2026

October 10, 2026 - AI Data Exploration Adds Multi-Source and Multi-Engine DataAgent

Dear MaxCompute users,

The AI Data Explorer client adds a multi-source and multi-engine DataAgent. AI Query can now jointly analyze offline data warehouse data in MaxCompute, real-time data in Hologres and StarRocks, vector data in Milvus, object files in OSS, and local business documents. Supporting capabilities include multi-engine SQL queries, a Milvus retrieval builder, OSS object storage management, and knowledge and memory. The capabilities are as follows:

• Multi-Source Data Access and Catalog Browsing

  Create and manage connections to MaxCompute (OAuth, no AccessKey required), Hologres, StarRocks, Milvus, and Object Storage Service (OSS) in the data source connection panel. MaxCompute and OSS support AccessKey authentication and Security Token Service (STS) temporary credential authentication. OSS can also connect to S3-compatible storage through a custom endpoint. The Catalog displays the resource hierarchy that corresponds to each data source type, such as projects, databases, schemas, tables, collections, and buckets. On a table or collection node, generate a query statement or view its details.

• Multi-Engine SQL Queries and Result Analysis

  The SQL editor supports MaxCompute ODPS SQL, Hologres PostgreSQL-compatible SQL, and StarRocks MySQL-compatible SQL. After a query runs, view MaxCompute execution logs and Logview, or Hologres and StarRocks job monitoring. Query results can be displayed in table, chart, pivot, and quality analysis views, and charts can be pinned to a data dashboard for further analysis.

• Milvus Retrieval Builder

  Generate Milvus JSON operation scripts from a form. Four modes are supported: search by ID, full-text search, conditional query, and get by ID. After selecting a collection and specifying an anchor ID, query text, filter expression, or ID list, write the script to the editor or run it directly. Retrieval results support vector analysis views such as distance distribution, nearest neighbors, principal component analysis (PCA), and heatmaps.

• OSS Object Storage Management

  On the OSS bucket management page, browse objects in column, list, or grid view. Create folders, upload, download, rename, delete, and preview files, and view transfer progress. AI Query can list buckets and objects, read file samples, and generate MaxCompute query SQL or external table DDL.

• Knowledge and Memory

  Add a local folder to build a knowledge space. After synchronization, search documents in natural language, view cited snippets grouped by document, and preview the source files. When files change, synchronize them manually or on a schedule. Memory stores preferences, facts, and business conventions that can be reused across sessions. Memories can be saved by AI during a conversation or created manually, and support search, tag filtering, and pinning.

• Integrated Analysis with AI Query

  Based on the question, AI Query uses the available data source connections, Catalog, knowledge spaces, and memories to run SQL queries, vector searches, full-text searches, or file reads. It then combines query results, cited snippets, and visualizations, and supports follow-up questions about metric definitions, anomaly sources, or breakdown dimensions. Write, delete, and file modification operations must be confirmed in an approval card.

  The multi-source and multi-engine DataAgent in AI Query is recommended for users who need to compare metric definitions between offline and real-time data, interpret business metrics together with business documents, or run semantic recall first and then validate conclusions against detailed data.

For more information, see Multi-source, multi-engine DataAgent.

If you have any questions or need assistance, please contact us by submitting a ticket.

Thank you for your understanding and support of MaxCompute!

September 1, 2026 - AI Data Exploration Client Capability Upgrade

Dear MaxCompute users,

The AI Data Explorer client has been upgraded with new capabilities, including MaxFrame Notebook, dbt integration, data dashboards, workplace collaboration, semantic package management, and multimodal dataset management, further enhancing the unified experience for data development and AI applications. The new capabilities are as follows:

• MaxFrame Notebook / Python UDF Development

  Develop MaxFrame distributed jobs in a notebook interface within the client. You can write and run code cell by cell, preview outputs and target table data in real time, and benefit from pre-execution static checks for common issues such as missing execute() calls and full-table scans. You can also generate complete jobs from natural language prompts using AI. Python UDFs allow you to encapsulate row-level logic that is difficult to express in SQL into reusable functions and call them directly in SQL statements.

• dbt and MaxCompute Ecosystem Integration

  Integrate dbt data transformation workflows with MaxCompute. Manage SQL logic, dependencies, and lineage in a model-based approach, and edit, run, and review compilation results within the client.

