Hybrid Manager (HM) 1.4.0 (LTS) expands deployment flexibility with Microsoft AKS support, simplifies day-to-day operations with a new automations engine, and deepens AI capabilities across pipelines, migration, and the built-in chatbot. This long-term support release consolidates all features from Innovation Releases 2025.11 through 2026.5.1. It also includes numerous bug fixes and quality-of-life improvements.
Release Date: June 24, 2026
Postgres refers to all distributions supported by EDB
- PostgreSQL
- EDB Enterprise Postgres - formerly, EDB Postgres Extended Server (PGE)
- EDB Enterprise Postgres (Oracle Compatible) - formerly, EDB Postgres Advanced Server (EPAS)
Release highlights
Azure Kubernetes Service (AKS) support: HM can now be deployed on Microsoft AKS, with full support for AI Pipelines, Analytics Accelerator, and the Data Migration Service.
Selective installations: Customize your HM deployment by enabling only the
scenariosyou need —core,dbaas,migration,ai, andanalytics— at install time or later, reducing resource usage and simplifying component management.Automations engine: A new automation framework handles routine database operations including disk auto-scaling, CPU and memory scaling, index application, and minor and patch database version updates — all with configurable maintenance windows and optional human-in-the-loop approvals.
OSS Library: Deploy community database tools — Apache Airflow, Apache Superset, Metabase, pgAdmin 4, pgBadger, and HammerDB — directly to HM projects from the Asset Library, with configurable parameters and approval workflows.
Chat Agent: A conversational assistant built into the HM console for Postgres cluster management, estate browsing, monitoring and alerts, health report retrieval, Oracle-to-Postgres SQL translation, and documentation Q&A with citation-backed answers. Supports models from OpenAI, Anthropic, and Google Gemini, as well as self-hosted models deployed through HM.
Custom load balancer configuration: HM supports custom load balancer annotations for use cases such as MetalLB address pool assignment and disabling Azure Private Link on Azure private clusters.
Three-location cluster deployments: Deploy Postgres clusters across three geographically separated locations for zero-data-loss configurations via synchronous replication. HM also supports Distributed High Availability (DHA) Witness Groups in a third location for quorum and split-brain prevention.
Unified schema migration: Migrate database schemas from Oracle and Postgres sources to Postgres destinations directly through HM, with Oracle SQL compatibility assessment and API-driven automation via AI agents.
Model Context Protocol (MCP) integration: HM now exposes its API capabilities through MCP, enabling AI agents and developer tooling to consume HM APIs for agentic workflows.
Agent Factory enhancements: Visual AI Pipeline Designer, multistep composable pipelines, hybrid search, the
summarize_text_aggregate()SQL function, and expanded Langflow components including EDB Airman MCP Server, EDB Embedded Models, and EDB Vector Index.Langflow integration: Langflow is natively integrated into the HM Launchpad. You can build AI-powered agents and workflows within HM, deploy flows as managed workloads, and use a Langflow template for end-to-end database migrations from Oracle and Postgres sources to Postgres destinations.
Enhanced migration risk assessment: Granular assessments for source databases covering replication slot health, WAL generation rates, and risky table configurations (primary keys,
REPLICA IDENTITY,TOAST, and unsupported data types for the Data Migration Service).Advanced observability: Daily cluster health reports, schema change detection, new query detection, a metrics comparison tool, and enhanced monitoring dashboards.
ARM architecture support: HM components now run on ARM-based architectures, enabling deployments on modern ARM platforms and Kubernetes nodes.
