Multicloud on AWS features
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Use cases
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No matter your use case, AWS delivers tools and guidance to help you succeed with your multicloud strategy, including capabilities to address key use cases such as:
- Mergers and acquisitions: Following a merger or acquisition, enable your combined organization to leverage existing solutions and data from various cloud and software providers.
- Line of business needs: Individual business units may have varied requirements and technical skillsets tuned for specific solutions on specific clouds.
- Contractual requirements: Highly regulated organizations may have customer contractual requirements requiring use of a specific cloud provider.
- Data collaboration: When data must remain private and protected, collaborate with your external partners’ datasets across multiple data sources and clouds without copying or sharing source data.
- Compliance and regulations: Meet compliance needs and digital sovereignty requirements, such as portability and interoperability, between cloud services from different cloud providers.
You can simplify cloud management across environments using one familiar toolset, speed up migrations and application modernization, extend networking across clouds, and gain insights from data anywhere—all through AWS.
Features
Open allCloud management & operations
Monitoring & observability
Generative AI
Analytics
Driving insights from disparate sources in a multicloud environment can require using multiple queries and workarounds to access the data. AWS offers analytics and ML services that allow you to gain insights from all your data, whether it’s stored on AWS or other clouds, on premises, at the edge, in SaaS applications, or in analytics services. Easily connect to data in applications including Adobe, Google Analytics, Google BigQuery, Salesforce, SAP, ServiceNow, and Zendesk and run analytics or machine learning.
You can query and surface insights from data stored in various external data sources—including relational, nonrelational, object, and other cloud data stores—without copying or transforming data with Amazon Athena. You can use Athena to run interactive queries across multiple systems of record, create unified datasets for business intelligence, and prepare data for use in ML training. For example, the Amazon Athena connector for Google BigQuery enables Amazon Athena to run SQL queries on your Google BigQuery data.
With Amazon AppFlow you can automate bi-directional data flows between SaaS applications and AWS services in just a few clicks. Run the data flows at the frequency chosen, whether on a schedule, in response to a business event, or on demand. Simplify data preparation with transformations, partitioning, and aggregation. Automate preparation and registration of your schema with the AWS Glue Data Catalog so you can discover and share data with AWS analytics and machine learning services.
Data
Moving and preparing data in a multicloud environment can require repeatedly running and managing multiple scripts. You can move data between AWS, on-premises file systems, and other cloud storage services using AWS DataSync, a secure service that automates and accelerates the movement of data between storage systems without needing to write and run scripts to manage repeated transfers. With DataSync, you can access data across 12 storage locations spanning other clouds, on-premises, and edge, and move it to and from AWS to support workflows and processing.
Make data preparation easier with AWS Glue, a serverless data integration service. With AWS Glue, you can discover and connect to over 80 diverse data sources, including other cloud databases, such as Google BigQuery, and analytics services. You can also manage your data in a centralized data catalog, and visually create, run, and monitor ETL (extract, transform, and load) pipelines to load data into your data lakes. You can move data bidirectionally between Amazon S3, and either Azure Blob Storage or Azure Dake Lake Storage, via connectors. You can also leverage new database connectors for AWS Glue Apache Spark, including Teradata, SAP HANA, Azure SQL, Azure Cosmos DB, Vertica, and MongoDB.
Want to safely collaborate with your partners without copying or sharing source data, oftentimes with datasets stored outside AWS? With AWS Clean Rooms, you can leverage privacy-enhancing controls to gain insights collaborating with your partners’ datasets across multiple data sources and clouds, such as Amazon S3, Amazon Athena, and Snowflake, with zero ETL (extract, transform, and load) and without needing to copy, share, or move your underlying data.
Networking
Containers
Deploying and configuring a multicloud Kubernetes cluster can be complex. Amazon Elastic Kubernetes Service (EKS) runs upstream Kubernetes and is certified Kubernetes-conformant, so you can use all the existing plug-ins and tooling from the Kubernetes community to save time in development and deployment in multicloud environments. Easily migrate any standard Kubernetes application to Amazon EKS without refactoring your code, and vice-versa, helping speed up migration or deployment in another cloud. Applications running on Amazon EKS are compatible with applications running on any standard Kubernetes environment, whether running in on other clouds or on-premises. And you can view and explore all of your Kubernetes clusters, applications, and associated cloud resources running in multicloud environments in the Amazon EKS console using the Amazon EKS Connector. Additionally, Amazon EKS Hybrid Nodes, Amazon EKS Anywhere, and Amazon ECS Anywhere allow you to manage containerized applications in multicloud and hybrid environments.
Security & Identity
Analyzing security data and managing identities and permissions from across your multicloud environment means having to collect it from different sources and locations. Centralize and analyze security data in multicloud environments to improve the protection of your workloads, applications, and data. AWS Security Lake is the first data lake to support the open standard for security data defined by the Open Cybersecurity Schema Framework (OCSF), which was co-founded by AWS. With Security Lake, you can automatically collect and combine security data from AWS and a broad range of enterprise security data sources that support the OCSF standard. You can use AWS CloudTrail Lake as a single location of immutable user and API activity events for auditing and security investigations, and with AWS Secrets Manager, you can store and manage secrets in multicloud or on-premises workloads from a secure and central place.
Securely manage identities and permissions to AWS resources for your applications and infrastructure running in multicloud environments. With AWS IAM Identity Center, you can create and manage user identities in AWS or connect to your existing identity source, including Microsoft Active Directory, Okta, Ping Identity, JumpCloud, Google Workspace, and Azure Active Directory. You can also provide temporary AWS resource access for your server, container, and application workloads running in multicloud environments with AWS IAM Roles Anywhere.
Open Source at AWS
Since its inception, AWS has been the best place to build and run open source software in the cloud. AWS offers a broad portfolio of managed open source services, allowing customers to choose the right open source solution for their needs with the added advantage of the agility, elasticity, cost savings, and global scale of our cloud.
AWS offers managed versions of popular open source software including Kubernetes, Apache Kafka, Apache Airflow, Grafana, Prometheus, PostgreSQL, MariaDB, MySQL, Jupyter, Envoy, and OpenZFS. Customers can also choose to deploy their preferred open source software on top of the Linux workload of their choice. To assist in this, we provide Amazon Linux, an application environment, and Amazon Linux 2, a Linux operating system, available at no additional cost to customers that offer long-term support with access to the latest open source innovations in Linux.
Additionally, AWS recognizes the importance to our customers of sustaining critical open source projects and has ongoing investments with Linux Foundation projects, such as OpenSearch and Valkey.