• Data Dashboard

  Persist SQL query results as dashboards with multiple chart types, cross-chart interactive filtering, parameterized queries, and drill-down capabilities. Dashboards can also be generated from query results with one click using AI.

• Workplace Collaboration

  Connect to workplace collaboration tools such as DingTalk to share query results, reports, and dashboards directly to collaboration platforms, bringing data insights into team workflows.

• Semantic Package Management and Application

  Consolidate business metric definitions, indicator specifications, and table relationships into semantic packages for AI reuse, ensuring that natural language query results align with actual business definitions.

• Multimodal Dataset Management

  Manage unstructured data such as images, audio, and video in tables using the Blob column type. Upload, preview, and batch-process multimodal data, sharing a single data foundation for both structured analysis and multimodal processing.

If you have any questions or need assistance, please contact us by submitting a ticket.

Thank you for your understanding and support of MaxCompute!

August 17, 2026 - PyODPS discontinued maintenance of odps.apis.storage_api_v2 starting from 0.13.1

Dear MaxCompute users,

Starting from PyODPS version 0.13.1, the odps.apis.storage_api_v2 module is officially discontinued. This module will no longer receive feature updates, bug fixes, or compatibility adaptations, and will be removed in a future version.

• Impact scope

  This only affects code that directly imports odps.apis.storage_api_v2. Released versions 0.13.1 and earlier can still be installed and run normally, but no further fixes will be provided for any issues encountered. Once you upgrade to a version that removes this module, the affected code will fail with an ImportError and cannot start.

• Recommended actions

  Please check your production jobs and internal tools for any references to this module and include them in your deprecation plan. Before completing the migration, we recommend pinning your PyODPS version (for example, specifying pyodps<=0.13.1 in your dependencies) to prevent job disruptions caused by upgrades.

If you have any questions or need assistance, contact us by submitting a ticket.

Thank you for your understanding and support of MaxCompute!

July 27, 2026 - Announcement on the regional availability of the official version of MaxAgent, the MaxCompute AI assistant

Dear MaxCompute users,

The official version of MaxAgent, the MaxCompute AI assistant, will be released in the China (Chengdu), China (Shenzhen), China (Zhangjiakou), China (Ulanqab), China (Beijing), China (Hangzhou), and China (Shanghai) regions starting from Thursday, July 30, 2026 (UTC+8).

This release introduces the following changes:

• The beta version will be discontinued at the same time.

• The new version is available only after you activate the service. After you activate the standard edition, a fixed amount of free Credits is granted each month (we recommend that you select auto-renewal upon activation). When the free quota is used up, you can purchase Credits packs to continue using the service. For billing details, see https://icms.alibaba-inc.com/content/maxcompute/maxcompute?l=2&m=16044&n=6748909.

• The new version of MaxAgent enhances job diagnostics creation and adds multiple O&M scenarios to improve O&M efficiency. For more information, see MaxAgent.

Going forward, MaxAgent will continue to expand its O&M and management capabilities, and Data Agent support is coming soon.

If you have any questions or need assistance, contact us by submitting a ticket.

Thank you for your understanding and support of MaxCompute!

July 22, 2026 - MaxCompute Graph End of Maintenance

Dear MaxCompute users,

After a comprehensive review of feature usage and product roadmap, MaxCompute Graph will enter end of maintenance on July 22, 2026 (Wednesday, Beijing Time). Starting from this date, MaxCompute Graph will no longer receive new feature development, bug fixes, or routine maintenance support.

Existing Graph jobs will continue to run during the transition period, but we recommend migrating to alternative solutions as soon as possible. Related documentation will remain available for reference.

If you have any questions or need assistance, submit a ticket.

Thank you for your understanding and continued support of MaxCompute.

July 13, 2026 - MaxCompute Append Delta Table - Hash Cluster Release

Dear MaxCompute users,

MaxCompute now supports Hash Cluster in the Append Delta Table format, combining incremental data processing capabilities with improved query performance.

This feature is suitable for the following scenarios:

• Equality filter queries: Perform point lookups or equality filtering on specific columns to reduce the amount of data scanned.

• Equality JOIN / GROUP BY: Join or aggregate multiple tables on the same key to reduce Shuffle overhead.

For more information, see Append table - Hash cluster (Invitation only).

If you have any questions or need assistance, submit a ticket.

Thank you for your understanding and continued support of MaxCompute.

