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In today's dynamic world of software development and system operations, making informed decisions and developing effective strategies rely heavily on data. The OODA loop, developed by military strategist John Boyd, consists of a recurring cycle: Observe, Orient, Decide and Act. This is then followed by a Feedback stage (not represented in the OODA acronym for some reason) before the cycle repeats itself, allowing for continuous optimization.
Although microservices and cloud architectures are the new norm for modern applications, cloud cost optimization could run high in observability. High costs are largely due to the number of components involved in cloud architectures. According to Cloud Data Insights in a recent report, around 71% of IT companies say that cloud observability logs are growing at an alarming rate— a driving factor for rising observability costs.
This blog post was co-authored by Igor Shvartser, Senior Technical Product Manager at Amazon Timestream, and Michael Mandrus, Senior Software Engineer at Grafana Labs. Grafana Labs Senior Software Engineers Stephanie Hingtgen and Kevin Minehart also helped with the content.