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Why We Care About FIPS (And You Should Too)

We are very pleased to announce that we have received Federal Information Processing Standards (FIPS) Validation (CMVP Cert #3702) for the D2iQ Kubernetes Platform (DKP). With FIPS validation, U.S. public sector organizations can accelerate adoption of the D2iQ Kubernetes Platform to more quickly and securely build and deploy cloud native applications and services.

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How to Reduce Overhead and Redundant Efforts in Multi-Cluster Management

Innovation. Scale. Power. These are just a few of the words used to describe the explosive impact that Kubernetes is having on the organizations leveraging it for their innovation efforts. Kubernetes gives organizations the ability to run Kubernetes clusters at scale across different cloud infrastructures and distributions. But as the number of clusters and workloads grow, it can be increasingly difficult to manage and create consistency across your organization’s digital footprint.

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Kubernetes Governance: Balancing the Needs of Everyone on Your Team

The problem with a majority of governance models is that they aren’t continuous. As development teams adopt cloud native technologies and evolve to more agile methods, such as continuous flow and continuous iteration, they are up against decades of policy that assume an older model and don’t fit into a month-long sprint. While governance models need to be restructured, if they’re too restrictive, it can discourage developers and prevent innovation.

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3 Ways Cluster Sprawl Creates Significant Waste and Risk For Your Organization

As various teams within your organization are discovering new ways to leverage Kubernetes, they’re adopting a growing number of clusters to support their project efforts. Unfortunately, this is where many of the challenges begin. While managing one Kubernetes cluster is not trivial, trying to manage multiple Kubernetes clusters across multiple environments becomes exponentially more difficult.

d2iq

Stabilizing Marathon: Part III

So far we covered team culture which amplifies our code culture and design. It was kind of abstract so far and you’ll be forgiven if you skipped right a way to this part. I will cover our test and release pipeline, the thing that probably has had the biggest impact on Marathon’s stability. The pipeline enabled us to discover issues before our users did. I will first give an overview of the pipeline stages and dive deep into the Loop. You will soon see what I meant by that.

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Stabilizing Marathon: Part II

Part I covered our team culture which applies to many different types of work and teams. This part will cover our software engineering best practices that help us stabilize Marathon. Marathon is written in Scala and makes heavy use of Akka Actors and Streams. I probably don’t have to mention that Scala’s type system and its immutable data structures avoid a lot of bugs before we even run unit tests.

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Stabilizing Marathon: Part I

This is a review of the last three years that we spent stabilizing Marathon. Marathon is the central workload scheduler in DC/OS. Most of the time when you launch an app or a service on DC/OS, it is Marathon that starts it on top of Apache Mesos. Mesos manages the compute and storage resources and Marathon orchestrates the workload. We sometimes dub it the “init.d of DC/OS”. Being such an integral part of DC/OS, we must ensure that it keeps functioning.