June 30, 2026 - Access Behavior Change for SQL UDF, Spark, and MaxFrame Jobs to OSS Intranet

Dear MaxCompute users,

Starting June 30, 2026 (Tuesday, Beijing Time), MaxCompute will block SQL UDF, Spark, and MaxFrame jobs from directly accessing OSS intranet addresses. If you need to access OSS intranet, configure access using the following solution. Failure to configure this may result in failed access to OSS intranet addresses. To access OSS VPC addresses, follow these steps:

1. Create a network connection. For more information, see Create the network connection.

2. Configure the following parameters:

   -- For SQL UDF:
   SET odps.session.networklink=networklink_name;
   
   -- For MaxCompute Spark:
   spark.hadoop.odps.cupid.eni.enable = true
   # Format: region:vpcid. vpcid is the target VPC ID used when setting up the dedicated connection.
   spark.hadoop.odps.cupid.eni.info = regionid:vpc-**********
   
   -- For MaxFrame,Add the following parameter in the UDF
   @with_network_options(vpc_network_link="networklink_name")
    def xxx():
        pass
   

3. Once the network connection is created and the networklink parameter is configured, you can access OSS intranet addresses.

If you have any questions or need assistance, submit a ticket.

Thank you for your understanding and continued support of MaxCompute.

June 17, 2026 - Tunnel Java SDK Version Upgrade Recommendation

Dear MaxCompute users,

To improve upload link stability and exception recovery, the latest Tunnel Java SDK includes exception detection and fast reconnection optimizations for server-side failover scenarios. Some projects are using earlier SDK versions that are susceptible to the following risks. Evaluate the impact and upgrade as soon as possible.

1. Background

   When using Stream Tunnel to upload data, if a server-side failover event occurs (including but not limited to unexpected node restarts or unplanned shutdowns), earlier SDK versions lack the ability to quickly detect such exceptions. This can cause prolonged 502 errors on the client side, affecting upload job stability. The latest SDK version includes targeted optimizations for this scenario to shorten the duration of 502 errors and reduce the impact on upstream services.

2. Impact

   All users who use Tunnel Java SDK for Stream Tunnel uploads, including but not limited to those who directly integrate the Java SDK or write to MaxCompute through Flink or other products.

3. Recommendations

   Upgrade to the following version baselines based on your setup:

   • Tunnel Java SDK: upgrade to version 0.51 or later.

   • Flink: upgrade to VVR 11.x or later.

Validate job compatibility in a staging environment before switching to production to ensure business continuity.

If you have any questions or need assistance during the upgrade, submit a ticket.

Thank you for your continued support of MaxCompute.

June 10, 2026 - PyODPS 0.13.0 Release Changes

Dear MaxCompute users,

PyODPS 0.13.0 and later versions include the following changes. Please evaluate the impact on your workloads and prepare for migration accordingly.

1. End of Python 2.7 Support

PyODPS 0.13.0 and later versions no longer support the Python 2.7 runtime. If you are currently using PyODPS with Python 2.7, please evaluate your workloads and migrate to Python 3 at your earliest convenience.

2. Removal of Mars Support

As the MaxCompute Mars framework has been decommissioned, PyODPS 0.13.0 and later versions no longer include Mars-related functionality. If you require distributed DataFrame or Tensor computing capabilities, consider migrating to MaxFrame, the MaxCompute distributed AI computing framework with a native Python development ecosystem.

If you have any questions or need assistance, submit a ticket.

Thank you for your continued support of PyODPS and the MaxCompute ecosystem.

June 9, 2026 - MaxCompute Agentic ecosystem tools launched

Dear MaxCompute users,

MaxCompute officially launches the Agentic ecosystem toolkit, which includes five components: AI Data Explorer, MCP Server (MCMCP), MaxCompute Skills, CatalogAPI SDK, and MaxCompute CLI. Together, they cover the full spectrum from desktop interactive analytics to AI Agent automated integration.

1. AI Data Explorer

A desktop data development and analytics tool that integrates SQL development, Catalog browsing, visual analytics, and AI-powered data exploration. Key features include:

• SQL development environment: syntax highlighting, intelligent auto-completion, formatting, multi-file management, and query history.

• Data visualization: 12 chart types, pivot tables, and data quality analysis.

• AI data exploration: conversation mode and Agent mode for natural-language-driven data analysis.

• Data management: CSV, Excel, and Parquet import/export, Blob file browsing, and WebDAV mounting.

• Supported on macOS 12.3+ (Apple Silicon) and Windows 10+ (64-bit).

