Mock sample for your project: AWS Comprehend Medical API

Amazon Redshift Overview This is an interface reference for Amazon Redshift. It contains documentation for one of the programming or command line interfaces you can use to manage Amazon Redshift clusters. Note that Amazon Redshift is asynchronous, which means that some interfaces may require techniques, such as polling or asynchronous callback handlers, to determine when a command has been applied. In this reference, the parameter descriptions indicate whether a change is applied immediately, on the next instance reboot, or during the next maintenance window. For a summary of the Amazon Redshift cluster management interfaces, go to Using the Amazon Redshift Management Interfaces. Amazon Redshift manages all the work of setting up, operating, and scaling a data warehouse: provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine. You can focus on using your data to acquire new insights for your business and customers. If you are a first-time user of Amazon Redshift, we recommend that you begin by reading the Amazon Redshift Getting Started Guide. If you are a database developer, the Amazon Redshift Database Developer Guide explains how to design, build, query, and maintain the databases that make up your data warehouse.

Kinesis Video Streams Signaling Service is a intermediate service that establishes a communication channel for discovering peers, transmitting offers and answers in order to establish peer-to-peer connection in webRTC technology.

You can use Amazon CloudWatch Logs to monitor, store, and access your log files from EC2 instances, CloudTrail, and other sources. You can then retrieve the associated log data from CloudWatch Logs using the CloudWatch console, CloudWatch Logs commands in the Amazon Web Services CLI, CloudWatch Logs API, or CloudWatch Logs SDK. You can use CloudWatch Logs to: Monitor logs from EC2 instances in real-time : You can use CloudWatch Logs to monitor applications and systems using log data. For example, CloudWatch Logs can track the number of errors that occur in your application logs and send you a notification whenever the rate of errors exceeds a threshold that you specify. CloudWatch Logs uses your log data for monitoring so no code changes are required. For example, you can monitor application logs for specific literal terms (such as "NullReferenceException") or count the number of occurrences of a literal term at a particular position in log data (such as "404" status codes in an Apache access log). When the term you are searching for is found, CloudWatch Logs reports the data to a CloudWatch metric that you specify. Monitor CloudTrail logged events : You can create alarms in CloudWatch and receive notifications of particular API activity as captured by CloudTrail. You can use the notification to perform troubleshooting. Archive log data : You can use CloudWatch Logs to store your log data in highly durable storage. You can change the log retention setting so that any log events older than this setting are automatically deleted. The CloudWatch Logs agent makes it easy to quickly send both rotated and non-rotated log data off of a host and into the log service. You can then access the raw log data when you need it.

Amazon Lex provides both build and runtime endpoints. Each endpoint provides a set of operations (API). Your conversational bot uses the runtime API to understand user utterances (user input text or voice). For example, suppose a user says "I want pizza", your bot sends this input to Amazon Lex using the runtime API. Amazon Lex recognizes that the user request is for the OrderPizza intent (one of the intents defined in the bot). Then Amazon Lex engages in user conversation on behalf of the bot to elicit required information (slot values, such as pizza size and crust type), and then performs fulfillment activity (that you configured when you created the bot). You use the build-time API to create and manage your Amazon Lex bot. For a list of build-time operations, see the build-time API, .

AWS Single Sign-On (SSO) OpenID Connect (OIDC) is a web service that enables a client (such as AWS CLI or a native application) to register with AWS SSO. The service also enables the client to fetch the user’s access token upon successful authentication and authorization with AWS SSO. This service conforms with the OAuth 2.0 based implementation of the device authorization grant standard ( https://tools.ietf.org/html/rfc8628). For general information about AWS SSO, see What is AWS Single Sign-On? in the AWS SSO User Guide. This API reference guide describes the AWS SSO OIDC operations that you can call programatically and includes detailed information on data types and errors. AWS provides SDKs that consist of libraries and sample code for various programming languages and platforms such as Java, Ruby, .Net, iOS, and Android. The SDKs provide a convenient way to create programmatic access to AWS SSO and other AWS services. For more information about the AWS SDKs, including how to download and install them, see Tools for Amazon Web Services.

The Amazon SageMaker runtime API.

Amazon WorkLink is a cloud-based service that provides secure access to internal websites and web apps from iOS and Android phones. In a single step, your users, such as employees, can access internal websites as efficiently as they access any other public website. They enter a URL in their web browser, or choose a link to an internal website in an email. Amazon WorkLink authenticates the user's access and securely renders authorized internal web content in a secure rendering service in the AWS cloud. Amazon WorkLink doesn't download or store any internal web content on mobile devices.

SageMaker Edge Manager dataplane service for communicating with active agents.

Amazon Route 53 API actions let you register domain names and perform related operations.

