Reconciling Kubernetes cost estimates with CUR / FOCUS billing data
https://github.com/tanrikuluozlem/burn
#HackerNews #Kubernetes #CostManagement #CloudBilling #DevOps #OpenSource
Reconciling Kubernetes cost estimates with CUR / FOCUS billing data
https://github.com/tanrikuluozlem/burn
#HackerNews #Kubernetes #CostManagement #CloudBilling #DevOps #OpenSource
Autodesk Tightens Grip on Construction Data with API Overhaul
Autodesk's Cost API update adds new features for contract management and data control. See how it affects construction project finances and developer access.
#AutodeskAPI, #ConstructionTech, #CostManagement, #APIUpdate, #DeveloperTools
https://newsletter.tf/autodesk-api-construction-cost-data-update/
Autodesk has added 11 new timestamp fields to its Cost API, allowing for much more detailed tracking of construction contract lifecycles. This is a significant increase in data granularity for developers.
#AutodeskAPI, #ConstructionTech, #CostManagement, #APIUpdate, #DeveloperTools
https://newsletter.tf/autodesk-api-construction-cost-data-update/
Harnessing Amazon Kinesis in Machine Learning and Artificial Intelligence
Amazon Kinesis, a suite of services offered by AWS, allows the collection, processing, and analysis of real-time streaming data, proving integral to advances in machine learning and artificial intelligence. The services support real-time ingestions, predictions, anomaly detection, personalized user experiences, predictive maintenance, fraud detection, and natural language processing. The tool's scalability, data quality, cost management, and security presents challenges, which can be mitigated with proper configuration, data validation, and robust monitoring.LLM Cost Management
Say goodbye to surprise bills: LLMCap helps you stay within budget
I caught up recently with #groundcover CEO Shahar Azulay to discuss the shifting requirements – and growing role -- for #observability tools in #AI development. From his point of view, #o11y has evolved from a post-production downtime prevention system to "the source of truth for everything from code creation to shipping and testing code, remediation and production."
In today’s episode, we’ll cover…
-- Coping with a further influx of observability data from #AIagents
-- Observability for #costmanagement
-- Data collection for AI agent workflows using #eBPF
-- Groundcover's #AIobservability roadmap
And more!
Watch on YouTube: https://youtu.be/wjYj7gskPJA

When do you actually bump up your Claude usage tier?
For me: I treat extra credits like a buffer for unexpected scope—not justification to overbuild. But I've seen people front-load heavy usage during dev, then coast on less during maintenance. Feels backwards to me, but maybe I'm missing something.
How do you decide when it's worth the jump?