IN-COMPANY TRAINING PROGRAMS
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This two-day instructor-led class equips you to build highly reliable and efficient solutions on Google Cloud Platform. It is a continuation of the Architecting with Google Cloud Platform: Infrastructure course and assumes hands-on experience with the technologies covered in that course. Through a combination of presentations, demos, and hands-on labs, you will learn to design GCP deployments that are highly reliable and secure; and how to operate GCP deployments in a highly available and cost-effective manner.
This training is for you if…
- Completed Architecting with Google Compute Engine, Architecting with Google Kubernetes, or have equivalent experience
- Basic proficiency with command-line tools and Linux operating system environments
- Systems operations experience, including deploying and managing applications, either on-premises or in a public cloud environment
This training is not for you if…
- No system operations experience
- Not completed Architecting with Google Compute Engine, Architecting with Google Kubernetes
Clients we've helped
What you'll learn
- Architect cloud and hybrid networks
- Implement reliable, scalable, resilient applications balancing key performance metrics with cost
- Choose the right Google Cloud deployment services for your applications
- Secure cloud applications, data, and infrastructure
- Monitor service level objectives and costs using Google Cloud tools
- Apply a tool set of questions, techniques, and design considerations
- Define application requirements and express them objectively as KPIs, SLOs and SLIs
- Decompose application requirements to find the right microservice boundaries
- Leverage Google Cloud developer tools to set up modern, automated deployment pipelines
- Choose the appropriate Cloud Storage services based on application requirements
- Module 1: Defining the Service
- Module 2: Microservice Design and Architecture
- Module 3: DevOps Automation
- Module 4: Choosing Storage Solutions
- Module 5: Google Cloud and Hybrid Network Architecture
- Module 6: Deploying Applications to Google Cloud
- Module 7: Designing Reliable Systems
- Module 8: Security
- Module 9: Maintenance and Monitoring
- Design for high availability, scalability, and maintainability
- Assess tradeoffs and make sound choices among Google Cloud Platform products
- Integrate on-premises and cloud resources
- Identify ways to optimize resources and minimize cost
- Implement processes that minimize downtime, such as monitoring and alarming, unit and integration testing, production resilience testing, and incident post-mortem analysis
- Implement policies that minimize security risks, such as auditing, separation of duties and least privilege
- Implement technologies and processes that assure business continuity in the event of a disaster
Google Cloud Authorized Trainer Google Cloud
Martijn van de GriftCloud Consultant
Martijn is specialised creating solutions using GCP and AWS. He has a strong software engineering background and host most relevant technical certifications for both clouds.
Martijn has a great passion for IT and likes to work with the latest technologies. He uses his experience to help clients become successful with Cloud technology.He loves to share his passion during training and webinars. Martijn is an authorized instructor for both GCP and AWS, and has an online course on O’Reilly’s Training Platform
Structured, to-the-point, good combination of theory and practical examples, very knowledgeable trainer who can explain concepts very well
It was a hands-on and tangible course. We could apply what we learned in a matter of minutes. The trainer did a great job of answering ad-hoc questions that complemented the material. We appreciated the fact that we could apply what we were taught directly to our company.
I liked every aspect of this training and would like to thank the trainers. They did an excellent job of explaining how to use Spark for data science. This is the fourth GoDataDriven training I’ve followed. All were great, but this was the best one so far.
Climbing a steep Python and Machine Learning curve in three days. This would have taken me months on my own.