AWS App Mesh Integrations

Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. Proactively detect and investigate IT infrastructure using a layered security approach. Visualize all infrastructure to plan, predict and mitigate risk. Build graph queries for near-real-time identity fraud pattern detection in financial and purchase transactions.

AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. Config continuously monitors and records your AWS resource configurations and allows you to automate the evaluation of recorded configurations against desired configurations. With Config, you can review changes in configurations and relationships between AWS resources, dive into detailed resource configuration histories, and determine your overall compliance against the configurations specified in your internal guidelines. This enables you to simplify compliance auditing, security analysis, change management, and operational troubleshooting. AWS Config is designed to be your primary tool to perform configuration audit and compliance verification of both your AWS and third-party resources. You can publish the configuration of third-party resources such as GitHub repositories, Microsoft Active Directory resources, or any on-premises server into AWS.

Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications. SQS eliminates the complexity and overhead associated with managing and operating message oriented middleware, and empowers developers to focus on differentiating work. Using SQS, you can send, store, and receive messages between software components at any volume, without losing messages or requiring other services to be available. Get started with SQS in minutes using the AWS console, Command Line Interface or SDK of your choice, and three simple commands. Use Amazon SQS to transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be available. SQS lets you decouple application components so that they run and fail independently, increasing the overall fault tolerance of the system.

AWS Fargate is a serverless compute engine for containers that works with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS). Fargate makes it easy for you to focus on building your applications. Fargate removes the need to provision and manage servers, lets you specify and pay for resources per application, and improves security through application isolation by design. Fargate allocates the right amount of compute, eliminating the need to choose instances and scale cluster capacity. You only pay for the resources required to run your containers, so there is no over-provisioning and paying for additional servers. Fargate runs each task or pod in its own kernel providing the tasks and pods their own isolated compute environment. This enables your application to have workload isolation and improved security by design.

Amazon Elastic Kubernetes Service (Amazon EKS) is a fully managed Kubernetes service. Customers such as Intel, Snap, Intuit, GoDaddy, and Autodesk trust EKS to run their most sensitive and mission-critical applications because of its security, reliability, and scalability. EKS is the best place to run Kubernetes for several reasons. First, you can choose to run your EKS clusters using AWS Fargate, which is serverless compute for containers. Fargate removes the need to provision and manage servers, lets you specify and pay for resources per application, and improves security through application isolation by design. Second, EKS is deeply integrated with services such as Amazon CloudWatch, Auto Scaling Groups, AWS Identity and Access Management (IAM), and Amazon Virtual Private Cloud (VPC), providing you a seamless experience to monitor, scale, and load-balance your applications.

Amazon S3 Glacier and S3 Glacier Deep Archive are a secure, durable, and extremely low-cost Amazon S3 cloud storage classes for data archiving and long-term backup. They are designed to deliver 99.999999999% durability, and provide comprehensive security and compliance capabilities that can help meet even the most stringent regulatory requirements. Customers can store data for as little as $1 per terabyte per month, a significant savings compared to on-premises solutions. To keep costs low yet suitable for varying retrieval needs, Amazon S3 Glacier provides three options for access to archives, from a few minutes to several hours, and S3 Glacier Deep Archive provides two access options ranging from 12 to 48 hours. The S3 Glacier storage classes offer sophisticated integration with AWS CloudTrail to log, monitor, and retain storage API call activities for auditing, and they support three different forms of encryption.

Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions. With Amazon Lex, the same deep learning technologies that power Amazon Alexa are now available to any developer, enabling you to quickly and easily build sophisticated, natural language, conversational bots (“chatbots”). With Amazon Lex, you can build bots to increase contact center productivity, automate simple tasks, and drive operational efficiencies across the enterprise. As a fully managed service, Amazon Lex scales automatically, so you don’t need to worry about managing infrastructure.