Release details
Hybrid Manager (HM) platform
| Type | Description |
|---|---|
| Platform support | Added support for Kubernetes 1.34 and OpenShift 4.21. |
| Platform support | Added ARM64 architecture support for HM, extending deployment options to ARM64-based Kubernetes environments. See the platform compatibility page for the supported configurations. |
| Feature | Added support for HM deployments on Microsoft Azure Kubernetes Service (AKS), with full support for AI Pipelines and the Data Migration Service (DMS). |
| Feature | Added support for bringing your own identity provider (IdP), configurable from the HM console (Settings > Identity Providers). HM can now automatically assign user roles based on IdP group attributes, declaratively mapping user groups to roles. |
| Feature | Added the Chat Agent, a conversational assistant in the HM console for informational queries and Postgres cluster management. |
| Feature | HM now exposes its API capabilities through the Model Context Protocol (MCP), enabling developers and AI agents to consume the HM API for agentic use cases, including integration with Langflow for streamlined database agent configuration. |
| Feature | The HM console now includes Langflow in the Launchpad for building and testing AI-powered agents and workflows directly within the platform. |
| Feature | HM now supports selective installations. Customize your deployment by enabling only the scenarios you need (core, dbaas, migration, ai, and analytics) at install time or later, reducing resource usage and simplifying component management. |
| Feature | Added support for deploying Postgres clusters across three geographically separated locations, enabling zero-data-loss architectures through synchronous replication. HM also supports deploying Distributed High Availability (DHA) Witness Groups in a third location to maintain quorum and prevent split-brain scenarios during automated failovers. |
| Feature | Introduced the Automations engine for automating routine database operations. Available automations include database storage auto-scaling, CPU and memory auto-scaling, automatic index application, and automatic minor and patch image upgrades. The framework features project-level maintenance windows, granular execution controls, optional human-in-the-loop approvals, and an integrated Task Manager for centralized monitoring of all automated activities. |
| Feature | Introduced OSS Library, a catalog of community database tools deployable directly to HM projects. The initial catalog includes Apache Airflow, Apache Superset, Metabase, pgAdmin 4, pgBadger, and HammerDB. Apps are deployed from the Asset Library > Apps section, with configurable parameters, optional deployment scheduling, and human-in-the-loop approval workflows. |
| Feature | Added the ability to initiate a write-leader switchover for Distributed High Availability clusters directly from the cluster detailed view in the HM console. |
| Feature | Added API audit logging. HM now emits structured JSON audit log entries for all authenticated API requests through the ingress gateway, capturing user, session, API key, and response details for compliance and security auditing. Logs are queryable via Grafana or kubectl. |
| Feature | Added dynamic PGD previews, enabling real-time preview capabilities for PGD configurations during cluster provisioning and management workflows. |
| Feature | Added nodeSelector and tolerations support in edbctl for Primary/Standby Replication (PSR) cluster create and edit operations, enabling dedicated and isolated node pools for Postgres workloads. |
| Enhancement | Added support for nodeSelector and tolerations in the Postgres cluster provisioning and patch API for advanced workload isolation. |
| Enhancement | The Chat Agent now uses a selection list interaction method and a separate password transmission path to ensure passwords aren't uploaded to the large language model. |
| Enhancement | Added support for publishing Langflow flows as bundles and deploying them within HM. |
| Enhancement | Simplified the multi-location (multi-dc) deployment procedure. Multi-dc topology is now primarily controlled via primary.yaml and secondary.yaml configuration files, supporting standard Helm practices. |
| Enhancement | The cluster detailed view now lists all group nodes of Distributed High Availability clusters, providing visibility into current topology and status before and after a switchover operation. |
| Enhancement | You can now change network configuration for Witness groups through the HM console. |
| Enhancement | Added global configuration parameters for HM ingress load balancers, providing more granular control over HM platform networking and traffic management. |
| Enhancement | Added support for Custom Loadbalancer annotations in EDB Postgres AI agent (beacon-agent) provisioning across supported platforms. |
| Enhancement | Enhanced load balancer configuration: private mode now allows custom annotations alongside HM default private annotations; public mode supports custom annotations, HM default private, and HM default public annotations. |
