The Cloud Pod

223: Get an AWS Spin on Savings with Cost Optimization Flywheel


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Welcome episode 223 of The CloudPod Podcast! It’s a full house – Justin, Matt, Ryan, and Jonathan are all here this week to discuss all the cloud news you need. This week, cost optimization is the big one, with a deep dive on the newest AWS blog. Additionally, we’ve got updates to BigQuery, Google’s Health Service, managed services for Prometheus, and more.
Titles we almost went with this week:
  • I swear to you Mr. Compliance Man, Mutator is not as bad as it sounds
  • Oracle Cloud customer  – or how we let Oracle Audit us internally at will 
  • We are all confused by the lack of AWS news
  • The CloudPod copies other Podcast’s Features
  • Get AWS spin on savings with Cost Optimization Flywheel 
  • A big thanks to this week’s sponsor:
    Foghorn Consulting provides top-notch cloud and DevOps engineers to the world’s most innovative companies. Initiatives stalled because you have trouble hiring?  Foghorn can be burning down your DevOps and Cloud backlogs as soon as next week.
    General News this Week:
    AWS

    No AWS news – so that should tell you we’re DEFINITELY getting close to announcement season. 

    GCP

    01:35 Introducing new SQL functions to manipulate your JSON data in BigQuery 

    • Enterprises are generating data at an exponential rate, spanning traditional structured transactional data, semi-structured like JSON and unstructured data like images and audio. 
    • Beyond the scale, the divergent types present processing challenges for developers, sometimes requiring a separate processing flow for each. 
    • BigQuery supported semi structured JSON at launch eliminating the need for processing and providing schema flexibility, intuitive querying and the scalability benefits afforded to structured data. 
    • Google is now releasing new sql functions for Bigquery JSON, extending the power and flexibility of their core JSON support. These new functions make it easier to extract and construct JSON data and perform complex data analysis. 
      • Convert JSON values into primitive types (INT64, FLOAT64, BOOL and STRING)
        • Is anyone else insulted that STRING is considered primitive?  
        • easier and more flexible way with new JSON LAX functions
        • Easily update and modify existing JSON values in BigQuery with new JSON Mutator functions.  
        • Construct JSON objects and JSON arrays with SQL in BigQuery with new JSON Constructor functions
        • 03:58 Justin – “Well, you only know that a NoSQL solution makes it once it gets a SQL interface. That’s how you know it’s truly become web scale.”

          06:25 Introducing Personalized Service Healt

          ...more
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          The Cloud PodBy Justin Brodley, Jonathan Baker, Ryan Lucas and Matthew Kohn

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