platform for Data and AI):
    • Introduction to Cloud Pak for Data (integrated platform for data science, machine learning, and AI).
    • Understanding its components (Data Virtualization, Data Refinery, Watson Studio, etc.).
    • Building and deploying machine learning models.
  • Machine Learning Services (Optional):
    • IBM Watson Studio (IDE for data science and ML).
    • IBM Watson Machine Learning (Deploying and managing ML models).

Section 8: Data and Analytics Services

  • IBM Cloud Data Services Overview:
    • Introduction to IBM Cloud's data and analytics offerings.
  • IBM Analytics Engine (Based on Spark and Hadoop):
    • Running Spark and Hadoop jobs on IBM Cloud.
    • Processing large datasets.
  • IBM Event Streams (Based on Kafka):
    • Introduction to Event Streams (Managed Kafka service).
    • Publishing and subscribing to topics.
    • Building real-time data pipelines.
  • Data Integration Services (Optional):
    • IBM DataStage (ETL tool).
    • IBM Cloud Pak for Integration (Comprehensive integration platform).

Section 9: Developer Tools and DevOps

  • IBM Cloud CLI (Command Line Interface):
    • Installing and configuring the IBM Cloud CLI.
    • Managing resources from the command line.
  • IBM Cloud Schematics (Infrastructure as Code):
    • Introduction to Infrastructure as Code (IaC).
    • Using IBM Cloud Schematics with Terraform.
    • Provisioning and managing infrastructure using code.
  • Continuous Integration and Continuous Delivery (CI/CD):
    • Introduction to CI/CD pipelines.
    • Using IBM Cloud Continuous Delivery (Toolchains, Delivery Pipelines, Git Repos).
    • Automating builds, tests, and deployments.
  • Monitoring and Logging:
    • IBM Cloud Monitoring (Based on Sysdig).
    • IBM Cloud Activity Tracker (Based on LogDNA).
    • Setting up monitoring and logging for applications and services.
    • Creating alerts and dashboards.
  • Application Performance Management (APM) (Optional):
    • IBM Cloud App Management.

Section 10: Enterprise and Hybrid Cloud (Optional)

  • IBM Cloud Satellite:
    • Extending IBM Cloud services to on-premises, edge, or other cloud environments.
    • Managing distributed applications and infrastructure.
  • IBM Cloud Paks:
    • Understanding IBM Cloud Paks (containerized software solutions for specific domains).
    • Deploying and managing Cloud Paks on OpenShift.
  • IBM Cloud for Financial Services (Optional):
    • Understanding industry-specific cloud solutions.

Section 11: Practice and Projects

  • Deploy a Simple Web Application:
    • Using Virtual Servers, Kubernetes, or Cloud Functions.
    • Connect it to a database service (e.g., PostgreSQL, Cloudant).
  • Build a Data Pipeline:
    • Ingest data using Event Streams.
    • Store data in Object Storage.
    • Process data using Analytics Engine or a serverless function.
  • Develop an AI-Powered Application:
    • Integrate a Watson service (e.g., Assistant, NLU) into an application.
  • Implement a CI/CD Pipeline:
    • Automate the build and deployment of an application using IBM Cloud Continuous Delivery.
  • Explore IBM Cloud Solutions Tutorials:
    • IBM provides many guided tutorials for specific use cases.