April 2019 Summaries

We've added new resources to the Learn platform to help users get started with Kubernetes, configure ACLs, integrate with Ambassador, and troubleshoot Consul issues. The Getting Started with Kubernetes track provides step-by-step guides on deploying Consul on Kubernetes, while the ACL Resources section offers guidance on configuring Access Control Lists for production security. We've also streamlined our Troubleshooting guide to make it easier to find Consul-specific guidance. Additionally, we've integrated Ambassador with Consul Connect and made it easily accessible through our Learn platform.

Ambassador, a service mesh API gateway, has introduced native support for the Consul service mesh, enabling organizations to expose any Consul service to the internet using declarative configuration. This integration provides a complete solution for traffic management in hybrid cloud environments, spanning Kubernetes, virtual machines, and bare metal infrastructure. With this architecture, application workloads can be moved anywhere without impacting security or end users, thanks to Consul's centralized management of available endpoints, service configuration, and secrets for TLS encryption. Ambassador serves as a common point of ingress, providing features such as user authentication, API management, and TLS termination, while using Consul for service discovery and end-to-end traffic security. The integration is designed to be stateless by design, relying on Consul and Kubernetes as the single source of truth, enabling simple horizontal scale-out of Ambassador instances.

The Singularity container runtime and image format is being used to simplify the process of moving applications, workloads, and computing environments across a single infrastructure or across hybrid environments. This allows enterprise users to directly access an entire solutions ecosystem that can handle demanding artificial intelligence, machine learning, and other advanced analytic workloads. The integration with Nomad enables data scientists and other users to run analytical workloads that combine the benefits of both systems. With its security features, such as blocking privilege escalation within containers, Singularity provides a platform designed around container mobility, reproducibility, security, and performance.

HashiCorp Terraform 0.12 Beta 2 is now available, bringing major language improvements and new features, including support for many providers such as AWS, Google, Kubernetes, and more, with automatic downloadable initialization via terraform init. The new release also includes updated configuration language documentation and a `terraform 0.12upgrade` command to help users transition from older versions. Although the beta version may still contain bugs, users are encouraged to provide feedback and test the new features in a non-production setting.

Packer v.1.4.0 introduces several notable features, including support for Docker on Windows, allowing users to build Windows containers using the Docker builder. Additionally, recursive user variable interpolation has been improved, enabling more complex template definitions. A new sleep provisioner has also been added, which allows for customizable timeouts and sleep durations. Other improvements include enhancements to shell and windows-shell provisioners, updated VNC port collision detection, and integration with hashicorp/go-getter for file downloads. Notably, backwards-incompatible changes have been made to improve template coherence, but users can utilize a fixer to address these changes. The release also highlights new builders, provisioners, post-processors, and miscellaneous features such as Vault + AWS integration and updated post-processor behavior.

Nomad 0.9 introduces new scheduling features that allow application owners and operators to have more fine-grained control over where their workloads are placed in the cluster, providing additional flexibility in expressing placement preferences and increasing failure tolerance of workloads. The new `spread` stanza allows operators to distribute their workloads in a customized way based on attributes and/or client metadata, while the `affinity` stanza enables operators to express placement preferences for their jobs on particular types of nodes, with scoring factors taking into account matching affinities and other constraints. These features provide more fine-grained control over workload placement and increase failure tolerance, enabling use cases such as spreading instances across multiple data centers or physical racks, targeting specific classes of nodes for specialized workloads, and preferring a specific class of nodes for workloads with specialized requirements.

The `open-source` project `Kubernetes` has reached its first major milestone, with over 15,000 contributors and a community-driven development process. The Kubernetes project was initially created by Google in 2014 as an open-source container orchestration system for automating the deployment, scaling, and management of containerized applications. It has since become one of the most widely used container orchestration systems in the industry, with a large and diverse user base. The project's growth has been driven by its flexibility, scalability, and ability to support a wide range of use cases, from small startups to large enterprises. With over 150,000 stars on GitHub, Kubernetes has become a de facto standard for container orchestration, with many organizations relying on it as the foundation for their cloud-native applications.