Workflow orchestrators help manage the complexities of asynchronous systems by streamlining state management, enhancing resiliency to errors, enabling traceability, and facilitating maintainability. Some popular options for workflow orchestrators include Apache Airflow, Argo, Temporal, and AWS Step Functions, each with their own strengths for managing workflows. Choosing the right orchestrator depends on factors like task complexity, scalability needs, and whether an open-source or managed service is preferred.

1. Workflow
orchestrators make
Asynchronous SOA
Easy

2. What is asynchronous SOA?
● Asynchronous SOA refers to a design where services communicate without requiring
an immediate response.
● It allows the client to send a request and continue with other tasks, receiving the
response at an unspecified later time.
● This approach enhances system performance and scalability as services can operate
independently and in parallel.

3. Asynchronous SOA - Behind the Scenes
● When you order food on your favorite food delivery app, it triggers concurrent,
asynchronous processes: order confirmation, payment processing, restaurant
notification, food preparation, and delivery.
● These steps, while appearing sequential to you, are processed concurrently in the
system

5. Challenges of
building
asynchronous SOA

6. State Management
● In an event-driven, asynchronous SOA like a food delivery app, managing state is
complex.
● As the order moves through stages - placed, confirmed, prepared, and delivered - each
stage is triggered by events and runs independently.
● Ensuring accurate state management across these dispersed, independent processes
is challenging, but vital to avoid inaccuracies and maintain a seamless user experience.

8. Resiliency
● Asynchronous systems must be resilient to
handle errors, such as a declined payment or a
missed restaurant notification.
● The system should adapt, adjust, and continue
functioning, just like a football team carrying on
after a bad pass..

9. Traceability
● Traceability is crucial in complex asynchronous systems like Uber Eats, involving
multiple components like user app, restaurant system, delivery app, and backend
services.
● Troubleshooting issues requires effective tracing mechanisms to maintain system
efficiency.

10. Maintainability
● Asynchronous systems, due to their complexity, can be challenging to maintain as they
evolve and scale.
● Adding new features or onboarding new team members should not require significant
system changes.

11. Workflow
orchestrators

12. Streamlining State Management
● Workflow orchestrators alleviate the challenge of state management in asynchronous
systems.
● Orchestrators meticulously oversee the stages and transitions of a process.
● Each state is properly tracked and managed, ensuring accurate and orderly flow.
● This eliminates chaos and potential inconsistencies in state transitions.

14. Enhancing Resiliency
● Workflow orchestrators offer built-in mechanisms to handle errors and enhance
resiliency.
● They provide intelligent error handling strategies, such as automatic retries and
backoffs.
● Orchestrators prevent process halts and enable system recovery in case of failures.
● This robustness ensures uninterrupted operations, even in the face of unpredicted
errors.

15. Enabling Traceability
● Workflow orchestrators simplify traceability in complex asynchronous systems.
● They provide comprehensive logging and monitoring capabilities.
● Each stage and transition within the system is made visible and traceable.
● This aids in troubleshooting, debugging, and identifying bottlenecks or issues.

16. Facilitating Maintainability
● Workflow orchestrators ease the challenge of maintaining complex asynchronous
systems.
● Clearly defined, code-based workflows make the system more understandable and
modifiable.
● Changes and updates can be implemented without disrupting the entire system.
● Adding new features or modifying existing ones becomes more manageable and
efficient.

17. Empowering Development Productivity
● Workflow orchestrators empower developers by abstracting complexities of
asynchronous systems.
● They provide a higher-level programming model, simplifying development efforts.
● Developers can focus on business logic and core functionalities rather than
infrastructure concerns.
● This enhances development productivity, accelerates time-to-market, and fosters
innovation.

18. Workflow
orchestrator
options

19. Apache Airflow
● Apache Airflow is a widely-used open-source workflow orchestrator.
● It allows you to define workflows as code using Python, providing flexibility and ease
of understanding.
● Airflow has a vibrant community and extensive plugin support for seamless
integration with various services.
● It excels in data engineering tasks and scenarios where the steps of workflows may
change frequently.

20. Argo
● Argo is a Kubernetes-native workflow orchestrator, specifically designed for
cloud-native environments.
● It leverages the power of Kubernetes to manage the execution of workflows.
● Each step in an Argo workflow is treated as a container, allowing for easy adoption of
containerization benefits.
● Argo is well-suited for organizations using Kubernetes and seeking scalability, fault
tolerance, and flexibility in their workflows.

21. Temporal
● Temporal is an open-source workflow orchestrator that focuses on reliability and
simplicity.
● It allows developers to define workflows as code, eliminating the need for managing
JSON or YAML files.
● Temporal offers long-duration execution, exactly-once semantics, and built-in
handling of failures and interruptions.
● It excels in managing stateful and long-running workflows while ensuring reliability
and ease of development.

22. AWS Step Functions
● AWS Step Functions is a fully managed workflow orchestrator provided by Amazon
Web Services (AWS).
● It simplifies the orchestration of complex, multi-step applications using visual
workflows.
● Step Functions seamlessly integrate with other AWS services, making it a suitable
choice for organizations already utilizing the AWS ecosystem.
● It offers scalability, fault tolerance, and ease of use, empowering developers to build
robust and scalable applications.

23. Choose the Right Workflow Orchestrator
● When selecting a workflow orchestrator, consider factors such as the complexity of
tasks, scalability requirements, fault tolerance, integrations with existing
infrastructure, and convenience of the programming model.
● Each orchestrator offers unique features and benefits, catering to specific use cases
and preferences.
● Evaluate whether a fully managed service like AWS Step Functions or Google Cloud
Composer aligns with your organization's needs or if the flexibility of an open-source
solution like Apache Airflow, Argo, or Temporal better suits your requirements.

24. Harness the Power of Workflow
Orchestrators
● Regardless of the choice of workflow orchestrator, leveraging these powerful tools
helps simplify the complexities of asynchronous systems.
● Each orchestrator offers unique features and advantages, enabling developers to build
resilient, scalable, and maintainable applications.
● Harnessing the power of workflow orchestrators empowers organizations to deliver
better services, optimize development processes, and stay ahead in today's dynamic
technology landscape.