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Orchestration

17 items tagged with "orchestration"

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Best Practices1

Best Practice

AI Agent Design Patterns

AI agent design patterns are reusable structures for LLM systems that plan, use tools, and act over multiple steps, covering reflection, tool use, planning, and multi-agent collaboration.

Models1

Model

Grok 4.20 Multi-Agent (Beta)

A Grok 4.20 beta variant positioned for multi-agent workflows, with a 2M token context window for coordinating longer multi-step tasks.

Tutorials2

Tutorial

How to orchestrate workflows with AWS Step Functions

Build a state machine with AWS Step Functions to orchestrate Lambda tasks with retries, branching, and error handling.

Tutorial

How to author a data pipeline DAG in Apache Airflow

Write an Airflow DAG with scheduled tasks and dependencies, run it locally, and monitor execution in the UI.

Migrations1

Migration

Docker Compose to Kubernetes Migration

Containerized application migration from Docker Compose to Kubernetes

Products1

Product

Kubernetes

Container orchestration platform for automating deployment

Playbooks1

Playbook

Data Pipeline Orchestration Program Playbook

Modernize fragile cron and script-based data pipelines into a governed orchestration platform with lineage, retries, and observability.

Stacks4

Stack

Airflow + Spark Batch Pipeline Stack

Classic big-data batch pattern: Apache Airflow orchestrates scheduled DAGs that run distributed Apache Spark jobs over data-lake storage.

Stack

LLM Agent Stack

Agentic AI stack: an orchestration framework drives an LLM to reason, call tools and APIs, and use vector memory to complete multi-step tasks autonomously.

Stack

Dagster + dbt

An asset-oriented data orchestration stack where Dagster schedules and observes pipelines built around dbt's transformation models.

Stack

Prefect + Spark

A Python-native orchestration stack where Prefect schedules and monitors large-scale data processing jobs running on Apache Spark.

Comparisons1

Comparison

Airflow vs Dagster

The established task-based workflow orchestrator versus Dagster's asset-oriented, developer-friendly data orchestrator.

FAQs5

FAQ

What is Kubernetes?

Kubernetes is an open-source platform for automating the deployment, scaling, and operation of containerized applications. It groups containers into l...

FAQ

What is the difference between a Kubernetes pod and a container?

A container is a single packaged process, while a pod is the smallest deployable unit in Kubernetes and can hold one or more containers that share the...

FAQ

When should I use Kubernetes?

Kubernetes makes sense when you run many containerized services that need automated scaling, self-healing, rolling updates, and consistent deployment ...

FAQ

What is container orchestration?

Container orchestration is the automated management of the lifecycle of containers across a cluster of machines, including scheduling, scaling, networ...

FAQ

What is a data pipeline?

A data pipeline is a series of automated steps that move data from sources to destinations, transforming and validating it along the way so it is read...