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How Netflix uses eBPF flow logs at scale for network insight

The Netflix TechBlog

By Alok Tiagi , Hariharan Ananthakrishnan , Ivan Porto Carrero and Keerti Lakshminarayan Netflix has developed a network observability sidecar called Flow Exporter that uses eBPF tracepoints to capture TCP flows at near real time. The Flow Exporter also publishes various operational metrics to Atlas.

Network 325
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From observability to sustainability: Reduce your IT carbon footprint with Dynatrace Carbon Impact

Dynatrace

ESG metrics are increasingly important to investors as they evaluate risk; in turn, these metrics are increasingly important to organizations because they measure and disclose their performance. The app translates utilization metrics, including CPU, memory, disk, and network I/O, into their CO2 equivalent (CO2e).

Energy 191
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Kubernetes vs Docker: What’s the difference?

Dynatrace

Just like shipping containers revolutionized the transportation industry, Docker containers disrupted software. It is a suite of tools for developers to build, share, run and orchestrate containerized apps. Initially developed by Google, it’s now available in many distributions and widely supported by all public cloud vendors.

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

We earned the trust of our engineers by developing empathy for their operational burden and by focusing on providing efficient tracer library integrations in runtime environments. We chose Mantis as our backbone to transport and process large volumes of trace data because we needed a backpressure-aware, scalable stream processing system.

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Forrester TEI™ Study Shows Tasktop Can Deliver a Customer ROI of 496% Over Three Years With a Payback Period of Less Than 3 Months

Tasktop

Reduced reporting and analytics burden for managers, saving managers 2.5 Tasktop Viz comes with ready-to-use connections to a wide portfolio of software development tools. This allowed the interviewees’ organizations to seamlessly integrate their toolchains across departments and teams, generating a consistent set of Flow Metrics.

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Edgar: Solving Mysteries Faster with Observability

The Netflix TechBlog

This difference has substantial technological implications, from the classification of what’s interesting to transport to cost-effective storage (keep an eye out for later Netflix Tech Blog posts addressing these topics). Tracing as a foundation Logs, metrics, and traces are the three pillars of observability.

Latency 296
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Data Movement in Netflix Studio via Data Mesh

The Netflix TechBlog

The paradigm spans across methods, tools, and technologies and is usually defined in contrast to analytical reporting and predictive modeling which are more strategic (vs. Processors with Different Inputs/Outputs Data Mesh allows developers to contribute processors to the platform. tactical) in nature. Iceberg, ElasticSearch, etc).

Big Data 253