If you want to query data using natural language and SQL, and frequently import or export data, the AI Data Explorer is recommended as an all-in-one SQL IDE, Data Agent, and multimodal data management tool.

For more information, see Get started with the AI data exploration client.

2. MCP Server (MCMCP)

An AI Agent data service access layer built on the Model Context Protocol (MCP). It enables agents to directly perform large-scale data analytics and intelligent O&M. Core capabilities include:

• Catalog metadata browsing and natural language search.

• Table management: creation, data insertion, and metadata updates.

• Read-only SQL analytics: cost estimation, asynchronous execution, and result retrieval, with server-side read-only enforcement.

• Multiple authentication methods: AccessKey pair, STS, Credentials URI, ECS RAM Role, and default credential chain.

• Compatible with OpenClaw, DataWorks Agent, Qwen Code, QoderWork, MaxAgent, and other Agent clients.

If you want to use your own desktop Agent to access MaxCompute for data analytics and O&M, MCMCP combined with scenario-specific Skills is recommended.

For more information, see MaxCompute MCP service guide.

3. MaxCompute Skills

A general-purpose skill pack for AI Agents that provides semantic capabilities specific to the MaxCompute domain. It includes:

• Information Schema semantic pack: designed for system-level O&M, with support for storage pressure diagnostics, cost analysis, job failure analysis, permission auditing, and hot table monitoring.

• Common command sets and development templates to lower the barrier for Agent-driven MaxCompute operations.

If you want to use your own desktop Agent to access MaxCompute for data analytics and O&M, MCMCP combined with scenario-specific Skills is recommended.

For more information, see MaxCompute MCP service guide.

4. CatalogAPI SDK

A RESTful SDK (current version: v0.2.2) for MaxCompute data catalog management. Available for Java and Python, it covers the following metadata resource management capabilities:

• Table management: create, query, update, and delete internal and external tables.

• Connection management: configure connections for external data sources such as OSS and OTS.

• Permissions and data security: fine-grained access control through roles and policies, column-level permissions with taxonomy policy tags, and dynamic data masking with DataPolicy.

• Metadata crawling: automatic discovery and crawling of external data source metadata through DataScan.

• Model management: multi-version management of machine learning model metadata.

For more information, see CatalogAPI SDK User Guide.

5. MaxCompute CLI

A command-line tool (command name: maxc) invoked through the Alibaba Cloud CLI as aliyun maxc. It is designed for script automation and AI Agent integration:

• Structured JSON output for easy programmatic parsing.

• Supported on Linux, macOS, and Windows.

• Distributed through the Alibaba Cloud CLI. Install or update the Alibaba Cloud CLI to get started.

If you want to use an Agent to schedule and execute data jobs, the MaxCompute CLI is recommended.

For more information, see MaxCompute CLI.

If you have any questions or need assistance, submit a ticket.

Thank you for your continued support of MaxCompute.

April 29, 2026 - Behavior change for MaxFrame groupby apply_chunk

Dear MaxCompute users,

Starting from MaxFrame SDK 2.6, the behavior of the DataFrameGroupBy.mf.apply_chunk method is changing. This update simplifies the index parameter and unifies behavior across the DPE and MaxCompute SQL engines. The new behavior is controlled by the prepend_index_group_keys parameter, which defaults to False for backward compatibility but will switch to True in a future release.

• Changes:

  • Simplified index parameter: The index parameter now represents only the index type of the user function output and no longer needs to include group keys. The final index composition depends on the group_keys and as_index parameters of the groupby function.

  • Unified engine behavior: In both the DPE and MaxCompute SQL engines, the input DataFrame passed to user-defined functions no longer includes group keys by default, eliminating the previous behavioral inconsistency between the two engines.

  For detailed migration steps and code examples, see Release notes.

• Scope of impact:

  MaxFrame users who use the groupby.mf.apply_chunk method. If you do not use this method, this change does not affect your workloads.

• Recommended actions:

  • Add prepend_index_group_keys=True to all groupby.mf.apply_chunk calls to opt in to the new behavior.

  • If you specify the index parameter, remove group keys from it.

  • If you use the DPE engine and your user-defined function references group columns, update your code to explicitly retain those columns.

If you have any questions or need assistance during migration, submit a ticket to contact us.

Thank you for your continued support of MaxCompute.

