Argo
Argo is an open-source, Kubernetes-native suite of tools for continuous delivery, workflow orchestration, and workload automation.
Platform Engineering on Kubernetes
Argo CD is a declarative continuous delivery tool that synchronizes application and infrastructure configuration from Git repositories to Kubernetes clusters.
- How it is used
- Deploys service-pipeline artifacts into Kubernetes environments by syncing their Git-held configuration.
- How deep it goes
- Walks through application creation and a release-change workflow, including repository selection, destination, Helm parameters and rollback.
- Examples
- Uses a staging configuration directory, Argo CD application settings and a frontend release pull request.
- What you can do after
- Operate/configure Argo CD to sync a staging environment and change or revert deployed service versions through Git.
Distributed Machine Learning Patterns
Argo Project is a suite of open-source tools for deploying and running applications and workloads on Kubernetes.
- How it is used
- Orchestrates end-to-end machine learning workflows on Kubernetes, connecting pipeline components and managing containerized steps.
- How deep it goes
- Explains workflow templates, submission, Pod inspection, DAG dependencies, conditional steps, and memoization; defers broader project implementation details.
- Examples
- Demonstrates hello-world, ConfigMap resource, Python script, diamond DAG, coin-flip conditional, and map-reduce-style workflows.
- What you can do after
- Apply it via Kubernetes and Argo Workflows to define, submit, inspect, and optimize container-native machine learning pipelines.
Read how Distributed Machine Learning Patterns explains Argo →
Effective Platform Engineering
Argo CD is a Kubernetes continuous-delivery tool that synchronizes applications with declarative configuration stored in version control.
- How it is used
- Separates application deployment from pipeline orchestration while supporting Kubernetes platform delivery.
- How deep it goes
- Explains deployment responsibilities and centralized versus per-cluster placement, but defers detailed scaling strategies.
- Examples
- Uses centralized multi-cluster management and per-cluster deployment as contrasting operating models.
- What you can do after
- Operate Kubernetes deployments through a dedicated deployer without granting pipelines direct Kubernetes API access.
Designing Deep Learning Systems: A guide for software engineers
Argo Workflows is an open-source container-native workflow engine for orchestrating jobs and pipelines, commonly on Kubernetes.
- How it is used
- Automates repeatable parallel or sequential job pipelines, especially when the surrounding system already runs on Kubernetes.
- How deep it goes
- Descends from architecture into CRDs, controller behavior, pod isolation, artifact passing, YAML, and operational commands.
- Examples
- Uses a daily data-processing pipeline that checks data, transforms it, writes a database table, and sends a Slack notification.
- What you can do after
- Operate/configure workflows through YAML, Argo commands, and kubectl, while inspecting runs and Kubernetes resources.
Read how Designing Deep Learning Systems: A guide for software engineers explains Argo →
Related concepts
- Kubernetesuses · Kubernetes is an open-source platform for orchestrating and automating the deployment, scaling, and management of containerized workloads across computing clusters.
- repositoryuses · A software repository is an organized storage location or collection of project files and related artifacts, often managed with version history and change tracking.
- GitOpsimplements · GitOps is an operational approach that uses version-controlled declarative configuration as the source of truth and automation to apply or reconcile system state.
- Apache Airflowalternative to · Apache Airflow is an open-source platform for authoring, scheduling, and monitoring programmatically defined workflows, commonly represented as directed acyclic graphs.
- agent orchestrationkind of · Orchestration is the coordination and sequencing of agents, services, tasks, or components to carry out a larger workflow or objective.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.