DevOps, FinOps and MLOps
Faster deployments, known costs, working models
Deployments, cloud costs, ML models
Manual deployments cost time. An unmanaged cloud costs money. A model without monitoring loses quality over time. We put all three areas in order.
We automate how software is built and deployed. We help you control cloud costs. We move ML models from the trial stage into production.
01 / DevOps, FinOps and MLOps
DevOps
Repeatable builds, tests and deployments.
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CI/CD
Every code change goes through tests and reaches the environment automatically.
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Infrastructure as code
We describe the environment in Terraform or Ansible. Every change can be reproduced.
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Containers
Docker and Kubernetes. The application runs the same way in every environment.
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Monitoring
Metrics, logs and alerts. You see a problem before a customer reports it.
02 / DevOps, FinOps and MLOps
FinOps
According to the FinOps Foundation, it is collaboration between engineering, finance and business on technology costs.
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Cost visibility
We tag resources and allocate costs to teams and projects.
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Optimisation
We shut down unused resources. We match machine sizes to the workload.
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Budgets and alerts
We set spending limits. Going over budget triggers an alert.
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Cost report
Every month, you receive a cost report with recommendations.
03 / DevOps, FinOps and MLOps
MLOps
We automate the lifecycle of ML models.
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Model deployment
A model reaches production through the same process as code.
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Model monitoring
We track prediction quality and changes in input data.
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Retraining
Retraining starts on a schedule or when quality drops.
04 / DevOps, FinOps and MLOps
Process
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Review
We review the deployment process, cloud bills and models.
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Plan
You receive a list of changes with their cost and expected effect.
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Implementation
We make changes in stages, with a rollback plan.
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Handover
We hand over the code and documentation. We train the team.
05 / DevOps, FinOps and MLOps
Use cases
- CI/CD pipeline for a web application
- Environment described in Terraform
- Moving an application into containers
- Allocating cloud costs to teams
- Shutting down test environments after working hours
- Automatic retraining of a sales forecast model
- Monitoring model quality in production
06 / FAQ
Frequently asked questions
What is FinOps?
According to the FinOps Foundation, it is a practice in which engineering, finance and business teams share responsibility for technology costs. Each team sees the cost of its resources and is accountable for it.
Which clouds do you work with?
AWS, Azure and Google Cloud. We also work with on-premises and hybrid environments.
Do you maintain what you implement?
Yes, under a separate contract. We can also hand everything over to your team.
Does MLOps make sense for a single model?
Yes, if the model runs in production. Monitoring and repeatable deployment protect you from an unnoticed drop in quality.
Do we need Kubernetes?
Not always. With a few applications, simpler container services are often enough. We choose the tool to fit the scale.
Let’s review your deployments and cloud costs
Describe your environment. We will propose the scope of a review.