Mock sample for your project: AuthorizationManagementClient API

Use these REST APIs for performing retrieving a collection of policy snippets available in Azure API Management deployment.

These APIs allow end users to operate on Azure Machine Learning Team Account resources. They support CRUD operations for Azure Machine Learning Team Accounts.

The Admin Storage Management Client.

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

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

The Update Admin Management Client.

REST API for Azure Blockchain Service

The Admin Storage Management Client.

A client for issuing REST requests to the Azure Batch service.

This is the API Reference for AWS Network Firewall. This guide is for developers who need detailed information about the Network Firewall API actions, data types, and errors. The REST API requires you to handle connection details, such as calculating signatures, handling request retries, and error handling. For general information about using the AWS REST APIs, see AWS APIs. To access Network Firewall using the REST API endpoint: https://network-firewall..amazonaws.com Alternatively, you can use one of the AWS SDKs to access an API that's tailored to the programming language or platform that you're using. For more information, see AWS SDKs. For descriptions of Network Firewall features, including and step-by-step instructions on how to use them through the Network Firewall console, see the Network Firewall Developer Guide. Network Firewall is a stateful, managed, network firewall and intrusion detection and prevention service for Amazon Virtual Private Cloud (Amazon VPC). With Network Firewall, you can filter traffic at the perimeter of your VPC. This includes filtering traffic going to and coming from an internet gateway, NAT gateway, or over VPN or AWS Direct Connect. Network Firewall uses rules that are compatible with Suricata, a free, open source intrusion detection system (IDS) engine. For information about Suricata, see the Suricata website. You can use Network Firewall to monitor and protect your VPC traffic in a number of ways. The following are just a few examples: Allow domains or IP addresses for known AWS service endpoints, such as Amazon S3, and block all other forms of traffic. Use custom lists of known bad domains to limit the types of domain names that your applications can access. Perform deep packet inspection on traffic entering or leaving your VPC. Use stateful protocol detection to filter protocols like HTTPS, regardless of the port used. To enable Network Firewall for your VPCs, you perform steps in both Amazon VPC and in Network Firewall. For information about using Amazon VPC, see Amazon VPC User Guide. To start using Network Firewall, do the following: (Optional) If you don't already have a VPC that you want to protect, create it in Amazon VPC. In Amazon VPC, in each Availability Zone where you want to have a firewall endpoint, create a subnet for the sole use of Network Firewall. In Network Firewall, create stateless and stateful rule groups, to define the components of the network traffic filtering behavior that you want your firewall to have. In Network Firewall, create a firewall policy that uses your rule groups and specifies additional default traffic filtering behavior. In Network Firewall, create a firewall and specify your new firewall policy and VPC subnets. Network Firewall creates a firewall endpoint in each subnet that you specify, with the behavior that's defined in the firewall policy. In Amazon VPC, use ingress routing enhancements to route traffic through the new firewall endpoints.

The Microsoft Azure management API provides create, read, update, and delete functionality for Azure MariaDB resources including servers, databases, firewall rules, VNET rules, log files and configurations with new business model.

Amazon Timestream is a fast, scalable, fully managed time series database service that makes it easy to store and analyze trillions of time series data points per day. With Timestream, you can easily store and analyze IoT sensor data to derive insights from your IoT applications. You can analyze industrial telemetry to streamline equipment management and maintenance. You can also store and analyze log data and metrics to improve the performance and availability of your applications. Timestream is built from the ground up to effectively ingest, process, and store time series data. It organizes data to optimize query processing. It automatically scales based on the volume of data ingested and on the query volume to ensure you receive optimal performance while inserting and querying data. As your data grows over time, Timestream’s adaptive query processing engine spans across storage tiers to provide fast analysis while reducing costs.

Amplify enables developers to develop and deploy cloud-powered mobile and web apps. The Amplify Console provides a continuous delivery and hosting service for web applications. For more information, see the Amplify Console User Guide. The Amplify Framework is a comprehensive set of SDKs, libraries, tools, and documentation for client app development. For more information, see the Amplify Framework.

Amazon Web Services X-Ray provides APIs for managing debug traces and retrieving service maps and other data created by processing those traces.

Directory Service Directory Service is a web service that makes it easy for you to setup and run directories in the Amazon Web Services cloud, or connect your Amazon Web Services resources with an existing self-managed Microsoft Active Directory. This guide provides detailed information about Directory Service operations, data types, parameters, and errors. For information about Directory Services features, see Directory Service and the Directory Service Administration Guide. Amazon Web Services provides SDKs that consist of libraries and sample code for various programming languages and platforms (Java, Ruby, .Net, iOS, Android, etc.). The SDKs provide a convenient way to create programmatic access to Directory Service and other Amazon Web Services services. For more information about the Amazon Web Services SDKs, including how to download and install them, see Tools for Amazon Web Services.

Azure Enterprise Knowledge Graph Service is a platform for creating knowledge graphs at scale.

You can use the Cost Explorer API to programmatically query your cost and usage data. You can query for aggregated data such as total monthly costs or total daily usage. You can also query for granular data. This might include the number of daily write operations for Amazon DynamoDB database tables in your production environment. Service Endpoint The Cost Explorer API provides the following endpoint: https://ce.us-east-1.amazonaws.com For information about the costs that are associated with the Cost Explorer API, see Amazon Web Services Cost Management Pricing.

AWS Auto Scaling Use AWS Auto Scaling to create scaling plans for your applications to automatically scale your scalable AWS resources. API Summary You can use the AWS Auto Scaling service API to accomplish the following tasks: Create and manage scaling plans Define target tracking scaling policies to dynamically scale your resources based on utilization Scale Amazon EC2 Auto Scaling groups using predictive scaling and dynamic scaling to scale your Amazon EC2 capacity faster Set minimum and maximum capacity limits Retrieve information on existing scaling plans Access current forecast data and historical forecast data for up to 56 days previous To learn more about AWS Auto Scaling, including information about granting IAM users required permissions for AWS Auto Scaling actions, see the AWS Auto Scaling User Guide.

Pinpoint SMS and Voice Messaging public facing APIs

Batch Using Batch, you can run batch computing workloads on the Cloud. Batch computing is a common means for developers, scientists, and engineers to access large amounts of compute resources. Batch uses the advantages of this computing workload to remove the undifferentiated heavy lifting of configuring and managing required infrastructure. At the same time, it also adopts a familiar batch computing software approach. Given these advantages, Batch can help you to efficiently provision resources in response to jobs submitted, thus effectively helping you to eliminate capacity constraints, reduce compute costs, and deliver your results more quickly. As a fully managed service, Batch can run batch computing workloads of any scale. Batch automatically provisions compute resources and optimizes workload distribution based on the quantity and scale of your specific workloads. With Batch, there's no need to install or manage batch computing software. This means that you can focus your time and energy on analyzing results and solving your specific problems.