Kubernetes Support Services

About Kubernetes

Kubernetes is an open-source container orchestration platform that automates the deployment, management, scaling, and operation of containerized applications.

It helps efficiently orchestrate workloads across a cluster of machines, ensuring high availability, scalability, and resource optimization.

Key components include the control plane (API server, scheduler, controller manager) and nodes (master and worker), which work together to maintain a desired application state defined by users.

Struggling with Kubernetes cluster management?

Fabian Dechent has optimized container orchestration for the most complex cloud-native environments in production - let's solve yours.

Common challenges with Kubernetes

Organizations adopting Kubernetes often encounter several critical implementation hurdles that can impact operational efficiency and ROI. These challenges require specialized expertise to navigate effectively, particularly for enterprises seeking to leverage container orchestration at scale. The following pain points represent the most significant barriers businesses face when implementing and maintaining Kubernetes environments in production.

Switching from legacy systems to Kubernetes
Deploying new software to a Kubernetes cluster

Implementing demand based scaling of deployments
Setting up monitoring and tracing
Troubleshooting deployments
Implementing security best practices

dida services

dida offers comprehensive Kubernetes expertise to address your organization's container orchestration needs. Our enterprise-grade services span the entire implementation lifecycle, from initial cluster setup to ongoing optimization and integration, ensuring your business achieves maximum value from Kubernetes technology.

I. dida can set up a cluster for clients transitioning to Kubernetes as a deployment solution

II. dida can deploy new solutions into existing clusters

III. dida can optimize deployments with respect to scaling and cost factors

IV. dida can support managing resources with Helm/Kustomize

V. dida can integrate deployments into CD pipelines and/or build them from scratch

How it works

Our streamlined process ensures you receive expert Kubernetes implementation tailored to your specific organizational requirements, with a clear path from initial consultation to production deployment.

We work with you through these key steps:

1

Book a 30min introductory meeting with one of our Machine Learning Engineers and tell us about your current situation / problem.
2

Based on your situation and requirements, dida will propose a lean plan on how to support your team quickly and efficiently (i.e. 1-3 days of Kubernetes support for approx. 1-3K EUR).
3

Within the next three working days, an experienced Machine Learning Engineer with competencies in Kubernetes will start working on your problem.
4

After successful completion: Decide to expand the service, book a certain capacity per month or continue on your own.

Flexible support services for development teams

This service is best suited for data science and IT teams that…

are planning on working with Kubernetes and want dida to do the initial setup and integration into their projects, or
are already working with Kubernetes and desire consultation, development support or evaluations of already developed code.

About dida

dida is a software company from Berlin, Germany, specialized in the development of individual machine learning services. The highly technical team not only trains and optimizes neural networks, it also deploys them in complex production systems and takes care of operations, maintenance and scaling.

Since Kubernetes is essential for modern AI infrastructure, dida has worked extensively on container orchestration for scalable and efficient ML deployments. After solving common challenges in Kubernetes-based workflows, dida now offers a dedicated support service to help organizations with deployment, scaling, and resource management.

Frequently asked questions

Who will be working on our project?

Depending on the desired support volume dida will provide you with 1-2 experienced Machine Learning engineers that have the most experience with this specific tool / technology / framework.
Who will be our main point of contact?

The dida engineer who will lead the project will be the main point of contact so that respective engineers can directly communicate with each other.
How quickly can dida’s team help us address our current challenges with Kubernetes?

After signing the contract, dida guarantees to start within the next three working days.
How will we communicate during the project?

We’re open to your preferred choice of communication and organization (Email, Slack, MS Teams, Gitlab / GIthub issues, …)
Does dida work remotely or on-site?

Most of dida’s work is typically performed from our office in Berlin, Germany. Nevertheless we regularly visit our clients for workshops, interim and final presentations or whenever the situation demands it. If on-site work is required, please let us know so that we can arrange it.
How often will we receive updates on the project?

For short term support services you will be updated either daily or after every milestone.
What qualifications and experience does your team have?

dida’s team comprises largely of scientists and engineers with backgrounds in mathematics and physics - many of them holding PhDs from prestigious institutions. The highly specialized team has 8 years of industry experience in implementing machine learning solutions. dida solves algorithmically complex problems and often tackles use cases where less specialized in-house departments previously failed. Amongst its clients are large European organizations such as Deutsche Bahn, Klöckner, Zeiss or APCOA.
Are there any subcontractors involved in the service delivery?

No, all purchased services will be provided by dida employees.