Tag: DevOps (Page 1 of 2)

Overwhelmed by logs? Kubernetes to the rescue!

In Soluto we use a microservices architecture, whereby each service can ship its logs to our third party logs provider and query them to create alerts and dashboards and to improve visibility. As logs multiplied, the issues started… The continuous growth of our company has presented a new challenge to our logs collection system. The weekly addition of new services to our backend architecture led to an exponential growth of our log volume. All good up to here. However, this…

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Can Kubernetes Keep a Secret? It all depends what tool you’re using

At Soluto, we have super-devs who have full ownership: from writing code to deploying it to monitoring. When we made the shift to Kubernetes, we wanted to keep our devs independent and put a lot of effort into allowing them to create services rapidly. It all worked like a charm – until they had to handle credentials. This challenge leads us to build Kamus – an open source, GitOps, zero trust, secrets solution for Kubernetes applications. Kamus allows you to…

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Can Kubernetes Deployment be fun and simple?

Short answer: YES (scroll to end to find out, or check out the sample repo). Long answer: Read along to find out! Kubernetes deployment seems pretty simple: all you need is just a bunch of YAML files, and by using kubectl (the Kubernetes command line utility) you’ll have your service up and running in your Kubernetes cluster. Although deploying one service is an easy task, how do you deploy hundreds of microservices? At Soluto, we have more than 100 live…

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How I learned to stop worrying and love TeamCity mac agents

If you’re an iOS developer, then you’re probably familiar with the difficult task of developing CI pipelines for your app. Most of the dark corners involved in developing CI Pipelines for iOS could be avoided by outsourcing it to SaaS CI/CD solutions such as Travis, Circle or Bitrise. But what happens if you have to build 30 applications? Or more? At Soluto, we’re building a lot of applications, and I do mean A LOT. Having to build more than 30…

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How we deployed a scikit-learn model with Flask and Docker

In our last post we discussed our customer satisfaction prediction model. We used AzureML studio for our first deployment of this machine learning model, in order to serve real-time predictions. In this post we would like to share how and why we moved from AzureML to a Python deployment using Flask, Docker and Azure App Service. During this time we also tried Azure Function with Python. In addition, we open-sourced a sample Python API with Flask and Docker for machine…

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