Remove the-network-needs-to-be-observable-part-2-network-telemetry-sources
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The Network Also Needs to be Observable, Part 2: Network Telemetry Sources

Kentik

In part 1 of this series , I talked about the importance of network observability as our customers define it — using advances in data platforms and machine learning to supply answers to critical questions and enable teams to take critical action to keep application traffic flowing. Introduction.

Network 128
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The Network Also Needs to be Observable, Part 3: Network Telemetry Types

Kentik

In part 2 of this series, I talked about the range of network devices and observation points that generate telemetry data. Over time, this range has expanded, and networks are more diverse than ever. In this blog, I discuss the telemetry data itself. Telemetry Types. Traffic Telemetry.

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KubeCon EU 2019: Top 10 Takeaways

Daniel Bryant

Together, we were part of six talks at KubeCon, staffed a packed booth with amazing T-shirts (if I do say so myself!), As there was so much goodness on offer at KubeCon EU, I’ve tried to summarise some of my key observations in this blog post. spoke to dozens of community members, and attended some fantastic talks.

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The Future of Ops Is Platform Engineering

Honeycomb

Either you can 1) go deep on infrastructure by joining a company that does infrastructure as a service, or 2) go broad on operability by joining a company to help them do as little infrastructure as possible. Two years ago I wrote a piece in The New Stack about the Future of Ops Careers. That second category I was describing now has a name.

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Why and How to Track Connectivity Costs

Kentik

Network Interconnection: Part 2 of our new “Building and Operating Networks” series. Previously on Network Interconnection…”. This article is the second in a series around building and operating networks. An eyeball network is an ISP with residential subscribers at the content consuming edge of the internet.

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How Netflix Scales its API with GraphQL Federation (Part 2)

Netflix Tech

In this post, we shift our attention to what is needed to run a federated GraphQL platform successfully?—?from Once we achieved broad alignment on the idea, we needed to ensure that adoption was seamless. from our journey implementing it to lessons learned. Nevertheless, teams started to jump into the graph in droves.