For this discussion, we will configure overlay2 as the storage driver. Although it is configured by default, and you can skip the steps if you are following this book, it is worth a read in case you want to change it to something else. First, let’s list the existing storage driver: $ docker info | […]
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If you mount a host directory that already contains files to an empty volume of the container, the container can see the files stored in the host. This is an excellent way to pre-populate files for your container(s) to use. However, if the directory does not exist in the host filesystem, Docker will create the […]
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Structuring the Git repository To implement GitOps, we require at least two repositories: the application repository and the environment repository. This does not mean that you cannot combine the two, but for the sake of simplicity, let’s take a look at each of them separately. The application repository The application repository stores the application code. […]
Read More… from The application repository – Source Code Management with Git and GitOps
Branching strategies and the GitOps workflow GitOps requires at least two kinds of Git repositories to function: the application repository, which is from where your builds are triggered, and the environment repository, which contains all of the infrastructure and configuration as code (CaC). All deployments are driven from the environment repository, and the changes to […]
Read More… from The push model – Source Code Management with Git and GitOps
GitOps has the following key principles: Implementing and living by these principles is simple with modern DevOps tools and techniques, and we will look at practically implementing them later in Chapters 11 and 12. In this chapter, however, we’ll examine their design principles using a branching strategy and GitOps workflow. […]
Read More… from The principles of GitOps – Source Code Management with Git and GitOps
GitOps is a method that involves implementing DevOps so that Git forms the single source of truth. Instead of maintaining a long list of scripts and tooling to support this, GitOps focuses on writing declarative code for everything, including the infrastructure, configuration, and application code. This means you can spin anything out of thin air […]
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Step 5: Train the model: This code initiates the training of the neural network model using the training data (X_train and y_train) for 20 epochs, with a batch size of 32. The validation data (X_test and y_test) is used to evaluate the model’s performance during training: Train the modelmodel.fit(X_train, y_train, epochs=20, batch_size=32, \ validation_data=(X_test, y_test)) Step 6: […]
Read More… from Hands-on – labeling audio data using a CNN – Labeling Audio Data-3