Operating containerized infrastructure brings with it a new set of challenges, particularly with instrumenting your containers, evaluating your API endpoint performance, and identifying bad actors in your infrastructure. The Istio service mesh enables instrumentation of APIs without code change and provides service latencies for free.
But how do you actually make sense all that data? With math, that’s how.
Fred Moyer explains how to get a comprehensive understanding of your Kubernetes infrastructure with a little math and an Istio service mesh implementation for your container-based infrastructure. You’ll learn about infrastructure performance and discover how to determine if your services are under- or overprovisioned. Along the way, Fred demonstrates mathematical techniques to ask and answer business queries and walks you through creating RED (rate, errors, and duration) dashboards that provide insight into API performance (which are essential for meeting service level objectives) and implementing cost-effective monitoring at scale with histograms (which preserve metric fidelity and enable statistical analysis).
Fred is a SLOgician at Zendesk. He spends his days thinking about service-level objectives, service-level indicators, error budgets, and how to apply them across Zendesk’s Kubernetes-based infrastructure of services. Fred has almost 20 years of developing production systems for companies such as Turnitin; he honed his observability skills recently as a developer evangelist at Circonus. He likes to write C, Go, Perl, Ruby, etc. Fred has two young kids and can always use more coffee.
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