Amazon Simple Notification Service (SNS) is a fully managed messaging service for both system-to-system and app-to-person (A2P) communication. It enables you to communicate between systems through publish/subscribe (pub/sub) patterns that enable messaging between decoupled microservice applications or to communicate directly to users via SMS, mobile push and email. The system-to-system pub/sub functionality provides topics for high-throughput, push-based, many-to-many messaging. Using Amazon SNS topics, your publisher systems can fanout messages to a large number of subscriber systems or customer endpoints including Amazon SQS queues, AWS Lambda functions and HTTP/S, for parallel processing. The A2P messaging functionality enables you to send messages to users at scale using either a pub/sub pattern or direct-publish messages using a single API.

Amazon Pinpoint is a flexible and scalable outbound and inbound marketing communications service. You can connect with customers over channels like email, SMS, push, or voice. Amazon Pinpoint is easy to set up, easy to use, and is flexible for all marketing communication scenarios. Segment your campaign audience for the right customer and personalize your messages with the right content. Delivery and campaign metrics in Amazon Pinpoint measure the success of your communications. Amazon Pinpoint can grow with you and scales globally to billions of messages per day across channels. Start easily with just a few clicks in Amazon Pinpoint. Whether you are a marketer or a developer, Amazon Pinpoint is flexible for marketing, bulk, or transactional communications use cases. Marketers can design, orchestrate, and run campaigns visually through the console. Developers can leverage the Amazon Pinpoint APIs for message sending, scheduling campaigns or tracking web and mobile activities.

AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning, and application development. AWS Glue provides all the capabilities needed for data integration so that you can start analyzing your data and putting it to use in minutes instead of months. Data integration is the process of preparing and combining data for analytics, machine learning, and application development. It involves multiple tasks, such as discovering and extracting data from various sources; enriching, cleaning, normalizing, and combining data; and loading and organizing data in databases, data warehouses, and data lakes. These tasks are often handled by different types of users that each use different products. AWS Glue runs in a serverless environment. There is no infrastructure to manage, and AWS Glue provisions, configures, and scales the resources required to run your data integration jobs.

Amazon MQ is a managed message broker service for Apache ActiveMQ that makes it easy to set up and operate message brokers in the cloud. Message brokers allow different software systems–often using different programming languages, and on different platforms–to communicate and exchange information. Amazon MQ reduces your operational load by managing the provisioning, setup, and maintenance of ActiveMQ, a popular open-source message broker. Connecting your current applications to Amazon MQ is easy because it uses industry-standard APIs and protocols for messaging, including JMS, NMS, AMQP, STOMP, MQTT, and WebSocket. Using standards means that in most cases, there’s no need to rewrite any messaging code when you migrate to AWS. With a few clicks in the Amazon MQ Console, Amazon MQ provisions your broker with support for version upgrades, so you can always use the latest version that Amazon MQ supports. Once you configure your broker, your applications can produce and consume messages.

AWS X-Ray helps developers analyze and debug production, distributed applications, such as those built using a microservices architecture. With X-Ray, you can understand how your application and its underlying services are performing to identify and troubleshoot the root cause of performance issues and errors. X-Ray provides an end-to-end view of requests as they travel through your application, and shows a map of your application’s underlying components. You can use X-Ray to analyze both applications in development and in production, from simple three-tier applications to complex microservices applications consisting of thousands of services.

AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages that are ready to deploy. With CodeBuild, you don’t need to provision, manage, and scale your own build servers. CodeBuild scales continuously and processes multiple builds concurrently, so your builds are not left waiting in a queue. You can get started quickly by using prepackaged build environments, or you can create custom build environments that use your own build tools. With CodeBuild, you are charged by the minute for the compute resources you use. With AWS CodeBuild, your build artifacts are encrypted with customer-specific keys that are managed by the AWS Key Management Service (KMS). CodeBuild is integrated with AWS Identity and Access Management (IAM), so you can assign user-specific permissions to your build projects. AWS CodeBuild belongs to a family of AWS Code Services.

