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Cloud Computing in Application Development

$249.00
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Includes a practical, ready-to-use toolkit containing implementation templates, worksheets, checklists, and decision-support materials used to accelerate real-world application and reduce setup time.
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This curriculum spans the technical and operational breadth of cloud adoption in large-scale software organisations, comparable in scope to a multi-workshop architecture immersion or an internal cloud centre of excellence program.

Module 1: Cloud Infrastructure Selection and Sizing

  • Selecting between on-demand, reserved, and spot instances based on workload predictability and cost tolerance.
  • Right-sizing virtual machine configurations by analyzing CPU, memory, and I/O utilization patterns from production telemetry.
  • Evaluating regional versus availability zone placement for compliance, latency, and fault isolation requirements.
  • Implementing storage tiering strategies using object, block, and file storage based on access frequency and durability needs.
  • Designing network topology with VPCs, subnets, and routing tables to support multi-tier application architectures.
  • Assessing egress costs and data transfer implications when integrating with third-party SaaS platforms.

Module 2: Cloud-Native Application Architecture

  • Decomposing monolithic applications into microservices with bounded contexts and independent deployment pipelines.
  • Choosing between serverless functions and containerized services based on cold start sensitivity and execution duration.
  • Implementing circuit breakers and retry policies in inter-service communication to handle transient failures.
  • Designing stateless services with externalized session storage to support horizontal scaling.
  • Integrating service mesh components for observability, mTLS, and traffic control in multi-service environments.
  • Managing configuration drift by externalizing environment-specific settings into centralized configuration stores.

Module 3: Identity, Access, and Security Governance

  • Enforcing least-privilege access using IAM roles and policies tied to service identities rather than long-lived credentials.
  • Implementing multi-factor authentication and conditional access policies for administrative console access.
  • Rotating secrets and API keys using automated secret management tools integrated into deployment workflows.
  • Configuring audit logging and monitoring for unauthorized access attempts across cloud resources.
  • Applying security group and network ACL rules to restrict inter-service communication to required ports and protocols.
  • Managing cross-account access for shared services using role assumption and organizational units.

Module 4: Data Management and Persistence in the Cloud

  • Selecting managed database services based on consistency, scalability, and operational overhead trade-offs.
  • Designing backup and point-in-time recovery strategies for databases with regulatory retention requirements.
  • Implementing read replicas and sharding to handle high-read and high-write workloads.
  • Encrypting data at rest and in transit using customer-managed or cloud provider key management systems.
  • Handling data residency and sovereignty by restricting storage and processing to approved geographic regions.
  • Migrating large datasets between cloud environments using offline transfer appliances or optimized bulk services.

Module 5: CI/CD and DevOps Automation

  • Designing immutable infrastructure pipelines that rebuild and redeploy artifacts instead of in-place updates.
  • Integrating security scanning tools into CI pipelines to detect vulnerabilities before deployment.
  • Implementing blue-green or canary deployments with automated rollback triggers based on health metrics.
  • Managing infrastructure as code using version-controlled templates with peer review and drift detection.
  • Orchestrating cross-environment promotions with manual approval gates for production changes.
  • Enforcing pipeline concurrency limits to prevent resource contention during parallel deployments.

Module 6: Monitoring, Observability, and Incident Response

  • Instrumenting applications with structured logging and distributed tracing to diagnose latency bottlenecks.
  • Defining service level objectives and error budgets to guide incident prioritization and release pacing.
  • Configuring alerting thresholds to minimize noise while ensuring critical failures trigger immediate response.
  • Correlating metrics, logs, and traces across services to identify root causes during outages.
  • Simulating failure scenarios using chaos engineering to validate system resilience.
  • Integrating monitoring data with incident management platforms for escalation and post-mortem tracking.

Module 7: Cost Management and Resource Optimization

  • Tagging resources with cost centers, environments, and owners to enable granular chargeback reporting.
  • Identifying underutilized instances and idle resources using cloud-native cost analysis tools.
  • Negotiating enterprise discount plans after establishing baseline usage and forecasting growth.
  • Implementing auto-scaling policies that balance performance SLAs with cost efficiency.
  • Archiving cold data to lower-cost storage tiers with retrieval time trade-offs.
  • Conducting regular cost reviews with engineering teams to align spending with business value.

Module 8: Hybrid and Multi-Cloud Integration Patterns

  • Establishing secure, low-latency connectivity between on-premises data centers and cloud VPCs using dedicated links.
  • Synchronizing identity directories across cloud and on-premises environments using federation protocols.
  • Designing data replication strategies for hybrid databases with conflict resolution mechanisms.
  • Standardizing deployment tooling across multiple cloud providers to reduce operational complexity.
  • Managing vendor lock-in risks by abstracting cloud-specific services behind façade interfaces.
  • Enforcing consistent security policies across cloud environments using centralized policy-as-code frameworks.