Mock sample for your project: Amazon Kinesis Firehose API

Amazon RDS Data Service Amazon RDS provides an HTTP endpoint to run SQL statements on an Amazon Aurora Serverless DB cluster. To run these statements, you work with the Data Service API. For more information about the Data Service API, see Using the Data API for Aurora Serverless in the Amazon Aurora User Guide.

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.

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

AWS Step Functions AWS Step Functions is a service that lets you coordinate the components of distributed applications and microservices using visual workflows. You can use Step Functions to build applications from individual components, each of which performs a discrete function, or task, allowing you to scale and change applications quickly. Step Functions provides a console that helps visualize the components of your application as a series of steps. Step Functions automatically triggers and tracks each step, and retries steps when there are errors, so your application executes predictably and in the right order every time. Step Functions logs the state of each step, so you can quickly diagnose and debug any issues. Step Functions manages operations and underlying infrastructure to ensure your application is available at any scale. You can run tasks on AWS, your own servers, or any system that has access to AWS. You can access and use Step Functions using the console, the AWS SDKs, or an HTTP API. For more information about Step Functions, see the AWS Step Functions Developer Guide .

AWS Service Catalog AWS Service Catalog enables organizations to create and manage catalogs of IT services that are approved for AWS. To get the most out of this documentation, you should be familiar with the terminology discussed in AWS Service Catalog Concepts.

Suite of geospatial services including Maps, Places, Routes, Tracking, and Geofencing

The Amazon SageMaker runtime API.

Amazon Kinesis Analytics Overview This documentation is for version 1 of the Amazon Kinesis Data Analytics API, which only supports SQL applications. Version 2 of the API supports SQL and Java applications. For more information about version 2, see Amazon Kinesis Data Analytics API V2 Documentation. This is the Amazon Kinesis Analytics v1 API Reference. The Amazon Kinesis Analytics Developer Guide provides additional information.

Amazon S3 Glacier (Glacier) is a storage solution for "cold data." Glacier is an extremely low-cost storage service that provides secure, durable, and easy-to-use storage for data backup and archival. With Glacier, customers can store their data cost effectively for months, years, or decades. Glacier also enables customers to offload the administrative burdens of operating and scaling storage to AWS, so they don't have to worry about capacity planning, hardware provisioning, data replication, hardware failure and recovery, or time-consuming hardware migrations. Glacier is a great storage choice when low storage cost is paramount and your data is rarely retrieved. If your application requires fast or frequent access to your data, consider using Amazon S3. For more information, see Amazon Simple Storage Service (Amazon S3). You can store any kind of data in any format. There is no maximum limit on the total amount of data you can store in Glacier. If you are a first-time user of Glacier, we recommend that you begin by reading the following sections in the Amazon S3 Glacier Developer Guide : What is Amazon S3 Glacier - This section of the Developer Guide describes the underlying data model, the operations it supports, and the AWS SDKs that you can use to interact with the service. Getting Started with Amazon S3 Glacier - The Getting Started section walks you through the process of creating a vault, uploading archives, creating jobs to download archives, retrieving the job output, and deleting archives.

Amazon Elastic File System Amazon Elastic File System (Amazon EFS) provides simple, scalable file storage for use with Amazon EC2 instances in the Amazon Web Services Cloud. With Amazon EFS, storage capacity is elastic, growing and shrinking automatically as you add and remove files, so your applications have the storage they need, when they need it. For more information, see the Amazon Elastic File System API Reference and the Amazon Elastic File System User Guide.

This is the Resource Access Manager API Reference. This documentation provides descriptions and syntax for each of the actions and data types in RAM. RAM is a service that helps you securely share your Amazon Web Services resources across Amazon Web Services accounts and within your organization or organizational units (OUs) in Organizations. For supported resource types, you can also share resources with IAM roles and IAM users. If you have multiple Amazon Web Services accounts, you can use RAM to share those resources with other accounts. To learn more about RAM, see the following resources: Resource Access Manager product page Resource Access Manager User Guide

Amazon DynamoDB Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. DynamoDB lets you offload the administrative burdens of operating and scaling a distributed database, so that you don't have to worry about hardware provisioning, setup and configuration, replication, software patching, or cluster scaling. With DynamoDB, you can create database tables that can store and retrieve any amount of data, and serve any level of request traffic. You can scale up or scale down your tables' throughput capacity without downtime or performance degradation, and use the AWS Management Console to monitor resource utilization and performance metrics. DynamoDB automatically spreads the data and traffic for your tables over a sufficient number of servers to handle your throughput and storage requirements, while maintaining consistent and fast performance. All of your data is stored on solid state disks (SSDs) and automatically replicated across multiple Availability Zones in an AWS region, providing built-in high availability and data durability.

Provides operations for working with resources and resource groups.

Amazon Comprehend is an AWS service for gaining insight into the content of documents. Use these actions to determine the topics contained in your documents, the topics they discuss, the predominant sentiment expressed in them, the predominant language used, and more.

Amazon Simple Workflow Service The Amazon Simple Workflow Service (Amazon SWF) makes it easy to build applications that use Amazon's cloud to coordinate work across distributed components. In Amazon SWF, a task represents a logical unit of work that is performed by a component of your workflow. Coordinating tasks in a workflow involves managing intertask dependencies, scheduling, and concurrency in accordance with the logical flow of the application. Amazon SWF gives you full control over implementing tasks and coordinating them without worrying about underlying complexities such as tracking their progress and maintaining their state. This documentation serves as reference only. For a broader overview of the Amazon SWF programming model, see the Amazon SWF Developer Guide .

Use these REST APIs for performing operations on User entity in Azure API Management deployment. The User entity in API Management represents the developers that call the APIs of the products to which they are subscribed.

Role based access control provides you a way to apply granular level policy administration down to individual resources or resource groups. These operations enable you to manage role definitions and role assignments. A role definition describes the set of actions that can be performed on resources. A role assignment grants access to Azure Active Directory users.

Alert operation endpoints and objects.

Azure Blueprints Client provides access to blueprint definitions, assignments, and artifacts, and related blueprint operations.

AWS CodeDeploy AWS CodeDeploy is a deployment service that automates application deployments to Amazon EC2 instances, on-premises instances running in your own facility, serverless AWS Lambda functions, or applications in an Amazon ECS service. You can deploy a nearly unlimited variety of application content, such as an updated Lambda function, updated applications in an Amazon ECS service, code, web and configuration files, executables, packages, scripts, multimedia files, and so on. AWS CodeDeploy can deploy application content stored in Amazon S3 buckets, GitHub repositories, or Bitbucket repositories. You do not need to make changes to your existing code before you can use AWS CodeDeploy. AWS CodeDeploy makes it easier for you to rapidly release new features, helps you avoid downtime during application deployment, and handles the complexity of updating your applications, without many of the risks associated with error-prone manual deployments. AWS CodeDeploy Components Use the information in this guide to help you work with the following AWS CodeDeploy components: Application : A name that uniquely identifies the application you want to deploy. AWS CodeDeploy uses this name, which functions as a container, to ensure the correct combination of revision, deployment configuration, and deployment group are referenced during a deployment. Deployment group : A set of individual instances, CodeDeploy Lambda deployment configuration settings, or an Amazon ECS service and network details. A Lambda deployment group specifies how to route traffic to a new version of a Lambda function. An Amazon ECS deployment group specifies the service created in Amazon ECS to deploy, a load balancer, and a listener to reroute production traffic to an updated containerized application. An EC2/On-premises deployment group contains individually tagged instances, Amazon EC2 instances in Amazon EC2 Auto Scaling groups, or both. All deployment groups can specify optional trigger, alarm, and rollback settings. Deployment configuration : A set of deployment rules and deployment success and failure conditions used by AWS CodeDeploy during a deployment. Deployment : The process and the components used when updating a Lambda function, a containerized application in an Amazon ECS service, or of installing content on one or more instances. Application revisions : For an AWS Lambda deployment, this is an AppSpec file that specifies the Lambda function to be updated and one or more functions to validate deployment lifecycle events. For an Amazon ECS deployment, this is an AppSpec file that specifies the Amazon ECS task definition, container, and port where production traffic is rerouted. For an EC2/On-premises deployment, this is an archive file that contains source content—source code, webpages, executable files, and deployment scripts—along with an AppSpec file. Revisions are stored in Amazon S3 buckets or GitHub repositories. For Amazon S3, a revision is uniquely identified by its Amazon S3 object key and its ETag, version, or both. For GitHub, a revision is uniquely identified by its commit ID. This guide also contains information to help you get details about the instances in your deployments, to make on-premises instances available for AWS CodeDeploy deployments, to get details about a Lambda function deployment, and to get details about Amazon ECS service deployments. AWS CodeDeploy Information Resources AWS CodeDeploy User Guide AWS CodeDeploy API Reference Guide AWS CLI Reference for AWS CodeDeploy AWS CodeDeploy Developer Forum

Backup Backup is a unified backup service designed to protect Amazon Web Services services and their associated data. Backup simplifies the creation, migration, restoration, and deletion of backups, while also providing reporting and auditing.

The WorkMail Message Flow API provides access to email messages as they are being sent and received by a WorkMail organization.