Amazon Forecast is a fully managed service that uses machine learning to deliver highly accurate forecasts. Companies today use everything from simple spreadsheets to complex financial planning software to attempt to accurately forecast future business outcomes such as product demand, resource needs, or financial performance. These tools build forecasts by looking at a historical series of data, which is called time series data. For example, such tools may try to predict the future sales of a raincoat by looking only at its previous sales data with the underlying assumption that the future is determined by the past. This approach can struggle to produce accurate forecasts for large sets of data that have irregular trends. Also, it fails to easily combine data series that change over time (such as price, discounts, web traffic, and number of employees) with relevant independent variables like product features and store locations.

Amazon GuardDuty is a threat detection service that continuously monitors for malicious activity and unauthorized behavior to protect your AWS accounts, workloads, and data stored in Amazon S3. With the cloud, the collection and aggregation of account and network activities is simplified, but it can be time consuming for security teams to continuously analyze event log data for potential threats. With GuardDuty, you now have an intelligent and cost-effective option for continuous threat detection in AWS. The service uses machine learning, anomaly detection, and integrated threat intelligence to identify and prioritize potential threats. GuardDuty analyzes tens of billions of events across multiple AWS data sources, such as AWS CloudTrail event logs, Amazon VPC Flow Logs, and DNS logs. With a few clicks in the AWS Management Console, GuardDuty can be enabled with no software or hardware to deploy or maintain.

Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect your sensitive data in AWS. As organizations manage growing volumes of data, identifying and protecting their sensitive data at scale can become increasingly complex, expensive, and time-consuming. Amazon Macie automates the discovery of sensitive data at scale and lowers the cost of protecting your data. Macie automatically provides an inventory of Amazon S3 buckets including a list of unencrypted buckets, publicly accessible buckets, and buckets shared with AWS accounts outside those you have defined in AWS Organizations. Then, Macie applies machine learning and pattern matching techniques to the buckets you select to identify and alert you to sensitive data, such as personally identifiable information (PII).

AWS Storage Gateway is a hybrid cloud storage service that gives you on-premises access to virtually unlimited cloud storage. Customers use Storage Gateway to simplify storage management and reduce costs for key hybrid cloud storage use cases. These include moving tape backups to the cloud, reducing on-premises storage with cloud-backed file shares, providing low latency access to data in AWS for on-premises applications, as well as various migration, archiving, processing, and disaster recovery use cases. To support these use cases, the service provides three different types of gateways – Tape Gateway, File Gateway, and Volume Gateway – that seamlessly connect on-premises applications to cloud storage, caching data locally for low-latency access. Your applications connect to the service through a virtual machine or hardware gateway appliance using standard storage protocols, such as NFS, SMB, and iSCSI.

Amazon ElastiCache allows you to seamlessly set up, run, and scale popular open-Source compatible in-memory data stores in the cloud. Build data-intensive apps or boost the performance of your existing databases by retrieving data from high throughput and low latency in-memory data stores. Amazon ElastiCache is a popular choice for real-time use cases like Caching, Session Stores, Gaming, Geospatial Services, Real-Time Analytics, and Queuing. Amazon ElastiCache offers fully managed Redis and Memcached for your most demanding applications that require sub-millisecond response times. Amazon ElastiCache works as an in-memory data store and cache to support the most demanding applications requiring sub-millisecond response times. By utilizing an end-to-end optimized stack running on customer-dedicated nodes, Amazon ElastiCache provides secure, blazing-fast performance.

Amazon EventBridge is a serverless event bus that makes it easy to connect applications together using data from your own applications, integrated Software-as-a-Service (SaaS) applications, and AWS services. EventBridge delivers a stream of real-time data from event sources, such as Zendesk, Datadog, or Pagerduty, and routes that data to targets like AWS Lambda. You can set up routing rules to determine where to send your data to build application architectures that react in real time to all of your data sources. EventBridge makes it easy to build event-driven applications because it takes care of event ingestion and delivery, security, authorization, and error handling for you. As your applications become more interconnected through events, you need to spend more effort to find events and understand their structure in order to write code to react to those events.

