Expand description
IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight.
Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources.
IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.
§Getting Started
Examples are available for many services and operations, check out the examples folder in GitHub.
The SDK provides one crate per AWS service. You must add Tokio
as a dependency within your Rust project to execute asynchronous code. To add aws-sdk-iotanalytics
to
your project, add the following to your Cargo.toml file:
[dependencies]
aws-config = { version = "1.1.7", features = ["behavior-version-latest"] }
aws-sdk-iotanalytics = "1.65.0"
tokio = { version = "1", features = ["full"] }
Then in code, a client can be created with the following:
use aws_sdk_iotanalytics as iotanalytics;
#[::tokio::main]
async fn main() -> Result<(), iotanalytics::Error> {
let config = aws_config::load_from_env().await;
let client = aws_sdk_iotanalytics::Client::new(&config);
// ... make some calls with the client
Ok(())
}
See the client documentation for information on what calls can be made, and the inputs and outputs for each of those calls.
§Using the SDK
Until the SDK is released, we will be adding information about using the SDK to the Developer Guide. Feel free to suggest additional sections for the guide by opening an issue and describing what you are trying to do.
§Getting Help
- GitHub discussions - For ideas, RFCs & general questions
- GitHub issues - For bug reports & feature requests
- Generated Docs (latest version)
- Usage examples
§Crate Organization
The entry point for most customers will be Client
, which exposes one method for each API
offered by AWS IoT Analytics. The return value of each of these methods is a “fluent builder”,
where the different inputs for that API are added by builder-style function call chaining,
followed by calling send()
to get a Future
that will result in
either a successful output or a SdkError
.
Some of these API inputs may be structs or enums to provide more complex structured information.
These structs and enums live in types
. There are some simpler types for
representing data such as date times or binary blobs that live in primitives
.
All types required to configure a client via the Config
struct live
in config
.
The operation
module has a submodule for every API, and in each submodule
is the input, output, and error type for that API, as well as builders to construct each of those.
There is a top-level Error
type that encompasses all the errors that the
client can return. Any other error type can be converted to this Error
type via the
From
trait.
The other modules within this crate are not required for normal usage.
Modules§
- client
- Client for calling AWS IoT Analytics.
- config
- Configuration for AWS IoT Analytics.
- error
- Common errors and error handling utilities.
- meta
- Information about this crate.
- operation
- All operations that this crate can perform.
- primitives
- Primitives such as
Blob
orDateTime
used by other types. - types
- Data structures used by operation inputs/outputs.
Structs§
Enums§
- Error
- All possible error types for this service.