| Enhancement | Added a Custom Loadbalancer Configuration option for network access when creating or editing clusters, allowing custom load balancer service annotations (key-value pairs) for read-write and read-only connections. |
| Enhancement | Added support for custom Kubernetes Service annotations on Kafka load balancers, including the Data Migration Service's Kafka services, enabling BYO-network and on-premises deployment scenarios. |
| Enhancement | HM now supports configuring dedicated object storage per HM project, including via the CLI using edbctl project create-object-store. |
| Enhancement | HM cluster APIs now provide more visibility when provisioning fails, enabling self-service diagnostics and faster time to resolution. |
| Enhancement | Added optional read-only connection strings for HA and DHA clusters to route read operations to standby replicas or non-write-leader nodes, reducing load on the primary. |
| Enhancement | Added advanced compression to HM backup capabilities through Barman Cloud integration. WAL compression is now enabled by default, using Snappy compression for basebackups and zstd for WAL files. |
| Enhancement | Introduced the consolidated system database (upm-system-db). |
| Enhancement | Enhanced the database notification system with expanded event sources, including agentic automated tasks generated by the platform. All resource types in the audit log table are now clickable. |
| Enhancement | Added support for GitLab container registry as a registry provider for image discovery. |
| Enhancement | Enhanced the image library Clusters Using This Image view to only show clusters you have permission to access, based on your user role and project permissions. |
| Enhancement | Added support for configuring kapp-controller TLS settings in the HM operator Helm chart. You can now set a custom CA certificate trust or disable TLS verification for private container registries. |
| Enhancement | Added a machine-readable API index following the llms.txt convention, providing a streamlined reference of available endpoints for LLM-powered coding assistants. |
| Change | Changed the default value of the edb_stat_monitor.edbsm_normalized_query GUC from false to true. Values used in predicates are no longer saved in HM by default, improving data privacy. |
| Change | Decoupled the HM operator from HM releases to enable independent versioning and deployment cycles. The operator now enforces the use of the remote method for operations, overriding any locally specified methods to ensure consistent cluster management behavior. |
| Change | Automated the intermediate steps required when upgrading HM to a new version. Previously, upgrades required manually executing a series of Kubernetes operations such as patching deployments, annotating resources, and applying CRDs. These steps are now handled automatically once the user initiates an upgrade by specifying the target version. |
| Change | Embedded the HM plugin into the edbctl CLI. The edbctl CLI now includes hm status, hm component suspend, hm component resume, and hm component retry commands. |
| Change | Reduced the minimum deployment footprint by consolidating multiple databases into a single database, decreasing operational overhead. |
| Change | Added support for an optional in-cluster container registry, enabled through the operator Helm chart. |
| Change | The prometheus-operator component can now be disabled when it's already installed on the target platform, rather than only annotating CRDs to avoid conflicts. |
| Change | Simplified load balancer and NodePort configuration. You can now configure both Istio and database services to use load balancers or NodePorts through a single parameter in the custom resource. |
| Change | Enhanced preflight checks to validate object storage connectivity before deployment begins, preventing failures caused by incorrect object storage secrets. |
| Change | Added support for configuring all PGD GUCs through HM, including previously unavailable settings like bdr.ddl_replication. |
| Change | Database cluster management capabilities — including provisioning, backups, storage locations, and cluster templates — are now controlled by a dedicated dbaas scenario, separated from the core scenario. New installations include dbaas by default. Existing installations upgrading from 2026.3 must explicitly add dbaas to their scenarios list to retain Postgres cluster management functionality. Without dbaas, cluster management APIs return 404 and the Clusters section is hidden in the HM console. |
| Deprecation | Deprecated the AHA – Advanced High Availability (PGD-S) cluster type. The cluster type is disabled in the HM console, preventing new AHA cluster provisioning. AHA is also deprecated in the MCP and chatbot components, and deprecation notices have been added to the API documentation. Existing AHA clusters continue to function normally. Plan to migrate existing AHA clusters to PGD single distributed group configurations. |
| Deprecation | Removed the Apache Spark component bundled with HM. Connecting to external Spark clusters remains supported. No action required. This component isn't replaced. |