Amazon Web Services Systems Manager is a collection of capabilities that helps you automate management tasks such as collecting system inventory, applying operating system (OS) patches, automating the creation of Amazon Machine Images (AMIs), and configuring operating systems (OSs) and applications at scale. Systems Manager lets you remotely and securely manage the configuration of your managed instances. A managed instance is any Amazon Elastic Compute Cloud instance (EC2 instance), or any on-premises server or virtual machine (VM) in your hybrid environment that has been configured for Systems Manager. This reference is intended to be used with the Amazon Web Services Systems Manager User Guide. To get started, verify prerequisites and configure managed instances. For more information, see Setting up Amazon Web Services Systems Manager in the Amazon Web Services Systems Manager User Guide. Related resources For information about how to use a Query API, see Making API requests. For information about other API operations you can perform on EC2 instances, see the Amazon EC2 API Reference. For information about AppConfig, a capability of Systems Manager, see the AppConfig User Guide and the AppConfig API Reference. For information about Incident Manager, a capability of Systems Manager, see the Incident Manager User Guide and the Incident Manager API Reference.

AWS Route53 Recovery Readiness

Key Management Service Key Management Service (KMS) is an encryption and key management web service. This guide describes the KMS operations that you can call programmatically. For general information about KMS, see the Key Management Service Developer Guide . KMS is replacing the term customer master key (CMK) with KMS key and KMS key. The concept has not changed. To prevent breaking changes, KMS is keeping some variations of this term. Amazon Web Services provides SDKs that consist of libraries and sample code for various programming languages and platforms (Java, Ruby, .Net, macOS, Android, etc.). The SDKs provide a convenient way to create programmatic access to KMS and other Amazon Web Services services. For example, the SDKs take care of tasks such as signing requests (see below), managing errors, and retrying requests automatically. For more information about the Amazon Web Services SDKs, including how to download and install them, see Tools for Amazon Web Services. We recommend that you use the Amazon Web Services SDKs to make programmatic API calls to KMS. Clients must support TLS (Transport Layer Security) 1.0. We recommend TLS 1.2. Clients must also support cipher suites with Perfect Forward Secrecy (PFS) such as Ephemeral Diffie-Hellman (DHE) or Elliptic Curve Ephemeral Diffie-Hellman (ECDHE). Most modern systems such as Java 7 and later support these modes. Signing Requests Requests must be signed by using an access key ID and a secret access key. We strongly recommend that you do not use your Amazon Web Services account (root) access key ID and secret key for everyday work with KMS. Instead, use the access key ID and secret access key for an IAM user. You can also use the Amazon Web Services Security Token Service to generate temporary security credentials that you can use to sign requests. All KMS operations require Signature Version 4. Logging API Requests KMS supports CloudTrail, a service that logs Amazon Web Services API calls and related events for your Amazon Web Services account and delivers them to an Amazon S3 bucket that you specify. By using the information collected by CloudTrail, you can determine what requests were made to KMS, who made the request, when it was made, and so on. To learn more about CloudTrail, including how to turn it on and find your log files, see the CloudTrail User Guide. Additional Resources For more information about credentials and request signing, see the following: Amazon Web Services Security Credentials - This topic provides general information about the types of credentials used to access Amazon Web Services. Temporary Security Credentials - This section of the IAM User Guide describes how to create and use temporary security credentials. Signature Version 4 Signing Process - This set of topics walks you through the process of signing a request using an access key ID and a secret access key. Commonly Used API Operations Of the API operations discussed in this guide, the following will prove the most useful for most applications. You will likely perform operations other than these, such as creating keys and assigning policies, by using the console. Encrypt Decrypt GenerateDataKey GenerateDataKeyWithoutPlaintext

Provides create, read, update and delete functionality for Azure SQL Database resources including servers, databases, elastic pools, recommendations, operations, and usage metrics.

Azure DevOps Resource Provider

The HDInsight Management Client.

The HDInsight Management Client.

These APIs allow end users to operate on Azure Machine Learning Web Services resources. They support the following operations: Create or update a web service Get a web service Patch a web service Delete a web service Get All Web Services in a Resource Group Get All Web Services in a Subscription Get Web Services Keys

The Container Service Client.

Azure Bot Service is a platform for creating smart conversational agents.

The HDInsight Management Client.

The Anomaly Detector API detects anomalies automatically in time series data. It supports two kinds of mode, one is for stateless using, another is for stateful using. In stateless mode, there are three functionalities. Entire Detect is for detecting the whole series with model trained by the time series, Last Detect is detecting last point with model trained by points before. ChangePoint Detect is for detecting trend changes in time series. In stateful mode, user can store time series, the stored time series will be used for detection anomalies. Under this mode, user can still use the above three functionalities by only giving a time range without preparing time series in client side. Besides the above three functionalities, stateful model also provide group based detection and labeling service. By leveraging labeling service user can provide labels for each detection result, these labels will be used for retuning or regenerating detection models. Inconsistency detection is a kind of group based detection, this detection will find inconsistency ones in a set of time series. By using anomaly detector service, business customers can discover incidents and establish a logic flow for root cause analysis.

Dev Spaces REST API