Course Overview of Application Development with Cloud Run

Cloud Composer is a fully managed workflow orchestration service built on Apache Airflow. This course provides a comprehensive guide to provisioning Composer instances, creating and managing Airflow Directed Acyclic Graphs (DAGs), and performing essential tasks such as testing, debugging, and monitoring workflows.

After completing Application Development with Cloud Run, Students will be able to

  • Define and build container images for application packaging.
  • Identify best practices for creating, testing, and securing containers.
  • Develop, test, and deploy applications and functions on Cloud Run.
  • Manage the container lifecycle, resource models, and autoscaling.
  • Implement service identity and IAM for secure application access.
  • Integrate Cloud Run applications with various Google Cloud services.

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Key Features of Application Development with Cloud Run

  • Comprehensive 3-in-1 Curriculum- Combines topics on creating containers, developing with Cloud Run, and Cloud Run functions.

  • Hands-On Learning- Includes 6 high-impact labs and multiple interactive quizzes to reinforce technical skills.

  • Production-Ready Focus- Covers advanced topics like traffic splitting, secrets management, and failure retries. 

  • Local-to-Cloud Workflow- Teaches how to develop and test applications locally before moving to production in the cloud.

  • Security Integrated- Dedicated modules on IAM, service identity, and protecting data with encryption keys.

Who should Attend Application Development with Cloud Run?

  • Cloud Developers
  • Solutions Architects
  • DevOps Engineers

Prerequisites of Application Development with Cloud Run

Familiarity with at least one high-level programming language (e.g., Python, Node.js, Go) and basic command-line proficiency.

Why choose CloudThat as your training partner for Application Development with Cloud Run?

  • Specialized GCP Focus- CloudThat specializes in cloud technologies, offering focused and specialized training programs. We are Authorized Trainers for the Google Cloud Platform. This specialization ensures in-depth coverage of GCP services, use cases, best practices, and hands-on experience tailored specifically for GCP. 
  • Industry-Recognized Trainers- CloudThat has a strong pool of industry-recognized trainers certified by GCP. These trainers bring real-world experience and practical insights into the training sessions, comprehensively understanding how GCP is applied in different industries and scenarios. 
  • Hands-On Learning Approach- CloudThat emphasizes a hands-on learning approach. Learners can access practical labs, real-world projects, and case studies that simulate actual GCP environments. This approach allows learners to apply theoretical knowledge in practical scenarios, enhancing their understanding and skill set. 
  • Customized Learning Paths- CloudThat understands that learners have different levels of expertise and varied learning objectives. We offer customized learning paths, catering to beginners, intermediate learners, and professionals seeking advanced GCP skills. 
  • Interactive Learning Experience- CloudThat's training programs are designed to be interactive and engaging. We utilize various teaching methodologies like live sessions, group discussions, quizzes, and mentorship to keep learners engaged and motivated throughout the course. 
  • Placement Assistance and Career Support- CloudThat often provides placement assistance and career support services. This includes resume building, interview preparation, and connecting learners with job opportunities through our network of industry partners and companies looking for GCP-certified professionals. 
  • Continuous Learning and Updates- CloudThat ensures that our course content is regularly updated to reflect the latest trends, updates, and best practices within the GCP ecosystem. This commitment to keeping the content current enables learners to stay ahead in their GCP knowledge. 
  • Positive Reviews and Testimonials- Reviews and testimonials from past learners can strongly indicate the quality of training provided. You can Check feedback and reviews about our GCP courses that can provide potential learners with insights into the effectiveness and value of the training. 

Learning Objectives of Application Development with Cloud Run

  • Container Fundamentals- Understand the resource model and lifecycle of containers within Google Cloud. 
  • Deployment Strategy- Learn to use Cloud Run and Google Kubernetes Engine (GKE) for different architectural needs. 
  • Secure Access- Authenticate and authorize access to functions and services using service identities. 
  • Data Integration- Connect Cloud Run functions to databases like Firestore and Memorystore. 
  • Performance Optimization- Implement best practices for scaling, traffic splitting, and networking. 

Course Outline for Application Development with Cloud Run Download Course Outline

Lecture Content

  • Evolution from virtual machines to containerized runtimes
  • Defining container images, layers, and Dockerfile design patterns
  • Decoupling application runtimes and isolating software dependencies
  • Open Container Initiative (OCI) specifications and container standardization

Learning Objectives

  • Explain the structural concepts of containerization and filesystem layering
  • Package microservices along with their isolated execution dependencies

Lecture Content

  • Automating container compilation using Google Cloud Build
  • Storing and auditing software components securely in Artifact Registry
  • Implementing image hardening, multi-stage builds, and base image minimalization
  • Vulnerability scanning and supply chain security for containerized workloads

Learning Objectives

  • Build, push, and secure standard container images using Cloud Build and Artifact Registry
  • Design optimized Dockerfiles to minimize risk vectors and target image sizing