March 30, 2026 - Billing changes for external tables and Data Lakehouse

Dear MaxCompute customer,

To align with the evolution of the Data Lakehouse architecture, MaxCompute will adjust the pay-as-you-go billing model for queries on external tables and Data Lakehouse analytics, effective Tuesday, June 30, 2026 (UTC+8). This adjustment is designed to cover a wider range of data sources and more accurately reflect the true cost of computation.

Key changes:

1. Billing basis change: The billing metric for input data will change from physical size to logical size. The logical size is the uncompressed raw data, typically 3 to 7 times larger than the physical size. The unit price remains CNY 0.03 per GB, but the calculation now includes a computational complexity factor. The new billing formula is: Logical data volume × Complexity factor × CNY 0.03/GB.

2. Expanded billing scope: In addition to OSS and OTS, read operations from the following data sources will now be billed: Hologres, RDS, HBase, Lindorm, Hive, HDFS, and Object Tables. The LOAD command will remain free of charge.

3. Subscription policy: For subscription plans, the cost remains unchanged. These jobs will consume your resource group quota, and no additional external computing fees will be charged.

If you are concerned about potential cost increases, we recommend the following actions:

• Migrate your compute jobs to run within the data warehouse or on the data lake.

• Recommended: Switch from the pay-as-you-go model to a subscription plan. This is the fastest transition method and allows you to lock in costs.

If you have any questions or need assistance, please submit a ticket.

Thank you for your continued support of MaxCompute.

March 5, 2026 - MaxFrame SDK upgraded to v2.5.0+

Dear MaxCompute user,

To deliver a more stable and feature-rich MaxFrame experience, the MaxFrame SDK has been upgraded to version 2.5.0. This upgrade improves system stability and expands functional capabilities. However, because it includes updates to underlying protocols, compatibility issues may arise in specific scenarios, causing MaxFrame jobs to fail or produce errors.

To avoid disrupting your business continuity and data output efficiency, upgrade your MaxFrame SDK to version 2.5.0 or later as soon as possible.

Before switching to the new version, validate the compatibility of your existing jobs in a staging environment. If a job fails or produces an error, check the job logs to confirm whether the issue stems from protocol incompatibility, and contact technical support immediately.

If you have any questions or need assistance during the upgrade or usage process, submit a ticket.

Thank you for your understanding and support.

February 24, 2026 - Sunset of Mars feature modules and billing items

Dear MaxCompute user,

To optimize the product structure and enhance the service experience, Alibaba Cloud MaxCompute will unpublish and cease maintenance for the Mars feature and its corresponding billing items (Data Science (Mars) pay-as-you-go) on Tuesday, March 31, 2026 (UTC+8).

If you are currently using Mars to run jobs, migrate your jobs as soon as possible to prevent failures or service unavailability.

If you have any questions or need assistance during migration, contact us through your dedicated DingTalk group or by submitting a ticket.

Thank you for your understanding and support.

January 29, 2026 - Sunset of MaxCompute Data Lakehouse Solution 1.0 and DataWorks entry

Dear MaxCompute user,

• Closure of DataWorks Data Lake Integration (Data Lakehouse) entry

  Effective Thursday, February 26, 2026 (UTC+8), MaxCompute will retire the DataWorks Data Lake Integration (Data Lakehouse) entry point in the China public cloud, China (Hong Kong), and Germany (Frankfurt) regions. After this date, you can no longer use the DataWorks Data Lake Integration feature to create Data Lakehouse 1.0 external projects, which have a two-level project-table structure. You can still view and manage existing Data Lakehouse 1.0 external projects in the MaxCompute console. MaxCompute will also continue to support referencing the catalog of a Data Lakehouse 1.0 external project from an internal project with a two-level structure. This allows you to query data mapped from DLF-legacy or Hive.

• Deprecation of Data Lakehouse Solution 1.0 features

  MaxCompute will retire all Data Lakehouse 1.0 features in the China public cloud, China (Hong Kong), and Germany (Frankfurt) regions on Thursday, April 30, 2026 (UTC+8). For a list of affected features, see Data Lakehouse 1.0 (Discontinued). We recommend migrating your existing projects and tasks by following the guide in Migrate Data Lakehouse 1.0 external projects to Data Lakehouse 2.0 external schemas. After migration, you can connect to a broader range of data sources and formats and benefit from more reliable, enterprise-grade Data Lakehouse capabilities.

If you have any questions or need assistance during usage, submit a ticket.

Thank you for your understanding and support.