| Deprecation | Deprecated the beaconServer.additionalTrustDomains field in the HM CRD. No action required — the field is still accepted by the CRD for backward compatibility but is no longer used. Any value set has no effect. This field has no replacement. |
| Deprecation | Deprecated the bootstrap and edbpgai-bootstrap Helm chart installation methods. Action required: migrate to the unified HM Helm chart. See Migrating from bootstrap to the HM operator. |
| Deprecation | Removed the Lakehouse Analytics Cluster feature from the HM console. No action required — existing clusters are unaffected and no migration to another cluster type is needed. Analytics functionality is now available via PGAA in Distributed High Availability (DHA) clusters and in single-node Postgres clusters with the PGAA extension enabled. |
| Deprecation | Removed the upm-beacon-analytics-cnpg-plugin component, which was tied to the Lakehouse Analytics Cluster feature. No action required. Use PGAA in DHA or single-node Postgres clusters instead. |
Agent Factory
| Type | Description |
|---|---|
| Feature | Added the ability to create, manage, and view all AIDB knowledge bases directly within HM. |
| Feature | Added the ability to review available AI models and add new ones directly from the HM interface, with essential model metadata including context window limitations and optimal use cases. |
| Feature | Agent Factory now supports Postgres 18. |
| Feature | AI Pipelines now includes Visual Pipeline Designer — a web-based graphical design tool for developing, deploying, and managing AI data preparation pipelines, integrated into HM. |
| Feature | Added support for accessing external services for model serving, allowing you to connect and use your own remote AI models within HM, data pipelines, and the HM chatbot. |
| Feature | Extended the AIDB pipeline framework to support multistep, composable pipelines. Chain preparer functions (for example, PDF to text, HTML to text) so that the output of one step feeds into the next, enabling flexible pipeline composition through the visual pipeline designer. |
| Feature | Added the summarize_text_aggregate() function. |
| Feature | Added a PDF-to-image conversion pipeline step to AIDB, supporting complex table layouts through a pipeline that converts pages to images and applies OCR (PaddleOCR) to extract text for downstream embedding and retrieval. |
| Feature | Expanded AIDB coverage in Langflow with hybrid search support for the EDB Knowledge Base component, and three new components: EDB Airman MCP Server; EDB Embedded Models, for CPU-based text and image inference; and EDB Vector Index, for creating vector indexes on EDB knowledge bases. |
| Feature | AI Pipelines now supports multiple compatible pipelines writing into a single shared knowledge base, enabling hybrid knowledge bases from multiple sources and formats. The vector table includes a new pipeline_id column to track source pipelines per embedding. |
| Feature | Added support for deploying Langflow flows to Kubernetes environments managed by HM, with configurable QoS constraints including memory, CPU allocation, autoscaling, and restart policies. Deployed flows include full observability and alerting integration. |
| Feature | Added hybrid search capabilities to AI Pipelines, combining full-text search, vector/semantic search, and predicate filtering. Includes convenience functions and documentation examples for common use cases. |
| Enhancement | You can build AI workflows using Langflow and publish your flows as assets on the HM platform, then run them as standalone jobs. |
| Enhancement | Added an error log and dead letters queue to improve AI pipeline error handling. Track which files or records succeed and which encounter errors during pipeline execution. |
| Enhancement | Added non-blocking error handling to AI pipelines. Pipelines now continue processing when errors affect only individual records, while still halting on pipeline-level errors. Use aidb.get_error_logs() and aidb.clear_error_logs() to query and manage errors. |
| Enhancement | Added support for creating AI data pipelines for on-premises databases and external CloudNativePG clusters. |
| Enhancement | Added AIDB pipeline support for external Postgres clusters managed by HM, including clusters running on secondary locations and outside the HM platform. |
| Enhancement | The AI Pipeline Designer now retrieves available models dynamically instead of using static defaults, enabling model selection based on specific project, resource, and database combinations. |
| Enhancement | Added support for configuring the PDF to Image pipeline step directly in the visual AI Pipeline Designer, including format, DPI, page ranges, and annotation rendering. |
| Enhancement | Added support for AIDB 7 in the AI Pipeline Designer, including improved knowledge base validation and fixes for pipelines with existing knowledge base tables and PGD clusters. |
