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Mesos has come a long way since the early research. But so has all the competition.

I'm biased, of course. I work for Pivotal, we're the lead builders of Cloud Foundry. Our current generation of software can spin up hundreds to thousands of machines without too much fuss. Our next generation[0] is ... better.

And again, this is my bias showing, but I think our design for container workload scheduling is better than Mesos and Kubernetes.

We don't get much buzz on HN because we sell a complete PaaS to F500s. It's not very approachable on a personal level.

[0] http://lattice.cf/




The two things that matter are performance and reliability. Are you able to go into how lattice improves over either Mesos or k8s in these regards?


I was interested in the design decisions, but sure.

Lattice is a selection of Cloud Foundry components, principally the Diego runtime system, Loggregator log streaming system and Gorouter HTTP routing system.

If how software is written matters to you, then you might like the way we work. Cloud Foundry is Pivotal Labs DNA, scaled up. 100% pairing, every new line of code is test-driven.

We dogfood everything by running Pivotal Web Services as a public PaaS, which is always within a week or two of HEAD across the board.

Where we follow is that Kubernetes is extracted from real experience and Mesos has a head start on implementation.

In terms of design, I like ours best. Tasks and long-running processes are distributed using an auction mechanism, which means that there's much less global resource-status chatter required to make the scheme work. Diego is "demand-driven", meaning activity occurs when new demands are made. Mesos is "supply-driven", meaning state-affecting activity occurs when resources become available. They both solve a critical problem by pushing intelligence out to the edges, but to different edges.

I am much less familiar with Kubernetes, so I will avoid being any wronger than usual.




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