January 22, 2026 - MaxCompute network connectivity solution upgrade

Dear MaxCompute user,

MaxCompute plans to upgrade the underlying technical solution for the network connectivity (networklink) feature in public cloud regions in China from Thursday, January 22, 2026 to Friday, January 30, 2026 (UTC+8).

• This upgrade affects the following users:

  Users who use networklink through the VPC access (Direct connect) and whose selected vSwitch (VSW) is in one of the following zones:

  • China (Beijing): Zones A, B.

  • China (Shanghai): Zones A, C, D, K.

  • China (Hangzhou): Zones D, E.

  • China (Shenzhen): Zone B.

• Validate as follows:

  1. Log on to the MaxCompute console. After you select a region, in the left-side navigation pane, choose Manage Configurations > Network Connection. Click a networklink to view its details.

     Record the VPC and vSwitch information from the details page to confirm the vSwitch's availability zone.

     In the Basic Information section, the Selected VPC field corresponds to the VPC ID, and the vSwitch field corresponds to the vSwitch ID.

  2. Log on to the virtual private cloud (VPC) Management Console. In the upper-left corner, select the region. In the navigation pane on the left, choose vSwitch. Then, confirm the zone of the vSwitch (VSW).

     In the vSwitch list, find the entry that corresponds to the vSwitch ID you recorded.

     Check the Availability Zone column for that entry to determine if it is in the list of affected zones.

• Modify as follows:

  If your vSwitch (VSW) is in one of the affected zones, rebuild the MaxCompute network connectivity.

  1. Record the VPC ID and security group ID of the affected network connectivity (networklink), and then delete the old networklink on the MaxCompute page.

  2. On the VPC page, create a new vSwitch (VSW) in a supported zone for the VPC associated with the networklink.

     Note

     The vSwitch (VSW) does not need to be in the same zone as your service. You can create a vSwitch (VSW) in one of the supported regions and zones listed below and use the newly created networklink to connect to services in the original zone.

     Supported zones are as follows:

     China (Hangzhou) — Zones H, I, J, K. China (Beijing) — Zones F, G, H, I, L. China (Shanghai) — Zones B, E, G, M, N. China (Zhangjiakou) — Zones A, B, C. China (Ulanqab) — Zones B, C. China (Shenzhen) — Zones C, D, E, F. China (Hong Kong) — Zones B, C. China (Shanghai) Finance Cloud — Zone F. Japan (Tokyo) — Zones A, B. Singapore — Zones A, B, C. Malaysia (Kuala Lumpur) — Zones A, B. Indonesia (Jakarta) — Zones A, B. Germany (Frankfurt) — Zones A, B, C. US (Silicon Valley) — Zones A, B. US (Virginia) — Zones A, B

  3. Finally, on the MaxCompute page, rebuild the networklink by selecting the original VPC ID, the new vSwitch ID, and the original security group ID. Then, update any jobs that used the old networklink to reference the new networklink, and run the jobs to validate the change.

Note: While you perform the steps above, jobs that access the VPC through the networklink (such as MaxCompute SQL UDFs, external tables, or Spark jobs) will fail. Therefore, perform these steps when no jobs related to the network environment are running.

If you encounter any issues or need assistance during usage, submit a ticket.

Thank you for your understanding and support of MaxCompute!

January 16, 2026 - New SQL Analysis is now available in all regions

Dear MaxCompute user,

The SQL Analysis feature in the MaxCompute console has been upgraded and is now available in all regions. This upgrade helps you adapt to cloud-native technologies and handle complex data analytics. For more information about the features and how to enable them, see Use SQL Analysis (New Version) to Connect.

The entry point for the previous version of SQL Analysis will be retired on March 31, 2026 (UTC+8). Before this date, please make sure to clean up your local files in the workspace of the previous version. To save your files for future use, manually move them to your personal folder in the new version of SQL Analysis.

If you encounter any issues while using the new SQL Analysis, submit a ticket.

Thank you for your understanding and support.

January 9, 2026 - MaxCompute ECS Resource Reuse Edition offline announcement

Dear MaxCompute user,

The MaxCompute ECS Resource Reuse Edition was officially taken offline on Friday, January 9, 2026 (UTC+8). If you have projects or jobs that specify the os_EcsQuota Quota, modify them and migrate to the subscription Standard Edition or pay-as-you-go Standard Edition.

If you encounter any issues or need technical support, submit a ticket.

Thank you for your understanding and support.