| Enhancement | Updated the AI Pipeline Designer to support AIDB 7's multi-pipeline Knowledge Base model. Knowledge bases can now be associated with multiple pipelines. The Pipeline Designer displays KB table references using full table format (vector_schema.vector_table); pipeline creation supports selecting existing KB tables; and the KB list view shows associated source pipelines with hyperlinks. |
| Enhancement | Added support for registering external inference services with insecure connections. The system requires explicit user acknowledgment of the security risk. |
| Enhancement | Added support for Hugging Face as a new model provider, configurable via Hugging Face Model Name, Object Storage path, or both. |
| Enhancement | Extended the invalid model name error message — previously only available on the Internal Model Cluster page — to the external inference service configuration page. |
| Enhancement | Enhanced error handling in the AI model creation form to display detailed error messages, improving user feedback when model creation requirements aren't met. |
| Enhancement | Added automatic retry for transient LLM errors in AI workflows, improving reliability when inference providers return temporary failures. |
| Enhancement | Restricted Langflow access to users with the AI Model Manager role for tighter control over AI workflow authoring. |
| Enhancement | You can now search AI models and services by tag name in the HM console. |
| Enhancement | Enhanced the chatbot to render data from metrics APIs using Mermaid charts, providing improved visualization of database metrics and monitoring data. |
| Enhancement | Added support for additional AI model families in the chatbot, including GPT-5 variants (mini, nano, codex), all Gemini models, and Anthropic models. |
| Enhancement | The conversation interface now displays the model name, providing greater transparency about which AI model is being used for each conversation. |
| Enhancement | Added health check validation when registering inference services. HM now detects invalid model endpoints during registration and provides detailed error messages. You can test registered inference services using a test button, and a new metrics endpoint exposes credential check results for Prometheus monitoring. |
| Enhancement | Added knowledge cutoff awareness to the HM documentation skill. Documentation snapshots now include compilation timestamps, and the AI assistant displays appropriate disclaimers when answering questions about topics that might not be covered in the current documentation snapshot. |
| Change | Removed the resolver component from the EDB Postgres AI agent (beacon-agent) and updated the agent to use AIDB 7 views directly, as part of supporting multi-pipeline knowledge base capabilities. |
| Change | Removed the AI Pipelines Default Settings page from the Sovereign AI section, as it was incompatible with the new instance-specific models list approach. |
Observability and monitoring
| Type | Description |
|---|---|
| Feature | Added proactive recommendation categories for Configuration and Security. Configuration recommendations suggest optimizing Postgres system parameters such as shared_buffers. Security recommendations flag potential security issues and provide actionable guidance for continuous monitoring of database environment integrity. |
| Feature | Added new critical alerts to monitor pods terminated by Out of Memory (OOM) events, backups exceeding 12 hours, and disk/WAL usage thresholds. |
| Feature | Users can now use event annotations on time-series charts as delimiters for selecting time periods, enabling easier isolation and analysis of data ranges associated with specific cluster events. |
| Feature | Added cluster health reports, automatically generated once a day for each HM-managed Postgres cluster. Reports are retained longer than raw metrics and can be used to track long-term health trends, spot anomalies, and share performance snapshots. The Chat Agent can retrieve and compare reports. |
| Feature | Added schema design recommendations via the chat agent. The chat agent assesses schema suitability to the running workload and provides actionable recommendations to improve performance. |
| Feature | Added support for monitoring multiple external PGD groups across different Kubernetes clusters as a single logical cluster, enabling unified visibility and topology management. |
| Feature | Added detection of queries that haven't been executed on a monitored database before. HM identifies new queries within one day, with mechanisms to disable detection and suppress excessive notifications. |
| Feature | Added schema change detection that automatically identifies changes in monitored database schemas and emits activity events to the cluster activity feed, enabling you to spot unexpected modifications, receive notifications, and compare database states before and after changes. |
| Feature | Added a metrics comparison tool to compare database metrics and query statistics between two user-defined time periods, with side-by-side or overlaid chart views, filters, zoom controls, and highlighted differences. |
| Enhancement | Self-managed PGD clusters now have full feature parity for replication matrices and lag monitoring. |