Analyze and visualize security data to rapidly get to the root cause of potential security issues. Amazon Detective makes it easy to analyze, investigate, and quickly identify the root cause of potential security issues or suspicious activities. Amazon Detective automatically collects log data from your AWS resources and uses machine learning, statistical analysis, and graph theory to build a linked set of data that enables you to easily conduct faster and more efficient security investigations. AWS security services like Amazon GuardDuty, Amazon Macie, and AWS Security Hub as well as partner security products can be used to identify potential security issues, or findings. These services are really helpful in alerting you when something is wrong and pointing out where to go to fix it. But sometimes there might be a security finding where you need to dig a lot deeper and analyze more information to isolate the root cause and take action.

IoT data is highly unstructured which makes it difficult to analyze with traditional analytics and business intelligence tools that are designed to process structured data. IoT data comes from devices that often record fairly noisy processes (such as temperature, motion, or sound). The data from these devices can frequently 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 additional, third party data inputs. For example, to help farmers determine when to water their crops, vineyard irrigation systems often enrich moisture sensor data with rainfall data from the vineyard, allowing for more efficient water usage while maximizing harvest yield. AWS IoT Analytics automates each of the difficult steps that are required to analyze data from IoT devices. AWS IoT Analytics is a fully managed and pay-as-you-go service that scales automatically.

As many IoT deployments consist of hundreds of thousands to millions of devices, it is essential to track, monitor, and manage connected device fleets. You need to ensure your IoT devices work properly and securely after they have been deployed. You also need to secure access to your devices, monitor health, detect and remotely troubleshoot problems, and manage software and firmware updates. AWS IoT Device Management makes it easy to securely register, organize, monitor, and remotely manage IoT devices at scale. With AWS IoT Device Management, you can register your connected devices individually or in bulk, and easily manage permissions so that devices remain secure. You can also organize your devices, monitor and troubleshoot device functionality, query the state of any IoT device in your fleet, and send firmware updates over-the-air (OTA)—all through a fully managed web application.

AWS Elemental MediaLive is a broadcast-grade live video processing service. It lets you create high-quality video streams for delivery to broadcast televisions and internet-connected multiscreen devices, like connected TVs, tablets, smart phones, and set-top boxes. The service works by encoding your live video streams in real-time, taking a larger-sized live video source and compressing it into smaller versions for distribution to your viewers. With AWS Elemental MediaLive, you can easily set up streams for both live events and 24x7 channels with advanced broadcasting features, high availability, and pay-as-you-go pricing. AWS Elemental MediaLive lets you focus on creating compelling live video experiences for your viewers without the complexity of building and operating broadcast-grade video processing infrastructure. AWS Elemental MediaLive automates the provisioning and management of all the infrastructure used for video encoding.

Amazon Elastic Transcoder is media transcoding in the cloud. It is designed to be a highly scalable, easy to use and a cost effective way for developers and businesses to convert (or “transcode”) media files from their source format into versions that will playback on devices like smartphones, tablets and PCs. Amazon Elastic Transcoder manages all aspects of the media transcoding process for you transparently and automatically. There’s no need to administer software, scale hardware, tune performance, or otherwise manage transcoding infrastructure. You simply create a transcoding “job” specifying the location of your source media file and how you want it transcoded. Amazon Elastic Transcoder also provides transcoding presets for popular output formats, which means that you don’t need to guess about which settings work best on particular devices. All these features are available via service API, AWS SDKs and the AWS Management Console.

As on the ground microservice practitioners quickly realize, the majority of operational problems that arise when moving to a distributed architecture are ultimately grounded in two areas: networking and observability. It is simply an orders of magnitude larger problem to network and debug a set of intertwined distributed services versus a single monolithic application. Envoy is a self contained, high performance server with a small memory footprint. It runs alongside any application language or framework. Envoy supports advanced load balancing features including automatic retries, circuit breaking, global rate limiting, request shadowing, zone local load balancing, etc. Envoy provides robust APIs for dynamically managing its configuration.

