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GitOps and the Millefeuille dilemma

28 June 2020

By Yann Albou et Sébastien Féré.

In this article, co-written with Sébastien Féré, we describe what GitOps is, its impacts in the company and an example of implementation.

For french speakers, we did a talk at DevOpsDays Geneva 2020, presenting GitOps as a way to manage enterprise K8s and virtual machines:

GitOps, from its inception in August 2017 by Alexis Richardson, CEO @ WeaveWorks, is described as 4 pillars:

  1. Declarative The entire system is described declaratively
  2. Git as Single Source of Truth Declarative changes let you think of changes as transactions
  3. Kubernetes Operator Approved changes to the desired state are automatically applied to the system
  4. Continuous Observability Software agents ensure correctness and alert on divergence

GitOps – Push or Pull ?

Since the inception of DevOps in 2010, push and pull deployments options have always been on the table. However for good or bad reasons – the idea of control being the most prominent – push-based deployment remains the favorite way to go in most companies.

Pull-based approach – the GitOps original one

source: based on the diagram from gitops.tech

With the pull-based approach, the Operator from inside the Kubernetes cluster is in charge of listening new events from the Git repository (containing the deployment manifest) and from the Docker image registry. When a new commit or a new image is produced, the operator compares the current state with the desired state of the deployment and performs possible modifications to match the desired state.

If you omit automated writes that can be easily performed by the CI pipelines, the Operator only requires read access to the Image Registry and the GitOps repository.

Being inside the cluster definitely improves the security because you are inside the "trusted zone" – no need for any credential with high-level permissions to access the cluster. This also improve the addressability – no need to specify the URL to target the right cluster, which might avoid deployment mistakes: which company never targeted the wrong environment during a deployment?!

Push-based approach – GitOps the half-way

source: based on the diagram from gitops.tech

With the well-known and most used push-based approach, the deployment is performed from outside the Kubernetes cluster. As it can achieve the same kind of results about the desired state of the system, it does not offer the feedback loop and the observability provided by the Operator. From a security perspective, the pull-based approach and its Operator are undoubtedly better than credentials with top-level permissions…

As introduced earlier, the push-based approach is preferred in most companies and this is not about to change… Kubernetes and Cloud-native are huge pieces of the Digital Transformation roadmaps, but companies also have legacy infrastructures. While the apps move to Kubernetes, databases or Windows workloads for instance are likely to stay on Virtual Machines for a couple of months – in this context and in combination with Helm, DevOps tools like Ansible remain very convenient.

While CI/CD pipelines are often described as a linear process, the GitOps approach also stands that CI and CD can be separated as two different processes in both pull / push approaches. In some circumstances, it is interesting to think about a set of Microservices – or Product – as a single unit of deployment. With GitOps, we can now manage deployments in different clusters depending on the git branch in a full declarative way!

GitOps in the Enterprise

As part of their Digital Transformation, many companies embrace DevOps methodologies and new technologies such as Containers, Kubernetes and Cloud… The first major milestone is undoubtably the go-live in a Production environment of a Business Application using Git as a Single Source of Truth to describe the Kubernetes resources such as:

  • Namespaces
  • Deployments
  • Services
  • Volumes & PersistentVolumes
  • Roles & RoleBindings
  • Network Policies
  • Quotas, Limits,

With Kubernetes, all these resources are part of the same unit of deployment (or two – one for global resources and namespaces, one for namespace-scoped resources) and they will coexist in the same Git repository…

The ownership and responsibility of the current or the equivalent of the Kubernetes ressources are today distributed throughout IT departments of the company – this is what we call the "millefeuille"…

The millefeuille

source: based on the interpretation of the millefeuille by Jean-François Piège

Instead of a classic representation of IT services / departments as silos, let’s represent them as the independent layers of the famous French pastry called "millefeuille". In most companies, existing policies, tooling and governance based on ITIL practices make each IT department having its own tools and obviously source of truth from the department perspective.

For instance, the database team generally has an inventory of databases, whereas the network team has a tool to manage network devices and all associated rules/policies without any connection between these two datastores.

With the "millefeuille", each layer is independent and represents an IT department that has its own domain and its own responsibility, leading to partial sources of truth within teams. In the end, a entire deployment is a succession of independent tickets/queues, manual actions, … Troubleshooting an issue in Production often requires to rebuild the knowledge for the Product under investigation.

Thanks to the concept of "context wagon", the story and issues about troubleshooting were greatly depicted in the presentation Operations: The Last Mile Problem For DevOps by Damon Edwards during the DevOps Enterprise Summit London 2018.

While these issues are more DevOps than pure GitOps concerns, the GitOps way of thinking will suffer the same organizational burden and demons of the past. In this context, Kubernetes and GitOps are just another lighthouse telling companies why and how to change their approach to Declarative infrastructure provisioning, environment and change management, … but also to adopt of Product-centric view, that is also largely promoted by Agile methodologies.

However, there is a huge difference:

  • Agile and DevOps promote a methodology, a way of thinking that is too easily remodelled by companies or people that don’t want to embrace the approach.
  • Kubernetes resources and GitOps offer a tool – a Git repository – to centralize all the configuration of a Product. A tool involves UI, CLI, API that can’t be twisted as easily as ideas and principles…

There are a lot of options to make each team part of the "GitOps" deployment process, using Git collaboration tools such as Pull-Request / Merge-Request reviews and approvals. For instance, the security and network teams may be part of the review and approval of pull requests related to NetworkPolicy resources. For a finer-grained process, the CodeOwner plugin for Git can help in defining individuals or teams responsible of specific files in a repository.