| Enhancement | Added API capabilities to annotate host metrics charts with activity logs as vertical dotted lines, enabling correlation of specific cluster events with host performance at exact points in time. |
| Enhancement | The GUC query_advisor.exclude_schema_list now includes predefined default values to automatically exclude internal database schemas from Query Advisor recommendations. |
| Enhancement | Added support for monitoring of self-managed EFM and PGD clusters. |
| Enhancement | The Disk Throughput chart now displays read and write throughput separately for more accurate monitoring. |
| Enhancement | HM now provides deeper deployment insights via pod-level status conditions in the cluster APIs. |
| Enhancement | Extended observability support for external PGD clusters to include CNPG-GC clusters. |
| Enhancement | Added a new EnableEDBUsageReporting configuration option for the beacon server with retry logic that attempts reconnection to IT links every 24 hours when unreachable. |
| Enhancement | When a cluster spec is updated — by a user change, autoscaling, or agentic automation — an annotation is automatically generated and displayed in the observability view. |
| Enhancement | Added configurable limits for Prometheus query requests to prevent resource exhaustion from overly broad queries. Store components now support request-samples and request-series limits. |
| Enhancement | Added an Annotations API to enable marking selected activity events on the monitoring dashboard, providing a foundation for automated operations. |
| Enhancement | Added WAL metrics collection for on-premises Postgres instances monitored by the EDB Postgres AI agent. |
| Enhancement | Added a validate command to the EDB Postgres AI agent (beacon-agent) for verifying database connectivity before ingestion. |
| Enhancement | HM now collects and displays cluster status metrics from self-managed EDB Failover Manager clusters. |
| Change | Updated the default alert evaluation interval to 2 minutes. |
| Change | Added tracing support to Thanos, Prometheus, and Grafana deployments, enabling detailed performance analysis of PromQL queries and better evaluation of monitoring system performance configurations. |
| Change | Removed CPU limits from EDB Postgres AI agent deployments to prevent throttling and improve monitoring performance. |
| Change | Enabled auto downsampling by default in Thanos Query, improving query performance for large time ranges by automatically using lower-resolution data when appropriate. |
| Change | Configured Istio to automatically expire old metric series for vanished peers on sidecars, preventing unbounded metric growth over time as peers come and go. |
| Change | Updated the beacon readiness probe to report ready status only after the EDB Postgres AI agent is fully booted with all connections and services active. |
| Change | Modified backend logic to ensure time data sent to charts includes appropriate timezone information or is converted to the user's local time for accurate chart rendering. |
HM console
| Type | Description |
|---|---|
| Feature | Added AI-powered query generation to the Query Editor. Select Generate with AI to create SQL queries using natural language prompts targeting data across your estate. |
| Enhancement | Added the ability to view database health reports directly in the HM console without downloading the PDF. |
| Enhancement | Added a configuration interface for HM authentication policies in the Settings section, including idle timeout for web login sessions. |
| Enhancement | Added an Invalidate User Sessions action to the Identity Providers management interface, allowing administrators to invalidate all active sessions for a specific identity provider. |
| Enhancement | Added filters in the role assignment interface to display only manually assigned roles, excluding roles assigned via IdP group mappings. |
| Enhancement | Added the beacon.enterprisedb.com/exclude-storage-from-dbaas=true label to exclude specific StorageClass or VolumeSnapshotClass resources from the Create Cluster dropdowns in shared Kubernetes environments. |
| Enhancement | You can now filter clusters by cluster or group ID in the HM console. |
| Enhancement | Added a searchable model-service picker in the HM console. |
| Enhancement | You can now display dates in a custom timezone in the HM console. |
| Enhancement | Improved keyboard accessibility in the HM console by adding keyboard event handlers to interactive elements that previously only supported mouse interactions. |
Analytics
| Type | Description |
|---|---|
| Feature | Added the ability to configure tiered tables directly from the HM console. Users can select and convert an existing table into a tiered table structure within the console. |
| Feature | Postgres Analytics Accelerator now supports Postgres 18. |
| Enhancement | Added insights and visual metrics for tiered tables, providing visual proof of tiered table configurations and moving diagnostics from the command line to the HM console. |
