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New Development in Application Development

New Development in Application Development

$249.00
When you get access:
Course access is prepared after purchase and delivered via email
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30-day money-back guarantee — no questions asked
How you learn:
Self-paced • Lifetime updates
Toolkit Included:
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 scope of a multi-quarter platform modernization initiative, covering the same depth of architectural decision-making, tool integration, and cross-team coordination seen in large-scale internal developer platform rollouts.

Module 1: Modern Application Architectures and Design Patterns

  • Selecting between monolithic, microservices, and serverless architectures based on team size, deployment frequency, and domain complexity.
  • Implementing service boundaries using domain-driven design (DDD) to minimize coupling in distributed systems.
  • Deciding when to adopt event-driven communication over request-response patterns in inter-service communication.
  • Designing for graceful degradation and circuit breaking in high-latency downstream service scenarios.
  • Managing schema evolution in shared message contracts across independently deployed services.
  • Integrating legacy systems using anti-corruption layers without introducing performance bottlenecks.

Module 2: Infrastructure as Code and Cloud-Native Deployment

  • Choosing between Terraform and cloud-native tools (e.g., AWS CloudFormation, Azure Bicep) for multi-cloud consistency vs. feature parity.
  • Structuring IaC modules to support environment parity while isolating secrets and region-specific configurations.
  • Implementing blue-green deployments with automated traffic shifting and rollback triggers in Kubernetes environments.
  • Managing state file locking and collaboration in shared Terraform configurations across multiple teams.
  • Enforcing cloud security baselines through policy-as-code tools like Open Policy Agent or HashiCorp Sentinel.
  • Optimizing container image build pipelines to reduce attack surface and improve pull times in CI/CD.

Module 3: Continuous Integration and Delivery at Scale

  • Designing parallelized test stages to reduce feedback loop duration in large monorepos.
  • Implementing canary analysis using metrics (latency, error rates) to gate production promotions.
  • Managing dependency versioning across shared libraries in a multi-repo environment with semantic release.
  • Securing CI/CD pipelines against credential leakage through ephemeral tokens and scoped permissions.
  • Integrating static analysis and SAST tools without introducing false positives that erode developer trust.
  • Orchestrating cross-environment configuration drift detection using GitOps principles and reconciliation loops.

Module 4: Observability and Runtime Intelligence

  • Instrumenting distributed systems with correlated trace IDs across service boundaries for root cause analysis.
  • Configuring log sampling strategies to balance cost and diagnostic completeness in high-volume systems.
  • Defining service-level objectives (SLOs) and error budgets that align with business availability requirements.
  • Integrating business metrics (e.g., transaction completion rate) into observability dashboards for operational context.
  • Selecting between open-source (e.g., Prometheus, OpenTelemetry) and vendor-managed telemetry backends.
  • Managing retention policies for logs, metrics, and traces under data sovereignty and compliance constraints.

Module 5: Security and Compliance in Development Workflows

  • Embedding security scanning (SCA, SAST, DAST) into pull request pipelines without blocking legitimate changes.
  • Implementing just-in-time access controls for production environments using identity brokers.
  • Managing secrets rotation in containers using external secret managers (e.g., HashiCorp Vault, AWS Secrets Manager).
  • Enforcing regulatory compliance (e.g., GDPR, HIPAA) through automated policy checks in CI/CD gates.
  • Auditing developer actions across infrastructure and code repositories for forensic readiness.
  • Hardening container runtimes with minimal base images and non-root execution policies.

Module 6: Data Management in Distributed Systems

  • Choosing between synchronous database transactions and eventual consistency based on user experience tolerance.
  • Implementing change data capture (CDC) to propagate data updates across services without tight coupling.
  • Partitioning databases by tenant or region to meet data residency requirements in global deployments.
  • Migrating schema in production databases with zero-downtime using dual-write and verification patterns.
  • Securing access to data stores using attribute-based access control (ABAC) instead of role-based models.
  • Designing offline-first capabilities in client applications using local data synchronization strategies.

Module 7: Platform Engineering and Internal Developer Platforms

  • Defining self-service interfaces for common provisioning tasks (e.g., databases, queues) using UI or CLI.
  • Measuring platform adoption through developer onboarding time and ticket reduction metrics.
  • Integrating third-party tools (e.g., monitoring, logging) into a unified developer console.
  • Managing API gateway configurations and rate limiting policies across multiple teams.
  • Standardizing application scaffolding templates that include security and observability defaults.
  • Balancing platform standardization with team autonomy in technology selection for specialized workloads.

Module 8: Evolutionary Practices and Technical Debt Management

  • Tracking technical debt using issue tagging and backlog prioritization in sprint planning.
  • Refactoring legacy components incrementally using the strangler pattern without disrupting business flows.
  • Allocating time for maintenance work in product roadmaps without diluting feature delivery commitments.
  • Measuring code health using metrics like cyclomatic complexity and test coverage trends over time.
  • Conducting architecture decision record (ADR) reviews to ensure alignment and traceability of key choices.
  • Establishing cross-functional guilds to share knowledge on emerging tools and patterns across engineering teams.
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