Temporal is a scalable and reliable runtime for durable function executions called Temporal Workflow Executions.
Said another way, it's a platform that guarantees the Durable Execution of your application code.
It enables you to develop as if failures don't even exist. Your application will run reliably even if it encounters problems, such as network outages or server crashes, which would be catastrophic for a typical application. The Temporal Platform handles these types of problems, allowing you to focus on the business logic, instead of writing application code to detect and recover from failures.
The Temporal System
Durable Execution in the context of Temporal refers to the ability of a Workflow Execution to maintain its state and progress even in the face of failures, crashes, or server outages. This is achieved through Temporal's use of an Event History, which records the state of a Workflow Execution at each step. If a failure occurs, the Workflow Execution can resume from the last recorded event, ensuring that progress isn't lost. This durability is a key feature of Temporal Workflow Executions, making them reliable and resilient. It enables application code to execute effectively once and to completion, regardless of whether it takes seconds or years.
What is the Temporal Platform?
The Temporal Platform consists of a supervising software typically called a Temporal Cluster and application code bundled as Worker Processes. Together these components create a runtime for your application.
The Temporal Platform
A Temporal Cluster consists of the Temporal Server and a database.
Our software as a server (SaaS) offering, Temporal Cloud, offers an alternative to hosting a Temporal Cluster yourself.
Worker Processes are hosted and operated by you and execute your code. Workers run using one of our SDKs.
Basic component topology of the Temporal Platform
What is a Temporal Application?
A Temporal Application is a set of Temporal Workflow Executions. Each Temporal Workflow Execution has exclusive access to its local state, executes concurrently to all other Workflow Executions, and communicates with other Workflow Executions and the environment via message passing.
A Temporal Application can consist of millions to billions of Workflow Executions. Workflow Executions are lightweight components. A Workflow Execution consumes few compute resources; in fact, if a Workflow Execution is suspended, such as when it is in a waiting state, the Workflow Execution consumes no compute resources at all.
A Temporal Workflow Execution is a Reentrant Process. A Reentrant Process is resumable, recoverable, and reactive.
- Resumable: Ability of a process to continue execution after execution was suspended on an awaitable.
- Recoverable: Ability of a process to continue execution after execution was suspended on a failure.
- Reactive: Ability of a process to react to external events.
Therefore, a Temporal Workflow Execution executes a Temporal Workflow Definition, also called a Temporal Workflow Function, your application code, exactly once and to completion—whether your code executes for seconds or years, in the presence of arbitrary load and arbitrary failures.
What is a Temporal SDK?
A Temporal SDK is a language-specific library that offers APIs to do the following:
A Temporal SDK enables you to write your application code using the full power of the programming language, while the Temporal Platform handles the durability, reliability, and scalability of the application.
Temporal currently offers the following SDKs:
- Get started with the Go SDK
- Get started with the Java SDK
- Get started with the PHP SDK
- Get started with the Python SDK
- Get started with the TypeScript SDK
Each SDK emits metrics which can be ingested into monitoring platforms. See the SDK metrics reference for a complete list.
Temporal offers methods of authenticating and authorizing client API calls within our SDKs.
Some SDKs support running Workflows inside a sandbox environment.
The Temporal Python SDK, for example, enables you to run Workflow code in a sandbox environment to help prevent non-determinism errors in your application. The Temporal Workflow Sandbox for Python is not completely isolated, and some libraries can internally mutate state, which can result in breaking determinism.
By default, Workflows run in a sandbox environment. If a Workflow Execution performs a non-deterministic event, an exception is thrown, which results in failing the Workflow Task. The Workflow will not progress until the code is fixed.
For more information, see the knowledge base article on Python sandbox environments.
SDKs in development
The following SDKs are in development and do not yet have developer's guides:
The following third-party SDKs exist but are not supported in the Developer's guide:
What is a Temporal Client?
A Temporal Client is available in each SDK and provides a set of APIs to communicate with a Temporal Cluster.
The most common operations that a Temporal Client enables you to perform are the following:
- Get the result of Workflow Execution.
- List Workflow Executions.
- Query a Workflow Execution.
- Signal a Workflow Execution.
- Start a Workflow Execution.
What is a Failure?
Temporal Failures are representations (in the SDKs and Event History) of various types of errors that occur in the system.
Failure handling is an essential part of development. For more information, including the difference between application-level and platform-level failures, see Handling Failure From First Principles. For the practical application of those concepts in Temporal, see Failure Handling in Practice.
For languages that throw (or raise) errors (or exceptions), throwing an error that is not a Temporal Failure from a Workflow fails the Workflow Task (and the Task will be retried until it succeeds), whereas throwing a Temporal Failure (or letting a Temporal Failure propagate from Temporal calls, like an Activity Failure from an Activity call) fails the Workflow Execution. For more information, see Application Failure.