| Enhancement | Postgres Analytics Accelerator now supports reading and writing Delta and Iceberg tables in Azure Data Lake Storage and Azure Blob Storage. |
| Enhancement | Updated the PGAA version shipped with HM to 1.9.1. |
| Enhancement | Enhanced Lakekeeper warehouse creation to support object storage environments that don't support AWS Security Token Service (STS). The system now automatically retries warehouse creation with STS disabled if the initial attempt fails on S3-compatible storage. |
Migrations
| Type | Description |
|---|---|
| Platform support | HM migration features are now fully supported in air-gapped on-premise environments (RKE and RHOS deployments). |
| Feature | Added a Langflow template for AI-powered, end-to-end database migrations from Oracle, and Postgres sources to Postgres destinations, including provisioning HM-managed clusters, migrating schemas, and performing snapshot plus streaming data migration. Oracle sources require schema conversion via Migration Portal before running the migration flow. |
| Feature | The HM console Sources and Destinations migration pages now display the RW_SERVICE_HOST environment variable needed by the Data Migration Service (DMS) agent (cdcagent) to connect to the HM instance, enabling self-service retrieval of this value. |
| Feature | HM now automatically creates Migration Portal projects when source database schemas are ingested by the EDB Postgres AI agent (beacon-agent), eliminating the need to manually create a Migration Portal project in most cases. |
| Feature | Added a replication slot health monitor that tracks the state of logical replication slots on the source Postgres database, reporting health status, replay lag, and disk retention for each slot in the downloadable metrics report. |
| Feature | Added a dedicated metrics fetcher that runs independently of schema change detection, enabling continuous monitoring of database metrics such as WAL generation rate at regular poll intervals. |
| Feature | Added a per-table tuple mutation rate assessment that estimates each table's contribution to WAL generation, enabling more granular migration planning for source Postgres databases. |
| Feature | Added a global WAL generation rate assessment that monitors WAL accumulation on the source Postgres database, helping estimate storage capacity requirements during migration snapshots. |
| Feature | Added a migration assessment that checks for risky combinations of primary key, REPLICA IDENTITY, and TOAST configurations in Postgres tables, identifying scenarios where the Data Migration Service (DMS) might silently miss changes. |
| Feature | Added a migration assessment that identifies Postgres data types unsupported or risky for DMS-based CDC, providing early warnings about potential compatibility issues before starting a migration. |
| Feature | Added a public API endpoint for downloading Migration Portal assessment reports in JSON format. |
| Feature | Added the ability to enter and display metadata about applications associated with databases and schemas in many-to-many relationships, providing better context for migration planning and prioritization. |
| Feature | Added the ability for the EDB Postgres AI agent (beacon-agent) to automatically configure Oracle and Postgres database connections from Oracle TNSNAMES.ORA files, CSV files, or AWS RDS auto-discovery. |
| Feature | Added unified schema migration capabilities to migrate database schemas from Oracle or Postgres sources to Postgres destinations directly through HM, with support for HM-managed and externally managed destinations, and API access for AI agent automation. |
| Feature | Added the ability to assess Oracle application SQL statements for compatibility with EDB Postgres Advanced Server, supporting SQL extracted from Oracle trace files and system views, as well as statements provided via the HM console or API. |
| Feature | Added a Metrics tab to the Migration details page in the HM console. While a migration is active, the tab links to a Grafana dashboard pre-filtered to that migration, showing throughput (rows/s, bytes/s), batch latency, commit latency, and batch sizing for both the read and write sides of the DMS agent. |
| Enhancement | HM migrations now include a migration Error history tab that provides detailed error messages including error source, activity status, timestamp, and full log outputs to help with troubleshooting. |
| Enhancement | The Oracle database details page now includes a schema compatibility summary describing database compatibility as reported by the Migration Portal project. |
| Enhancement | Migration Portal now includes information on dependent objects and schemas to prevent related incompatibility issues such as missing relation references. |
| Enhancement | The Postgres database details page Assessment tab now includes new sections listing configuration items that could impact migration complexity: extensions installed, foreign servers, foreign tables, tablespaces, and installed procedural languages. |
