SE Radio 596: Maxim Fateev on Durable Execution with Temporal
Dec 27, 2023
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Maxim Fateev, CEO of Temporal, discusses durable execution, concepts of workflows, activities, timers, event histories, signals, and queries. He compares self-hosted clusters with Temporal Cloud for deployment. Also, explore the evolution of Temporal from Cadence, saga pattern implementation, Temporal client SDKs, parallel execution in different languages, setting up a Temporal cluster, database contents, and challenges of workflow versioning.
Durable execution in Temporal ensures code continuity and preservation of local state during process crashes or infrastructure outages.
Temporal simplifies the implementation of sagas by guaranteeing compensation actions for failed actions within a workflow.
Temporal provides language-specific SDKs that leverage native language features for parallel execution, improving performance and productivity.
Deep dives
Durable Execution: A New Abstraction
Durable execution is a new abstraction that provides the capability to keep the full state of code execution durable all the time. This means that even in the event of process crashes or infrastructure outages, the code continues running seamlessly, preserving the entire local state and blocking calls. It offers the guarantee of completion, making it suitable for scenarios that require durability and compensation handling.
Temporal: An Open Source Workflow Automation Project
Temporal is an open-source project that provides an MIT-licensed backend server and client SDKs for various programming languages. It was originally called Cadence and has seven years of production usage at scale by numerous companies. Temporal enables developers to automate business processes using distributed systems. With Temporal, developers can build workflows with durable execution, manage state, and handle complex business logic in an efficient and reliable manner.
Implementing Sagas with Temporal
Temporal simplifies the implementation of sagas, which are patterns used to handle business-level failures and compensation in distributed systems. By utilizing the durability and event-driven nature of Temporal, developers can easily guarantee compensation actions for failed actions within a workflow. Temporal provides a fault-oblivious approach, ensuring that the code keeps running even in the face of failures, such as infrastructure crashes or unpredictable errors. This enables developers to focus on the logic of compensation actions, making implementing sagas in Temporal straightforward and highly effective.
Parallel Execution and Language-Specific SDKs
Temporal provides language-specific SDKs for Go, Java, PHP, Python, TypeScript, and upcoming .NET. These SDKs leverage native language features to enable developers to harness the power of parallel execution. For example, in Java, developers can use asynchronous calls and Java's built-in features, while in Go, they can utilize Goroutines and channels. Parallel execution allows for efficient processing of multiple tasks concurrently, improving performance and productivity.
Scalability and Workflow Versioning
Temporal provides a scalable solution for handling large blobs by recommending the storage of blobs in other systems and passing pointers. It also offers a way to handle the versioning of workflows, allowing for code upgrades and compatibility between different versions.
Multi-Cluster Replication and Namespace as a Service
Temporal offers multi-cluster replication for improved reliability and failover support. It allows running multiple clusters in different regions, each with their own storage and communication through a high-level application protocol. Temporal Cloud also provides namespaces as a service, separating the cluster management from the user, offering scalability, and supporting individual failovers for each namespace.
Maxim Fateev, the CEO of Temporal, speaks with SE Radio's Philip Winston about how Temporal implements durable execution. They explore concepts including workflows, activities, timers, event histories, signals, and queries. Maxim also compares deployment using self-hosted clusters or the Temporal Cloud.
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