We’re very happy to announce that meshcloud is the first corporate sponsor of the Dhall Language Project via open collective. In this post I want to explain how we came to use Dhall at meshcloud, what challenges it solves for us and why we hope it will play a role in enabling software projects to more easily adapt to multi-cloud environments.
Enabling DevOps at scale
At the beginning of this year, we realized we had a challenge scaling configuration and operations of our software for customers. meshcloud helps enterprises become cloud-native organizations by enabling "DevOps at scale". Our tool helps hundreds or thousands of DevOps teams in an enterprise to provision and manage cloud environments like AWS Accounts or Azure Subscriptions for their projects while ensuring they are secured and monitored to the organization’s standards.
Enabling DevOps teams with the shortest "time to cloud" possible involves the whole organization. Our product serves DevOps teams, IT Governance, Controlling and IT Management in large enterprises. That means meshcloud is an integration solution for a lot of things, so we need to be highly configurable.
Because we also manage private clouds (OpenStack, Cloud Foundry, OpenShift etc.) we often run on-premises and operate our software as a managed service. This presents unique challenges for our SRE team. Not only do we need to maintain and evolve configuration for our growing number of customers, but we also need to support deploying our own software on different infrastructures like OpenStack, AWS or Azure[1].
At the end of the day, this boils down to having good and scalable configuration management. After going through various stages of slinging around YAML with ever more advanced tricks, we realized we needed a more fundamental solution to really crack this challenge.
Configuration management at scale – powered by dhall
The Dhall configuration language solves exactly this problem. It\’s a programmable configuration language that was built to express configuration – and just that. Dhall is decidedly not turing complete. It\’s functional nature makes configuration easy to compose from a set of well-defined operations and ensures that configuration stays consistent.
Using Dhall allows us to compile and type check[2] all our configuration for all our customers before rolling things out. We use Dhall to compile everything we need to configure and deploy our software for a customer: Terraform, Ansible, Kubernetes templates, Spring Boot Config. We even use Dhall to automatically generate Concourse CI pipelines for continuous delivery of our product to customers.
Since adopting Dhall earlier this year, we measurably reduced our deployment defect rate. We feel more confident about configuration changes and can safely express configuration that affects multiple services in our software.
Empowering a Multi-Cloud Ecosystem
We believe that open-source software and open-source cloud platforms are crucial for enabling organizations to avoid vendor lock-in. Now that mature tools like Kubernetes exist and can do the heavy lifting, enabling portability between has become a configuration management challenge.
What we found especially interesting about Dhall is that it\’s not just an "incremental" innovation atop of existing configuration languages like template generators, but instead looks at the problem from a new angle and tries to solve it at a more fundamental level. This is something we can relate to very well as we\’re trying to solve multi-cloud management using an organization as code (like infrastructure as code) approach.
That’s why we\’re happy to see Dhall innovating in this space and reached out to the Dhall community to explore ways we can support the project. We hope that providing a steady financial contribution will allow the community to further evolve the language, tooling and its ecosystem.
Footnotes:
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[1]: In this way meshcloud is not only a multi-cloud management software but is also a multi-cloud enabled software itself.
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[2]: Dhall purists will want to point out that expressions are not compiled, instead they\’re normalized.