| Enhancement | The Migrate > Migrations list view now includes Migration Type and Migration Progress columns. The Migration Progress column shows live metrics per migration: total tables included, snapshot tables completed, and cumulative rows migrated. The Tables tab in the migration details view shows per-table snapshot status, mapped columns, rows migrated, and migration rate (rows/s). |
| Enhancement | Enhanced the EDB Postgres AI agent and related services to better support ingestion, assessment, and concurrent migration of large numbers of external databases. |
| Enhancement | DMS has been tested and certified to support migrations to HM-managed Postgres 18 databases, and from or to externally managed Postgres 18 databases. |
| Enhancement | The migration assessment in the detailed view now provides clearer diagnostics regarding Replica Identity for Postgres sources. |
| Enhancement | Improved the search for migration statuses in the Estate > Migrations tab for faster results. |
| Enhancement | Error logs for ongoing migrations now provide minute-level data for easier troubleshooting. |
| Enhancement | Added new DMS agent environment variables for finer control over the schemas and tables in a source database that are available for data migrations. |
| Enhancement | Added a section to the Postgres database details page to display tablespace usage, listing the count of object types by schema for each tablespace. |
| Enhancement | Improved DMS snapshot performance by deferring primary key application until after the snapshot phase. Composite primary keys are collected and applied in order post-snapshot, with support for deduplication between snapshot and streaming phases. |
| Enhancement | Extended the Migration Portal assessment reports API to support bulk downloads. The new endpoint accepts multiple database resource IDs and returns assessment reports in a single JSONL file. |
| Enhancement | When a Postgres database is registered for migration, its schemas are now automatically ingested, parsed, and stored in the Migration Portal backend database and made available for migration via new API behaviors. |
| Enhancement | The migration agent now honors upstream cancellation signals when extracting Oracle schemas, enabling cleaner shutdown behavior. |
| Enhancement | Added support for replicating PostgreSQL DOMAIN types based on DATE, TIME, TIMESTAMP, INTERVAL, UUID, JSON, XML, and POINT types in both snapshot and CDC replication modes. |
| Enhancement | Added concurrent schema finalization for schema_and_data migrations. After the snapshot stage completes, you can select Finalize Schema Concurrently to apply indexes, foreign keys, and other schema objects in the background using non-blocking DDL variants, significantly reducing cutover time. |
| Enhancement | Extended Postgres-to-Postgres schema migration in the DMS to handle Postgres-specific database objects — including custom domain types — during schema migration, ensuring correct dependency ordering for complete end-to-end schema migration between Postgres databases. |
| Enhancement | Enhanced the Simple Migration Agent Langflow template with an improved architecture leveraging unified schema migration, streamlined agent components, automatic password generation, database setup, and support for Llama 3 Nemotron 49B and Nano 4B models. |
| Enhancement | The Simple Migration Agent Langflow template is passwordless, using global secrets management to handle credentials without exposing them to the large language model (LLM). |
| Enhancement | Optimized the migration creation form to skip table loading and validation when the migration scope is set to schema-only. |
| Change | Updated the Migration Copilot with improved AI models: GPT 5.2 is now the default model, with support for validated Nemotron 49B Llama3 as an alternative. |
| Change | Added support for per-database binary path configuration in the EDB Postgres AI agent (beacon-agent). You can now specify a custom pg_bin_path for each database entry in beacon_agent.yaml, enabling a single beacon-agent to connect to multiple PostgreSQL flavors that require different pg_dump and pg_dumpall binaries. |
| Change | Added pre-flight validation for Postgres table REPLICA IDENTITY before enrolling tables in DMS publications. Tables without primary keys or proper REPLICA IDENTITY settings are rejected at setup time with clear remediation steps, rather than causing UPDATE/DELETE operations to fail after migration begins. |
| Change | Added support for PostgreSQL 18 pg_dump and pg_dumpall output parsing, including new psql meta-commands (\restrict and \unrestrict) and improved ROLE object classification. |
| Change | Updated the Migration Copilot to use hardened Echo base container images, improving security posture and reducing vulnerability exposure. |
| Deprecation | The domain_name parameter moved from componentsParameters["transporter-rw-service"] to globalParameters.dms_domain_name in an earlier Innovation Release. If you're upgrading directly from the latest patch version of HM 1.3.x, this migration is handled automatically by the hmupgrader tooling. Users who followed the Innovation Release track will have already applied this change. |