Amazon DevOps Guru is a machine learning (ML)-powered service designed to make it easy to improve the operational performance and availability of an application. DevOps Guru helps detect behaviors that deviate from normal operating patterns, so you can identify operational errors long before they affect your customers. DevOps Guru uses ML models with information collected over years by Amazon.com and AWS Operational Excellence to identify anomalous application behavior (for example, increased latency, error rates, resource limitations, etc.) and helps detect critical errors that could potentially cause service interruptions. When the DevOps Guru identifies a critical issue, it automatically sends an alert and provides a summary of related anomalies, the likely root cause, and context on when and where the issue occurred.

AWS CloudTrail is a service that enables governance, compliance, operational auditing, and risk auditing of your AWS account. With CloudTrail, you can log, continuously monitor, and retain account activity related to actions across your AWS infrastructure. CloudTrail provides event history of your AWS account activity, including actions taken through the AWS Management Console, AWS SDKs, command line tools, and other AWS services. This event history simplifies security analysis, resource change tracking, and troubleshooting. In addition, you can use CloudTrail to detect unusual activity in your AWS accounts. These capabilities help simplify operational analysis and troubleshooting. Detect unauthorized access using the Who, What, and When information in CloudTrail Events. Respond with rules-based EventBridge alerts and automated workflows. Continuously monitor API usage history using machine learning (ML) models to spot unusual activity in your AWS accounts, and determine root cause.

Run code without thinking about servers. Pay only for the compute time you consume. AWS Lambda lets you run code without provisioning or managing servers. You pay only for the compute time you consume. With Lambda, you can run code for virtually any type of application or backend service - all with zero administration. Just upload your code and Lambda takes care of everything required to run and scale your code with high availability. You can set up your code to automatically trigger from other AWS services or call it directly from any web or mobile app. AWS Lambda automatically runs your code without requiring you to provision or manage servers. Just write the code and upload it to Lambda. AWS Lambda automatically scales your application by running code in response to each trigger. Your code runs in parallel and processes each trigger individually, scaling precisely with the size of the workload.

Easily collect, process, and analyze video and data streams in real time. Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin. Amazon Kinesis enables you to ingest, buffer, and process streaming data in real-time, so you can derive insights in seconds or minutes instead of hours or days.

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. No machine learning experience required. There is a treasure trove of potential sitting in your unstructured data. Customer emails, support tickets, product reviews, social media, even advertising copy represents insights into customer sentiment that can be put to work for your business. The question is how to get at it? As it turns out, Machine learning is particularly good at accurately identifying specific items of interest inside vast swathes of text (such as finding company names in analyst reports), and can learn the sentiment hidden inside language (identifying negative reviews, or positive customer interactions with customer service agents), at almost limitless scale. Amazon Comprehend uses machine learning to help you uncover the insights and relationships in your unstructured data.

Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data using open-source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. With EMR you can run Petabyte-scale analysis at less than half of the cost of traditional on-premises solutions and over 3x faster than standard Apache Spark. For short-running jobs, you can spin up and spin down clusters and pay per second for the instances used. For long-running workloads, you can create highly available clusters that automatically scale to meet demand. If you have existing on-premises deployments of open-source tools such as Apache Spark and Apache Hive, you can also run EMR clusters on AWS Outposts. Analyze data using open-source ML frameworks such as Apache Spark MLlib, TensorFlow, and Apache MXNet. Connect to Amazon SageMaker Studio for large-scale model training, analysis, and reporting.