GitOps and Delivery Pipeline

Best of both worlds

Kubernetes deployments are always described as a single transaction with the API Server through the kubectl CLI. However, either in the Cloud or on-premise, enterprise-grade deployments typically involve external APIs, endpoints or engines to configure.

Considering the various system to configure in addition to the Kubernetes workloads, the diagram below represents a serious option to implement the CD pipeline:

A GitOps push-based approach has been used with a combination of Ansible and Helm to deploy applications in the different Kubernetes environments and on legacy infrastructure.

The CI pipeline produces the Docker images and publishes them into a Container Registry. This is not the purpose of this blog post to describe how to build enterprise-ready docker images or to review the organization of Docker registries but keep in mind it is also a very important part of the DevSecOps approach, to bring automation and security all along the CI/CD pipeline.

Helm was used at the beginning but in the context of some projects we decided to remove it.

Not because of the security: Helm v2 with Tiller was not a security issue — as we can hear very often — thanks to the Tillerless approach. Thus, Helm v3 doesn’t use Tiller anymore.

Lightweight and overall simplicity

While Helm is very popular in the Kubernetes ecosystem, we decided not to use it in the context of that story, but why?

  • Packaging time and management – not a huge issue, but Helm charts need to be packaged, which adds an additional CI pipeline.
  • Umbrella charts – one thing we wanted to achieve was the ability to create basic charts (springboot, nodejs, Angular, PostgreSQL, … charts) and global charts to compose with the basic ones. This is quite difficult to achieve because of the way Helm handles configuration.
  • Not only for Kubernetes – Helm is a tool dedicated to Kubernetes environments and no one would use it outside of that context… Then you need a second configuration tool to manage configurations and deployments outside of Kubernetes.
  • Duplicate features – Helm can manage the lifecycle of your application and provide versioning of your application, do rollbacks, … With GitOps, the lifecycle is managed by the state of the Git repository, which also offers many more capabilities such as traceability, auditing, diff, …
  • 1 is better than 2 – when it comes to adoption, learning curve, maintenance, etc. less is better than more. While slightly different, Helm and Ansible are in the end two configuration and deployment tools with – for instance – two different approaches to templating (Go templating vs. Jinja2).

Helm or Kubernetes Operators are definitely perfect matches for software editors to distribute their packaged offerings and give their users/customers an easy and standard way to configure and deploy the solution.

While Ansible is perhaps not the best option for Kubernetes deployments (k8s_module), it makes really sense in the Enterprise story of GitOps & pushed-based deployments on Virtual Machine and Kubernetes clusters.

As any design and decisions, we bring on the table opinions that are valid in space – our Enterprise context – and time – before the arrival of Helm 3.

Enterprise wants standards

Just like Helm, Ansible has the capability to create templates of Kubernetes resources… but why creating templates?

Each company designing software has a set of common ground practices, tooling and frameworks:

Some people hate frameworks or scripts that hide complexity behind the so-called "black magic". However, it is necessary to bring standards in the enterprise for:

  • Reusability
  • Conventions, including labelling
  • Security
  • Default Limits / Quotas
  • Default Network segregation
  • Default config

Whether with Helm or Ansible, one should decide the degree of liberty when it comes to templating… what do you expose? what do you allow to be overridden without breaking enterprise or security rules?

These questions would find their answers in a tradeoff between all the DevSecOps stakeholders. However, as a few rules of thumb:

  • Keep templates simple (KISS principle) – identify usages and make different templates (for instance, our springboot and angular Kubernetes templates are more than 90% identical)
  • Don’t reinvent the wheel – keep templates as close as possible to the Kubernetes resources, APIs and syntax

Continuously delivering a Product

A lot of companies have designed micro-services to answer business needs with more or less success to the extend that some folks now come up with idea to not use microservices

Monoliths are the future because the problem people are trying to solve with microservices doesn’t really line up with reality. Kelsey Hightower

That said, one key ability – to deploy microservices completely independent of one another – may not be fully respected in the Enterprise context of microservices deployment. Adding to the mix non-frequent releases and a complex release process end up with deploying microservices as a monolith stack – which seems to be a complete anti-pattern at first glance, but can make sense in a declarative Product-centric approach…

With the Kubernetes / GitOps fully declarative approach, it is interesting to maintain a complete and consistent Application Manifest of the Product by leveraging the Enterprise templates described in the previous section.

Either with Ansible or Kubernetes idempotent design, a new deployment of the entire Product only apply changes by comparing the desired GitOps state and the current system state.

The GitOps approach enforces a declarative, complete, versioned and consistent Manifest of the Product, which would delight any Release / Environment Manager.


The journey to Kubernetes tends be long and tedious as it involves many changes including Cloud-Native Applications, CI/CD toolchain, Infrastructure and Environment provisioning, knowledge about containers and orchestration, operational processes, etc. But any journey starts with a first step in the right direction!

The declarative approach — brought by the DevOps movement and enforced by Kubernetes & GitOps — brings a lot of power using Git as the Source of Truth and integrate quite easily in the Enterprise with dozens of applications and IT environments. The story might be seen as a half-way (push-based) GitOps approach — but is the glass half full or half empty?

All these changes shake up more than ever the established assumptions, the existing tooling, the organizational structure and people. Many challenges and solutions have identified during our journey in which security and automation are at the heart.

A few topics have been left aside for a larger consideration than just a section of this article:

  • Cloud Native Application design
  • Best practices for securing Dockerfiles
  • Git branching model for GitOps repositories
  • Secure the delivery and the usage of public packages
  • Secure the delivery of internal Docker images thanks to promotion
  • Shift-Left practices and tooling for the CI/CD pipeline
  • Continuous Integration of infrastructure pieces, including Kubernetes clusters
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