关于Anthos在分布式数据平台的作用及多云等效产品的技术问询

Great questions—let’s break this down clearly, since managing scattered data across on-prem and multiple clouds is a common pain point for many teams.

How Anthos Operates in Distributed Data Platforms #

At its core, Anthos is a Kubernetes-based platform that creates a unified control plane across your on-premises infrastructure, GCP, AWS, and Azure. Here’s how it translates to distributed data scenarios:

• Consistent cluster management: Anthos lets you deploy and manage Kubernetes clusters anywhere (on-prem, AWS, Azure) through a single interface. This means your data-related services (like query engines, data pipelines, or caching layers) can run consistently across environments without rework.
• Service mesh for data traffic: Anthos Service Mesh (ASM) handles secure, observable communication between data services across different clouds/on-prem. For example, a query running in GCP can safely pull data from your on-prem Teradata cluster with encrypted traffic and latency monitoring.
• Config and policy enforcement: Anthos Config Management ensures uniform access policies, security rules, and compliance standards for all your data systems. So you don’t have to reconfigure permissions separately for Teradata, Redshift, and Snowflake.

Can Anthos Integrate Teradata, Redshift, Snowflake for Low-Latency Queries/Reporting? #

Anthos itself isn’t a data integration or query tool, but it provides the foundation to deploy and manage tools that do this. Here’s how you’d make it work:

• Deploy data virtualization tools: You can run open-source tools like Trino (or Presto) or GCP’s BigQuery Omni on Anthos clusters. These tools act as a single query layer that connects to Teradata, Redshift, and Snowflake directly, letting users run SQL queries across all datasets without moving data.
• Optimize for low latency: For frequently accessed data, you can deploy caching services (like Redis) on Anthos to store query results or hot datasets. Alternatively, use Anthos Dataflow (a managed Apache Beam service) to sync subsets of data from your sources to a centralized data lake (like GCS) for faster reporting.
• Unified access: Anthos lets you set up single sign-on (SSO) and role-based access control (RBAC) across all your data tools and sources. So your team can use one set of credentials to query any of the datasets via the virtualization layer.

AWS and Azure Equivalents to GCP Anthos #

If you’re looking for similar hybrid/multi-cloud platform capabilities on other clouds, here are the closest matches:

• AWS: The combination of EKS Anywhere (for managing Kubernetes clusters across on-prem, AWS, and other clouds) + AWS App Mesh (service mesh for cross-environment traffic) + AWS Systems Manager (config and policy management) comes closest to Anthos. For data-specific hybrid capabilities, AWS Outposts lets you run AWS services locally, and Redshift Spectrum can query data across different stores—though it’s not a full platform like Anthos.
• Azure: Azure Arc is the direct equivalent. It provides a unified control plane to manage Kubernetes clusters, data services (like Azure SQL Managed Instance), and applications across on-prem, Azure, AWS, and GCP. Azure Arc also integrates with Azure’s data tools (like Synapse Analytics) to enable cross-source querying, similar to how Anthos works with GCP’s data ecosystem.

内容的提问来源于stack exchange，提问作者Arvind Kumar