AWS CodeDeploy is a fully managed deployment service that automates software deployments to a variety of compute services such as Amazon EC2, AWS Fargate, AWS Lambda, and your on-premises servers. 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. You can use AWS CodeDeploy to automate software deployments, eliminating the need for error-prone manual operations. The service scales to match your deployment needs. AWS CodeDeploy is platform and language agnostic, works with any application, and provides the same experience whether you’re deploying to Amazon EC2, AWS Fargate, or AWS Lambda. You can easily reuse your existing setup code. CodeDeploy can also integrate with your existing software release process or continuous delivery toolchain (e.g., AWS CodePipeline, GitHub, Jenkins).

Amazon GameLift is a dedicated game server hosting solution that deploys, operates, and scales cloud servers for multiplayer games. Whether you’re looking for a fully managed solution, or just the feature you need, GameLift leverages the power of AWS to deliver the best latency possible, low player wait times, and maximum cost savings. Amazon GameLift leverages the AWS global infrastructure for managing game servers. Match players into game sessions and autoscale that start one, hundreds, or even thousands of instances simultaneously, without thinking about scaling with fluctuating player demand. Game services provide basic multiplayer game support, like matchmaking, session directory, player data, and player analytics. With AWS, you can use services like AWS Lambda that provide serverless, scalable, and flexible computing, or features in services like Amazon GameLift FlexMatch, for matchmaking.

AWS WAF is a web application firewall that helps protect your web applications or APIs against common web exploits that may affect availability, compromise security, or consume excessive resources. AWS WAF gives you control over how traffic reaches your applications by enabling you to create security rules that block common attack patterns, such as SQL injection or cross-site scripting, and rules that filter out specific traffic patterns you define. You can get started quickly using Managed Rules for AWS WAF, a pre-configured set of rules managed by AWS or AWS Marketplace Sellers. The Managed Rules for WAF address issues like the OWASP Top 10 security risks. These rules are regularly updated as new issues emerge. AWS WAF includes a full-featured API that you can use to automate the creation, deployment, and maintenance of security rules. With AWS WAF, you pay only for what you use. The pricing is based on how many rules you deploy and how many web requests your application receives.

AWS Device Farm is an application testing service that lets you improve the quality of your web and mobile apps by testing them across an extensive range of desktop browsers and real mobile devices; without having to provision and manage any testing infrastructure. The service enables you to run your tests concurrently on multiple desktop browsers or real devices to speed up the execution of your test suite, and generates videos and logs to help you quickly identify issues with your app. Test your app in parallel against a massive collection of physical devices in the AWS Cloud. Use one of our built-in frameworks, to test your applications without having to write or maintain test scripts, or use one of our supported automation testing frameworks. Gesture, swipe, and interact with devices in real time, directly from your web browser. Run your Selenium tests in parallel on multiple versions of Chrome, Internet Explorer, and Firefox, that are hosted in the AWS Cloud.

Centrally view and manage security alerts and automate security checks. AWS Security Hub gives you a comprehensive view of your security alerts and security posture across your AWS accounts. There are a range of powerful security tools at your disposal, from firewalls and endpoint protection to vulnerability and compliance scanners. But oftentimes this leaves your team switching back-and-forth between these tools to deal with hundreds, and sometimes thousands, of security alerts every day. With Security Hub, you now have a single place that aggregates, organizes, and prioritizes your security alerts, or findings, from multiple AWS services, such as Amazon GuardDuty, Amazon Inspector, Amazon Macie, AWS Identity and Access Management (IAM) Access Analyzer, and AWS Firewall Manager, as well as from AWS Partner solutions. AWS Security Hub continuously monitors your environment using automated security checks based on the AWS best practices and industry standards.

AWS Certificate Manager is a service that lets you easily provision, manage, and deploy public and private Secure Sockets Layer/Transport Layer Security (SSL/TLS) certificates for use with AWS services and your internal connected resources. SSL/TLS certificates are used to secure network communications and establish the identity of websites over the Internet as well as resources on private networks. AWS Certificate Manager removes the time-consuming manual process of purchasing, uploading, and renewing SSL/TLS certificates. SSL, and its successor TLS, are industry standard protocols for encrypting network communications and establishing the identity of websites over the Internet. SSL/TLS provides encryption for sensitive data in transit and authentication using SSL/TLS certificates to establish the identity of your site and secure connections between browsers and applications and your site.

