Continuous Integration and Continuous Delivery are two concepts that
come up frequently in modern DevOps. At a high level, continuous
integration (CI) describes the processes and tooling used to ensure
that software changes can be tested and built in an automated fashion.
Continuous delivery (CD) adds to that concept by providing the setup
needed for newly built software releases to be deployed to production or
While logically, CI and CD are distinct processes, practically, they are
often combined into a single step. Many organizations will use the same
tool—such as Jenkins, GitHub Actions, Gitlab CI, or many others—to
build, test, and deploy the new version of their code.
Limitations of combined CI/CD
CI/CD is certainly a viable approach, and it's one we have used many
times in the past at FP Complete. However, we're also aware of some its
limitations. Let's explore some of the weaknesses of this approach.
A combined CI/CD pipeline will end up needing several different
Read access to the source code repository
Push access to the binary artifact repository, e.g., the Docker
Update access to the production hosting, e.g., the Kubernetes
These permissions are typically passed in via secret variables to the CI
system. By combining CI/CD into a single process, we essentially require
that any users with maintainer access to the job get access to all these
abilities. Furthermore, if a nefarious (or faulty) code change is merged
into source code that reveals secret variables from CI, production
cluster tokens may be revealed.
Following the principle of least privilege, reducing a CI system's
access is preferable.
Baking CD into the primary CI job of an application means that any
cluster that wants to run that application needs to modify the
originating CI job. In many cases, this isn't a blocker. There's a
source repository with the application code, and the application runs on
just one cluster in one production environment. Hard-coding information
into the primary CI job about that one cluster and environment feels
But not all software works like this. Providing CI, QA, staging, and
production environments is one common obstacle. Does the CI job update
all these environments on each commit? Is there unique mapping from
different branches to different environments?
Multi-cloud or multi-region deployment take this concept further. If
your application needs to be geolocated, configuring the originating CI
job to update all the different clouds and regions can be a burden.
Continuing this theme is the presence of upstream software. If you're
deploying an open-source application or vendor-provided software, you
likely have no direct control of their CI job. And modifying that job to
trigger a deployment within your cluster is likely not an option — not
to mention a security nightmare.
Cycling cluster credentials
Tying up the story is cluster credentials. As part of normal cluster
maintenance, you will likely rotate credentials for cluster access. This
is a good security practice in general and maybe absolutely required
when performing certain kinds of updates. When you have dozens of
applications on several different CI systems, each with its own set of
cluster credentials hardcoded into CI secret variables, such rotations
Kube360, we decided
to go the route of minimizing the role of Continuous Integration to:
This addresses the four concerns above:
Permissions model: We've reduced the CI system's permissions to
things that do not directly impact what is running on the production
system. The CI system now can read source code and write to the
Docker registry. This latter step can cause issues in production by
overwriting an existing tag with a new image. However, if you deploy
based on SHA256 hashes, you're protected even against this. The CI
system can no longer directly modify what is running in production.
Multi-cluster deployments: The CI system knows nothing about
any clusters. The responsibility to notify the clusters of an
available update is handled separately, as described below.
Upstream tools: We are now modeling our custom-written
proprietary software in the same way we would deploy upstream tools.
A vendor or open-source provider will write software, build it, and
publish a release. We are now shifting the in-house software model
to behave the same way: CI publishes a release, and deployment
responsibility picks up from there.
Cycling cluster credentials: This step is no longer necessary
since the CI system maintains no such credentials.
But it still begs the question: how do we handle Continuous
Deployment in Kube360?
Dedicated in-cluster CD
Kube360 ships with ArgoCD out of the box. ArgoCD provides in-cluster
Continuous Deployment. It relies on a GitOps workflow. Each deployed
application tracks a Git repository, which defines the Kubernetes
manifest files. These manifest files contain a fully declarative
statement of how to deploy an application, including which version of
the Docker image to deploy. This provides centralized definitions of
your software stack and the audibility and provenance of deployments
through Git history.
This has some apparent downsides. Deploying new versions of software is
now a multi-step process, including updating the source code, waiting
for CI, updating the Git repository, and then updating ArgoCD. You must
now maintain multiple copies of manifest files for different clusters
and different environments.
With careful planning, all of these can be overcome. And as you'll see
below, some of these downsides can be a benefit for some industries.
In our recommended setup, we strongly leverage overlays for creating
modifications of application deployments. Instead of duplicating your
manifest files, you take a base set of manifests and apply overlays for
different clusters or different environments. This cuts down on
repetition and helps ensure that your QA and staging environments are
accurately testing what you deploy to production.
Each deployment can choose to either enable or disable auto-sync. With
auto-sync enabled, each push to the manifest file Git repository will
automatically update the code running in production. When disabled, the
central dashboard will indicate which applications are fully
synchronized and lagging the Git repository of manifest files.
Which option you choose depends upon your security and regulatory
concerns. Development environments typically enable auto-sync for ease
of testing. In some cases, auto-sync makes perfect sense for production;
you may want to strongly limit the permissions model around updating a
production deployment and make the final deploy step the responsibility
of a quality auditor.
An advantage of the GitOps workflow is that each update to the
deployment is accompanied by a Git commit reflecting the new version of
the Docker image. A downside is that this requires an explicit action by
an engineer to create this commit. In some cases, it's desirable to
automatically update the manifest repository each time a new Docker
image is available.
To allow for this, FP Complete has developed a tool for automatic
management of these Git repositories, providing fast updates without an
operator's involvement. When paired with auto sync, this can provide for
a fully automated deployment process on each commit to a source
repository. But by keeping this as an optional component, you retain
full flexibility to create a pipeline in line with your goals and
Permissions for modifying your cluster always stay within your cluster.
You no longer need to distribute Kubernetes tokens to external CI
systems. Within the cluster, Kube360 grants ArgoCD access to update
deployments. When deploying to a new cluster, no update of Kubernetes
configuration is needed. Once you copy over Docker registry tokens, you
can read in the Docker images and deploy directly into the local
At FP Complete, we believe it is vital to balance developer productivity
and quality guarantees. One of the best ways to optimize this balance is
to leverage great tools to improve both productivity and quality
simultaneously. With Kube360, we've leveraged best-in-class tooling with
innovative best practices to provide a simple, secure, and productive
build and deploy pipeline. To learn more, check out our free video
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