Lab Content

  • Building and Securing Container Images

Lecture Content

  • Google Cloud computing choices: Evaluating Cloud Run vs. GKE vs. Compute Engine
  • Serverless concurrency paradigms, execution lifecycles, and scaling to zero
  • Navigating the Cloud Run resource models (Services vs. Jobs execution types)
  • Understanding automated autoscaling mechanics based on CPU utilization and request limits

Learning Objectives

  • Contrast the structural differences, operations, and cost profiles of Cloud Run and GKE
  • Configure autoscaling targets, min/max instances, and concurrent request thresholds

Lecture Content

  • Writing cloud-native containerized applications tuned for serverless environments
  • Handling stateless request processing, ephemeral data systems, and health checks
  • Testing containerized microservices locally using the Cloud Code IDE extensions
  • Deploying service revisions and managing container configuration metrics

Learning Objectives

  • Develop, test, and deploy resilient, stateless microservices directly to Cloud Run
  • Diagnose application startup metrics and configure operational readiness health checks

Lab Content

  • Develop and Test Cloud Run Applications

Lecture Content

  • Deep dive into Google Cloud resource access boundaries and IAM roles
  • Implementing Least Privilege principles using custom Service Identities
  • Distinguishing between developer deployment permissions and runtime application identities
  • Configuring ingress controls: Public unauthenticated vs. Private internal access parameters

Learning Objectives

  • Enforce strict identity boundaries by configuring dedicated service accounts for Cloud Run services
  • Limit service connectivity pathways using fine-grained cloud identity configurations

Lab Content

  • Configure Service Identity and IAM for Cloud Run

Lecture Content

  • Architectural strategies for service-to-service asynchronous communications
  • Connecting Cloud Run natively with Pub/Sub event queues and Cloud Storage buckets
  • Utilizing Serverless VPC Access connectors to safely map into internal VPC resources
  • Constructing orchestrated multi-tier microservice networks with Google Cloud APIs

Learning Objectives

  • Integrate Cloud Run microservices seamlessly with downstream managed cloud infrastructure components
  • Establish secure internal networking pathways from serverless environments into custom VPC nets

Lab Content

  • Integrate Cloud Run with Google Cloud Services

Lecture Content

  • Lightweight serverless compute choices: The evolution of Cloud Functions (2nd gen)
  • Understanding event-driven execution paradigms, pricing models, and stateless functions
  • Navigating trigger categories: HTTP endpoints vs. Eventarc background listeners
  • Setting up local development runtimes, testing frameworks, and deployment CLI commands

Learning Objectives

  • Distinguish when to deploy containerized microservices vs. single-purpose lightweight functions
  • Construct background functions that execute code in response to system event streams

Lab Content

  • Develop, Test, and Deploy Cloud Run Functions

Lecture Content

  • Authenticating external HTTP invocations vs. authorizing background system events
  • Restricting function runtime permissions via distinct execution service accounts
  • Hardening functions by integrating customer-managed encryption keys (CMEK)
  • Ingress and egress network filtering controls for serverless application runtimes

Learning Objectives

  • Enforce granular access management profiles for incoming event ingestion streams
  • Implement advanced security policies to encrypt and protect background compute instances

Lecture Content

  • Connecting serverless code backends to transactional and document cloud databases
  • Storing and mounting sensitive credential parameters safely using Secret Manager
  • Injecting environment variables dynamically into functions without exposing code variables
  • Decoupling structural state management across Cloud Firestore and Cloud Memorystore (Redis)

Learning Objectives

  • Fetch and parse protected database access keys programmatically via Secret Manager
  • Inject serverless function logic natively into document-store databases like Firestore

Lab Content

  • Integrate Cloud Run Functions with Firestore

Lecture Content

  • Mitigating performance latency: Optimization techniques for reducing "cold starts"
  • Designing idempotent functions to safeguard execution flows during retried failures
  • Advanced traffic routing strategies, canary staging, and progressive traffic splitting
  • Concurrency limits, global memory allocation configurations, and operational cost management

Learning Objectives

  • Tune function runtime performance variables to minimize execution overhead and billing costs
  • Architect defensive, idempotent functions that reliably process re-driven event anomalies

Lecture Content

  • Retrospective technical synthesis of core cloud-native serverless concepts
  • Blueprint mapping for production-grade architectures utilizing Run Services and Functions
  • Google-recommended developer checklist for maintaining scalable, secure enterprise workflows

Learning Objectives

  • Synthesize the core capabilities of Cloud Run and Cloud Run Functions to design elastic, decoupled enterprise cloud applications

Certification Details of Application Development with Cloud Run

    CloudThat Course Completion Certificate will be awarded to all learners who complete the training.

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Course ID: 29131

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FAQs for Application Development with Cloud Run

This is a comprehensive 2-day instructor-led course.

Yes, the three core components (Containers, Cloud Run Apps, and Functions) can be delivered as individual sessions.

Students should have basic application development experience and familiarity with command-line tools.

Yes, the course includes 7 hands-on labs and 10 quizzes to ensure practical mastery.

It provides a high-level comparison between Cloud Run and GKE but focuses specifically on Cloud Run.

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