AWS IoT Core lets you connect IoT devices to the AWS cloud without the need to provision or manage servers. AWS IoT Core can support billions of devices and trillions of messages, and can process and route those messages to AWS endpoints and to other devices reliably and securely. With AWS IoT Core, your applications can keep track of and communicate with all your devices, all the time, even when they aren’t connected. AWS IoT Core also makes it easy to use AWS and Amazon services like AWS Lambda, Amazon Kinesis, Amazon S3, Amazon SageMaker, Amazon DynamoDB, Amazon CloudWatch, AWS CloudTrail, Amazon QuickSight, and Alexa Voice Service to build IoT applications that gather, process, analyze and act on data generated by connected devices, without having to manage any infrastructure. AWS IoT Core allows you to connect any number of devices to the cloud and to other devices without requiring you to provision or manage servers.

Businesses and organizations need to plan and set expectations around cloud costs. However, the cloud agility requires you to adapt your forecasting processes and tools to match the dynamic nature of your usage. Set up custom budgets and stay informed of how your cost and usage progress and respond quickly when cost or usage exceeds threshold. AWS Budgets allows you to set custom budgets to track your cost and usage from the simplest to the most complex use cases. With AWS Budgets, you can choose to be alerted by email or SNS notification when actual or forecasted cost and usage exceed your budget threshold, or when your actual RI and Savings Plans' utilization or coverage drops below your desired threshold. Create annual, quarterly, monthly, or even daily budgets depending on your business needs.

AWS Cost Explorer has an easy-to-use interface that lets you visualize, understand, and manage your AWS costs and usage over time. Get started quickly by creating custom reports that analyze cost and usage data. Analyze your data at a high level (for example, total costs and usage across all accounts) or dive deeper into your cost and usage data to identify trends, pinpoint cost drivers, and detect anomalies. A set of default reports are included to help you quickly gain insight into your cost drivers and usage trends. Set a custom time period, and determine whether you would like to view your data at a monthly or daily level of granularity. Dig deeper into your data by taking advantage of filtering and grouping functionality, using a variety of available dimensions. Use forecasting to get a better idea of your what your costs and usage may look like in the future, so that you can plan ahead.

Amazon Elastic Block Store (EBS) is an easy to use, high-performance, block-storage service designed for use with Amazon Elastic Compute Cloud (EC2) for both throughput and transaction intensive workloads at any scale. A broad range of workloads, such as relational and non-relational databases, enterprise applications, containerized applications, big data analytics engines, file systems, and media workflows are widely deployed on Amazon EBS. You can choose from six different volume types to balance optimal price and performance. You can achieve single-digit-millisecond latency for high-performance database workloads such as SAP HANA or gigabyte per second throughput for large, sequential workloads such as Hadoop. You can change volume types, tune performance, or increase volume size without disrupting your critical applications, so you have cost-effective storage when you need it.

Amazon Personalize enables developers to build applications with the same machine learning (ML) technology used by Amazon.com for real-time personalized recommendations – no ML expertise required. Amazon Personalize makes it easy for developers to build applications capable of delivering a wide array of personalization experiences, including specific product recommendations, personalized product re-ranking, and customized direct marketing. Amazon Personalize is a fully managed machine learning service that goes beyond rigid static rule based recommendation systems and trains, tunes, and deploys custom ML models to deliver highly customized recommendations to customers across industries such as retail and media and entertainment. Amazon Personalize provisions the necessary infrastructure and manages the entire ML pipeline, including processing the data, identifying features, using the best algorithms, and training, optimizing, and hosting the models.

