FinOps Training

FinOps training helps engineering teams understand the financial implications of their technical decisions and helps improve collaboration with finance. Finitizer provides several formal and highly customized training courses for your team.

Our training program currently includes the following courses – Google Cloud FinOps Fundamentals, Google Cloud Big Query Optimization and Google Cloud  Kubernetes and CPU  Optimization.

Google Cloud FinOps Fundamentals

This course covers all the fundamental aspects of cloud financial management and includes all the essential technical elements required to implement FinOps practices on the Google Cloud Platform (GCP).  

  • Understand why FinOps is a cultural practice and the most efficient techniques for teams to manage their cloud costs
  • Learn the tools and best practices needed to manage costs in Google Cloud
  • End to end architecture to aggregate billing data and usage data to Big Query
  • Plan and optimize committed use discounts (CUDS) and other discounts needed
  • How to set up notifications and budgets to alert your team about potential issues
  • Identify which services are driving up your cloud expenses and learn how to reduce those costs.

Google Cloud Big Query Optimization

Implementing best practices to optimize SQL access in BigQuery is crucial. It ensures that queries run quickly and efficiently, even as your data grows. Additionally, optimizing queries reduces costs and minimizes failures, as optimized queries consume fewer resources and perform better. Some examples of optimizations covered are:

  • Eliminate unnecessary Common Table Expressions (CTEs)
  • Avoid Anti-SQL Patterns SELECT * (Wildcard), Excessive Wildcard Tables, Not Filtering Early, Avoiding Explicit JOINs and Ignoring Partitioned Tables
  • Use materialized views to take advantage of query rewriting, which helps eliminate duplicate query processing
  • Introduce BI Engine Caching
  • Limit query costs by restricting the number of bytes charged
  • Use clustered or partitioned tables
  • Use Materialized Views
  • Convert JSON strings into JSON types to optimize CPU usage in Big Query

Google Cloud  GKE / CPU  Optimization

Managing utilization cost for containers is critical optimizing cost. With this training identify sources of wasted cost in container environments, how to build in observability to track cost, and how to handle idle and shared elements.

  • Ensure that Kubernetes nodes are appropriately sized to match CPU requirements for workloads
  • Implement Horizontal Pod Autoscaling to automatically scale the number of replicas of your application based on CPU utilization
  • Implement Vertical Pod Autoscaling to adjust the CPU and memory requests for pods based on their actual resource usage.
  • Set resource requests and limits for containers appropriately
  • Use Kubernetes pod scheduling features such as node affinity and to optimize workload
  • If workloads can tolerate interruptions, consider using preemptible VMs in GKE to take advantage of discounted pricing
  • Enable Cluster Autoscaler to automatically resize your GKE cluster based on resource utilization.

 

Cost Optimization Hackathons

Create cost saving hackathons to optimize workloads and drive cost savings. Solicit ideas and raise awareness among teams about the importance of managing resources efficiently. 

Scroll to Top