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Information Technology in Application Development

Information Technology in Application Development

$250.00
How you learn:
Self-paced • Lifetime updates
When you get access:
Course access is prepared after purchase and delivered via email
Your guarantee:
30-day money-back guarantee — no questions asked
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Trusted by professionals in 160+ countries
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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What does the Information Technology in Application Development course cover?

Information Technology in Application Development is covered here in 8 modules: Technology Stack Selection and Evaluation, Software Development Lifecycle Governance, Infrastructure as Code and Environment Management and 5 more. The outline lists 48 specific topics, opening with selecting between monolithic and microservices architectures based on team size, deployment frequency, and domain complexity.

How do you approach Information Technology in Application Development step by step?

The work is sequenced in 8 stages. It starts with Technology Stack Selection and Evaluation, moves through Software Development Lifecycle Governance and Infrastructure as Code and Environment Management, and ends at Cloud-Native Application Design and Operations. Each stage carries its own topic list, so the sequence is followed rather than summarised.

What is in Module 1 of the Information Technology in Application Development course?

Module 1 is Technology Stack Selection and Evaluation. It works through selecting between monolithic and microservices architectures based on team size, deployment frequency, and domain complexity., evaluating long-term maintainability of open-source frameworks by analyzing contributor activity and update frequency., assessing cloud provider lock-in risks when adopting proprietary managed services such as AWS Lambda or Azure Functions. and 3 more.

How is the Information Technology in Application Development course delivered?

The Information Technology in Application Development course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.

How much does the Information Technology in Application Development course cost?

The Information Technology in Application Development course is $250 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.

Closely related courses: Information Technology in Application Management, Information Requirements in Application Management, Application Security in Information Security Management, Information Technology in Application Performance.

More answers: what you get with every course, refund policy, all help answers.

This curriculum spans the technical and operational rigor of a multi-workshop program focused on enterprise-scale application development, covering the same breadth of concerns as an internal capability build for cloud-native systems, from architecture and security to deployment and data governance.

Module 1: Technology Stack Selection and Evaluation

  • Selecting between monolithic and microservices architectures based on team size, deployment frequency, and domain complexity.
  • Evaluating long-term maintainability of open-source frameworks by analyzing contributor activity and update frequency.
  • Assessing cloud provider lock-in risks when adopting proprietary managed services such as AWS Lambda or Azure Functions.
  • Choosing database technologies (SQL vs. NoSQL) based on query patterns, consistency requirements, and scalability needs.
  • Integrating front-end frameworks (React, Angular, Vue) with legacy systems while maintaining backward compatibility.
  • Conducting proof-of-concept benchmarks for performance-critical components before full-scale adoption.

Module 2: Software Development Lifecycle Governance

  • Defining branching strategies in Git (e.g., trunk-based vs. GitFlow) to balance release stability and feature velocity.
  • Implementing mandatory code review policies with role-based approvers for compliance and security-critical modules.
  • Establishing release gates that require automated test coverage thresholds and static analysis results.
  • Managing technical debt by allocating sprint capacity for refactoring and enforcing architectural guardrails.
  • Coordinating cross-team dependencies in agile environments using integration milestones and shared roadmaps.
  • Enforcing versioning discipline for APIs to support backward compatibility and client upgrade paths.

Module 3: Infrastructure as Code and Environment Management

  • Structuring Terraform modules to support multi-environment deployments with environment-specific overrides.
  • Managing secrets in CI/CD pipelines using vault integration versus environment variables.
  • Designing immutable infrastructure patterns to eliminate configuration drift in production.
  • Implementing blue-green deployments using infrastructure templates to reduce downtime and rollback risk.
  • Enforcing tagging standards across cloud resources for cost allocation and compliance audits.
  • Automating environment teardown for non-production instances to control cloud spending.

Module 4: Application Security and Compliance Integration

  • Integrating SAST and DAST tools into CI pipelines with fail-on-critical-vulnerability policies.
  • Implementing role-based access control (RBAC) at the application level aligned with enterprise identity providers.
  • Designing audit logging to capture user actions, data access, and configuration changes for regulatory reporting.
  • Applying data masking in non-production environments to comply with GDPR and HIPAA requirements.
  • Conducting threat modeling during design phases to identify attack surfaces and mitigation strategies.
  • Managing cryptographic key rotation schedules and storage in hardware security modules (HSMs) or cloud KMS.

Module 5: Scalability, Performance, and Observability

  • Setting up distributed tracing across microservices to diagnose latency bottlenecks in production.
  • Configuring auto-scaling policies based on custom metrics such as request queue depth or CPU per container.
  • Designing caching strategies using Redis or CDN layers to reduce database load during traffic spikes.
  • Instrumenting applications with structured logging to support centralized log aggregation and alerting.
  • Establishing service-level objectives (SLOs) and error budgets to guide incident response priorities.
  • Conducting load testing with production-like data volumes to validate system behavior under peak conditions.

Module 6: DevOps and CI/CD Pipeline Engineering

  • Designing multi-stage pipelines with manual approval steps for production promotions in regulated industries.
  • Optimizing build times through parallelization, artifact caching, and incremental compilation.
  • Securing pipeline execution by restricting agent permissions and scanning container images for vulnerabilities.
  • Implementing canary deployments with automated rollback triggers based on error rate thresholds.
  • Managing configuration drift by enforcing declarative pipeline definitions stored in version control.
  • Integrating deployment notifications with incident management systems for operational transparency.

Module 7: Data Management and Integration Patterns

  • Selecting between batch ETL and real-time streaming (e.g., Kafka, Kinesis) based on data freshness requirements.
  • Designing idempotent message processors to handle duplicate events in distributed systems.
  • Implementing change data capture (CDC) to synchronize transactional and analytical databases.
  • Enforcing data validation and schema contracts at API boundaries to prevent integration failures.
  • Managing data retention and archival policies in alignment with legal and storage cost constraints.
  • Resolving data consistency issues in distributed transactions using saga patterns or compensating actions.

Module 8: Cloud-Native Application Design and Operations

  • Refactoring legacy applications for containerization while preserving stateful dependencies.
  • Designing service meshes (e.g., Istio, Linkerd) to manage traffic routing, mTLS, and observability.
  • Implementing health checks and readiness probes to ensure reliable Kubernetes pod scheduling.
  • Optimizing container resource requests and limits to balance performance and cluster utilization.
  • Managing cross-region failover strategies for stateful services with asynchronous data replication.
  • Applying cost-performance analysis to select appropriate instance types and spot/flexible VM usage.
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