Amazon Virtual Private Cloud (Amazon VPC) is a service that lets you launch AWS resources in a logically isolated virtual network that you define. You have complete control over your virtual networking environment, including selection of your own IP address range, creation of subnets, and configuration of route tables and network gateways. You can use both IPv4 and IPv6 for most resources in your virtual private cloud, helping to ensure secure and easy access to resources and applications. As one of AWS's foundational services, Amazon VPC makes it easy to customize your VPC's network configuration. You can create a public-facing subnet for your web servers that have access to the internet. It also lets you place your backend systems, such as databases or application servers, in a private-facing subnet with no internet access.

The service combines advanced video and audio capabilities with a simple web services interface and pay-as-you-go pricing. With AWS Elemental MediaConvert, you can focus on delivering compelling media experiences without having to worry about the complexity of building and operating your own video processing infrastructure. AWS Elemental MediaConvert lets you use a wide range of internet and professional media formats to produce high-quality video outputs that look great on any device. With support for ultra-high definition resolutions, high dynamic range video, graphic overlays, advanced audio features, content protection, and closed captioning, AWS Elemental MediaConvert offers a full set of tools to deliver high-quality viewing experiences. AWS Elemental MediaConvert does not require any set up, management, or maintenance of underlying infrastructure. Process video files and clips to prepare on-demand content for distribution or archiving.

Easily store, share, and deploy your container software anywhere. Push container images to Amazon ECR without installing or scaling infrastructure, and pull images using any management tool. Share and download images securely over Hypertext Transfer Protocol Secure (HTTPS) with automatic encryption and access controls. Access and distribute your images faster, reduce download times, and improve availability using a scalable, durable architecture. Amazon ECR is a fully managed container registry offering high-performance hosting, so you can reliably deploy application images and artifacts anywhere. Meet your organization’s image compliance security requirements using insights from common vulnerabilities and exposures (CVEs) and the Common Vulnerability Scoring System (CVSS). Publish containerized applications with a single command and easily integrate your self-managed environments.

AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis. A data lake lets you break down data silos and combine different types of analytics to gain insights and guide better business decisions. Setting up and managing data lakes today involves a lot of manual, complicated, and time-consuming tasks. This work includes loading data from diverse sources, monitoring those data flows, setting up partitions, turning on encryption and managing keys, defining transformation jobs and monitoring their operation, reorganizing data into a columnar format, deduplicating redundant data, and matching linked records. Once data has been loaded into the data lake, you need to grant fine-grained access to datasets, and audit access over time across a wide range of analytics and machine learning (ML) tools and services.

Amazon Comprehend Medical is a HIPAA-eligible natural language processing (NLP) service that uses machine learning to extract health data from medical text–no machine learning experience is required. Much of health data today is in free-form medical text like doctors’ notes, clinical trial reports, and patient health records. Manually extracting the data is a time consuming process, while automated rule-based attempts to extract the data don’t capture the full story as they fail to take context into account. As a result, the data remains unusable in large-scale analytics needed to advance the healthcare and life sciences industry and improve patient outcomes and create efficiencies.

Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. As a document database, Amazon DocumentDB makes it easy to store, query, and index JSON data. Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data. Amazon DocumentDB is designed for 99.99% availability and replicates six copies of your data across three AWS Availability Zones (AZs).

Reliable, secure, and flexible transport for live video. Prepare file-based video assets for on-demand broadcast and multiscreen delivery. Convert inputs into live outputs for broadcast and multiscreen video delivery. Originate and package live and on-demand video content. Originate and store video assets for live or on-demand media workflows. Personalize and monetize multiscreen video content with server-side ad insertion. Convert inputs into live outputs for broadcast and multiscreen video delivery. Prepare file-based content for on-demand broadcast and multiscreen delivery. Manage video networks for live and on-demand content. Connect a live video source to AWS Elemental MediaLive. The most purpose-built capabilities of any cloud to help customers transform content production, media supply chain, broadcast, direct-to-consumer & streaming, and analytics. Customers reinventing media and entertainment with AWS.