This course features a combination of lectures, design activities, and hands-on labs to show participants how to use proven design patterns on Google Cloud to build highly reliable and efficient solutions and operate deployments that are highly available and cost-effective.
- Define application requirements and express them objectively as KPIs, SLO’s and SLI’s
- Decompose application requirements to find the right microservice boundaries
- Leverage Google Cloud developer tools to set up modern, automated deployment pipelines
- Choose the appropriate Google Cloud Storage services based on application equirements
- Architect cloud and hybrid networks
- Monitor service level objectives and costs using Stackdriver tools
Module 1: Defining the Service
- Write qualitative requirements with user stories, quantitative requirements using key performance indicators (KPIs) and Evaluate KPIs using SLOs and SLIs.
Module 2: Microservice Design and Architecture
- Decompose monolithic applications into microservices and recognize appropriate microservice boundaries.
- Implement services using 12-factor best practices and Build loosely coupled
Module 3: DevOps Automation
- Automate service deployment using CI/CD pipelines and builds Leverage Cloud Source Repositories for source and version control.
- Create infrastructure with code using Deployment Manager and Terraform.
Module 4: Choosing Storage Solutions
- Store binary data with Cloud Storage, NoSQL data using Firestore and Cloud Bigtable.
- Cache data for fast access using Memorystore.
- Build a data warehouse using BigQuery.
Module 5: Google Cloud and Hybrid Network Architecture
- Design VPC networks
- Configure global and regional load
- Leverage Cloud CDN to provide lower latency and decrease network egress.
- Create hybrid networks between Google Cloud and on-premises data centers
Module 6: Deploying Applications to Google Cloud
- Choose the appropriate Google Cloud deployment service for your applications.
- Configure scalable, resilient infrastructure using Instance Templates and Groups.
- Orchestrate microservice deployments using Kubernetes and GKE.
- Leverage App Engine for a completely automated platform as a service (PaaS).
- Create serverless applications
Module 7: Designing Reliable Systems
- Implement fault-tolerant systems by avoiding single points of failure, correlated failures, and cascading failures.
- Design resilient data storage with lazy deletion.
- Analyze disaster scenarios and plan for disaster recovery using cost/risk analysis.
Module 8: Security
- Leverage Cloud Security Command Center to help identify vulnerabilities.
- Secure people using IAM roles, Identity-Aware Proxy, and Identity Platform.
- Mitigate DDoS attacks by leveraging Cloud DNS and Cloud Armor.
Module 9: Maintenance and Monitoring
- Forecast, monitor, and optimize service cost Use Uptime Checks to determine service availability.
Date & Time
Date: 4, 11 Jun 2022 (Sat)
Time: 09:30 – 17:00 (Total 12 training hours)
Cantonese, supplemented with English terminology
HK$8,100 (May apply up to HK$5,400 subsidy)
*Maximum saving, with the final grant subjects to approval.
- This course was created for those who have already completed the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine course or have equivalent experience.
- Participants should have basic proficiency with command-line tools and systems operations experience, including deploying and managing applications, either on-premises or in a public cloud environment.
Who Should Attend?
- Cloud Solutions Architects, Site Reliability Engineers, Systems Operations professionals, DevOps Engineers, IT managers
- Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform