#516 Issue
Aug. 17, 2026
Welcome to issue #515 August 10th, 2026
News
Cloud SpannerData AnalyticsDatabasesUnifying public and private data: Scale knowledge graphs with Data Commons on Spanner - Now, you can create a knowledge graph from public Data Commons data as well as your private data with a new Spanner Graph-native platform.
AgentsDatabasesIntroducing Database Operations Agents: The future of autonomous database management - A closer look at AI-powered database operations agents for setting up and onboarding AlloyDB, Bigtable, Cloud SQL, Spanner, as well as managing them.
BigQueryData AnalyticsZero-code, low-cost data ingestion: New BigQuery DTS capabilities - Discover new BigQuery Data Transfer Service capabilities. Automate low-cost data ingestion from diverse sources directly into your data warehouse.
AIAPI GatewayLLMModel routing with Google Cloud API Gateway - Google Cloud API Gateway now offers a model routing feature in Public Preview, allowing developers to dynamically route traffic to models like Gemini, Claude, or OpenAI OSS-GPT without hardcoding endpoints or managing open-source proxies. Developers can easily configure these routing rules directly within their OpenAPI 3.x specifications by mapping virtual model names to specific backend targets on a shared host.
AgentsGCP CertificationGemini Enterprise Agent PlatformYour agentic summer: No-cost lessons from Google experts to build and scale agents - Access no cost training through Google Cloud’s Gemini Enterprise Agent Ready (GEAR) program to build in-demand agentic skills.
Articles, Tutorials
Infrastructure, Networking, Security, Kubernetes
Threat IntelligenceUNC6671 Rebrands: Multi-Brand Vishing Extortion Targets Financial Services and Enterprise Cloud Environments - UNC6671 has rebranded from BlackFile to REDACT while diversifying its extortion operations across multiple brands, including FALCON, HELIX, and PINK.
AI SecurityHow Google Cloud detects, contains, and protects against emerging threats - Learn more about how Google Cloud empowers you with the tools, governance, and infrastructure you need to securely deploy workloads and maintain long-term trust.
AI Mainframe MigrationReal-world mainframe modernization with AI: A safe, scalable path from mainframe to cloud - At Google Cloud, we propose an end-to-end mainframe modernization strategy that leverages the power of AI and the agility of the cloud.
Distributed CloudDigital sovereignty in the age of AI: You don’t have to choose between control and innovation - Learn how Google Distributed Cloud (GDC) satisfies regulated industries’ preference for AI infrastructure that offers data residency controls.
AI Confidential ComputingAdvancing brain tumor research with privacy-first AI - Discover how Google Cloud and MedPerf use Confidential Computing to enable secure, privacy-first collaborative medical AI evaluation.
GCP Experience NetworkingGOL! How TelevisaUnivision streamed the FIFA World Cup to millions with Google Cloud - How TelevisaUnivision partnered with Google Cloud to stream all 104 FIFA World Cup 2026 games to viewers across Latin America.
AI DevOps LLMScaling real-time AI agents with session-aware load balancing - Real-time AI agents break traditional request-response load balancing paradigms because they rely on long-lived, stateful bidirectional streams that obscure true server capacity. To solve this, developers must implement application-level session tracking directly within the runtime to accurately measure the committed concurrent workload of active conversations.
AI Infrastructure KubernetesBootstrapping OSS Kubernetes on GCE with TPU6 and Open-Source DRANET with Gemma 4 LLM - This article explores how to deploy an open-source Kubernetes cluster directly on Google Compute Engine while integrating Cloud TPU v6e accelerators.
Cloud Storage Google Kubernetes Engine LLMHow to build an elastic, scalable LLM Inference Platform on GKE using Fluid Compute - This guide provides a comprehensive walkthrough on architecting a fault-tolerant, cost-optimized Large Language Model (LLM) serving platform on Google Cloud using diverse GPU consumption types. It demonstrates how to leverage Google Kubernetes Engine (GKE), multi-region GCS buckets with zonal rapid caching, and custom compute classes to balance high availability with significant cost savings.
FinOps Google Kubernetes EngineHow We Reduced GKE Costs by 33% Through Smarter Scheduling and Resource Governance: A DevOps Case Study - This DevOps case study explores how an engineering team successfully reduced their Google Kubernetes Engine (GKE) monthly infrastructure bill by 33% without sacrificing performance. By implementing smarter workload scheduling, migrating non-critical environments to cost-effective Spot nodes, right-sizing resource requests, and enforcing strict node governance, they transformed an organically grown and expensive cluster into an efficient, highly available system.
App Development, Serverless, Databases, DevOps
Database Migration Service DatabasesMultiple result sets: How Database Migration Service automates SQL server to PostgreSQL translation - Learn how Google DMS automates the translation of SQL Server Stored Procedures into PostgreSQL, and how to run and test the generated code.
Cortex Framework Data Analytics SAPCortex Framework v7 is GA: Build agentic workflows without disrupting SAP operations - Discover Cortex Framework v7, now GA. Transform SAP data into AI-ready data products in BigQuery and Knowledge Catalog to power AI agents with Gemini.
API Apigee GCP ExperienceHow Deutsche Bank unlocked agility with an API-ready ecosystem - Needing a system that was adaptable, scalable, reliable, secure, and AI-ready for the demands of modern banking, Deutsche Bank chose Google Cloud's Apigee as our APIM platform.
Cloud Filestore StorageUnlocking the future of shared storage: Filestore on Colossus - By leveraging the Colossus, Google’s distributed storage system, Filestore delivers greater flexibility and scalability for modern workloads.
Cloud Spanner Data Analytics Databases RetailHow Target is enhancing retail discovery and cutting database maintenance by 50% with Spanner Graph - Discover how Target transitioned to Spanner Graph to overcome siloed data and build a generative AI-powered Shopping Graph for better discovery.
Agents DevOpsBehind the scenes: How we build, test, and scale Google Agent Skills - Discover how Google scales and maintains quality for Agent Skills with standard layouts, automated CI/CD checks, and continuous evals.
Cloud Storage DatabasesBuilding an Agentic DB Analyst: pgvector, Google Cloud Storage (GCS) , and Deterministic SQL - Bridging relational databases and Cloud Storage without sacrificing mathematical accuracy.
Agents AI Hypercomputer GPUScaling agentic AI: How UiPath built its high-performance GPU platform on AI Hypercomputer - UiPath is helping to pioneer an industry shift toward agentic AI. Learn how they used Google Cloud to build a high-performance GPU platform.
Cloud Armor Cloud LoggingLog Sampling on Google Cloud - How to selectively log for Cloud Armor.
Model ArmorModel Armor Doesn’t Redact PII. Sensitive Data Protection Does - This article explains how to properly configure Google Cloud Model Armor and Sensitive Data Protection (SDP) to redact personally identifiable information (PII) from AI model responses instead of simply blocking them. It provides a technical walkthrough on setting up the necessary inspect and de-identify templates, avoiding common silent failure traps, and properly handling cross-project permissions.
Big Data Cloud Run DevOps TerraformFrom Two Days to One Command - How we turned data ingestions into a factory with Cloud Run + Terraform.
Big Data, Analytics, ML&AI
Cloud Dataflow Cloud Pub/Sub Data AnalyticsSolving the "Noisy Neighbor": How Sharded Architecture Protects Multi-Tenant Platforms - Prevent noisy neighbors from impacting multi-tenant platforms. Learn how sharded hub-and-spoke architecture helps isolate workloads and maintain SLAs.
Apache Iceberg BigQuery DatabricksDatabricks Iceberg — BigQuery query - This article provides a comprehensive technical guide on how to configure and query Apache Iceberg tables created in Databricks (hosted on Google Cloud Platform) using BigQuery. It explains how to set up Google Cloud Storage, Databricks Unity Catalog, and IAM permissions to successfully implement catalog federation between the two platforms. Ultimately, the piece enables data teams to seamlessly read and analyze Databricks-managed Iceberg data directly through Google's cloud-native query engine.
Agents BigQuery Data AnalyticsAgentic Future Ready With BigQuery: Continually Improving Price-Performance, Zero Effort - Learn about the latest innovations to help improve BigQuery price-performance with autonomous query processing.
AI Hypercomputer GPU Startups TPUMirendil taps AI Hypercomputer TPUs and GPUs for pre- and post-training applications - With Google Cloud’s AI Hypercomputer, Mirendil gains access to TPUs and NVIDIA GPUs to support its model pre-training and post-training applications.
ADK Cloud Run GCP Experience GeminiFrom repetitive queries to instant SQL: Building Carrefour’s internal data assistant in a weekend - Discover how retail giant Carrefour leveraged Google Cloud ADK, Gemini, and Cloud Run to build a scale-to-zero RAG assistant integrated directly into Google Chat. This smart agent automates responses to internal data platform questions in minutes, significantly reducing support bottlenecks and saving valuable engineering hours.
AI BigQueryHow to Build an Adaptive Feedback Loop for AI Agents in BigQuery - Live RAG remediation and AI agent post-mortems in BigQuery.
Agents AI MCPAgent Plugins package your skills, tools, and more - Agent Plugins 1.0.0 is a new, vendor-neutral directory specification—backed by Google, Amazon, Microsoft, and others—for packaging Agent Skills and MCP servers into a single portable unit. By standardizing the manifest (plugin.json) and utilizing a fixed directory layout, it eliminates the need for developers to maintain separate wrappers or configurations to support different AI coding agents and IDEs.
AI MCPScaling AI Agent Infrastructure with the MCP Stateless updates - The 2026-07-28 Model Context Protocol (MCP) specification replaces legacy stateful constraints with a fully stateless core, enabling cloud-native horizontal scaling, serverless deployments, and standard round-robin load balancing. This architectural shift introduces standardized HTTP headers for efficient routing without deep packet inspection, caching controls, and Multi Round-Trip Requests (MRTR) to handle interactive and long-running tasks without blocking connections.
AgentsScaling agentic AI on Google Cloud: How AppsFlyer built a governed multi-agent platform - AppsFlyer built a scalable, governed multi-agent AI platform on Google Cloud to handle thousands of daily enterprise agents without sacrificing data security. By combining tools like Vertex AI, Cloud Run, BigQuery, and AlloyDB, the platform standardizes agent deployment, enforces strict data governance, and enables seamless collaboration across different teams.
Agents MCPStandardizing Agent Plugins for Google Data Cloud - Empower your coding agents with standards based, vendor-neutral plug-ins to Google Data Cloud services.
Releases
Cloud Run - Cloud Run supports sandboxes for all resources, including jobs and worker pools ( Preview ).
Cloud SQL MySQL - You can change the backup plan for your Cloud SQL enhanced backups without first removing the existing plan. For more information, see Change your instance's associated backup plan. Cloud SQL for MySQL supports resource groups. MySQL resource groups let you manage resource allocation for different workloads on your Cloud SQL for MySQL instance. By using resource groups, you can prevent less important workloads from consuming excessive CPU or memory resources. To use MySQL resource groups, you must have maintenance version MYSQL_VERSION.R20260320.00_20 or later installed on your instance. For more information, see Manage CPU allocation with MySQL resource groups. DNS automation is now generally available ( GA ) on Cloud SQL instances where Private Service Connect is enabled. You can use DNS automation to provision and manage per-instance DNS records automatically. On Enterprise Plus edition instances where DNS automation is enabled, you can also enable a global write endpoint DNS that automatically resolves to your current primary instance. Performance capture for Cloud SQL for MySQL is now generally available ( GA ). Performance capture lets you take a point-in-time snapshot of your database and operating system metrics automatically and route them to Cloud Logging for root-cause analysis. With the GA release, you can configure custom thresholds that end long-running transactions automatically before they slow down your database. In addition, the GA release includes six additional performance capture triggers: High CPU utilization High memory usage High temporary files usage History list length Semaphore waits Transaction lock waits For more information, see Cloud SQL performance capture overview.
Compute Engine - Changed: The minimum provisioned throughput for a Hyperdisk ML volume attached to more than 20 instances is 20 MiB/s per instance, reduced from 100 MiB/s. For more information, see Share a Hyperdisk ML volume between instances.
Confidential VM - The accelerator-optimized g4-standard-48 machine type for securely running AI and ML workloads is generally available (GA), with the following specifications: 5th Generation AMD EPYC Turin processor AMD SEV 1 NVIDIA RTX PRO 6000 GPU
Dataproc Serverless - Managed Service for Apache Spark latest image and runtime versions: Configured spark.scheduler.listenerbus.exitTimeout to 30s. New Managed Service for Apache Spark (formerly Google Cloud Serverless for Apache Spark) subminor runtime versions: 1.2.85 2.2.85 2.3.38 Notes: Apache Spark upgraded to 3.5.3 in 2.2 runtime. Apache Gluten upgraded to 1.6 in 2.3 runtime.
GKE new features - TPU Subslicing (also known as Dynamic Subslicing) is now generally available for Ironwood (TPU7x). This feature enables you to incrementally provision node pools for a cube or litepod, breaking them into smaller slices (subslices) to run workloads requiring smaller topologies. Updates in this GA release include: Dynamic sub-slicing (topologies smaller than 4x4x4, such as 2x2x1, 2x2x2, 2x2x4, and 2x4x4 ): Supported in GKE version 1.36.0-gke.3712000 or later. Dynamic super-slicing (topologies 4x4x4 or larger): Supported in GKE version 1.35.2-gke.1842000 or later. Partition Health Labels: The partition state label is updated to cloud.google.com/gke-tpu-partition-[shape]-state to specify smaller subslice shapes. It also introduces UNSET and INCOMPLETE states. Support for the DEGRADED state only applies to the top-level 4x4x4 topology, and not for smaller sub-slicing topologies. For more information, see About GKE dynamic slicing. TPU Subslicing (also known as Dynamic Subslicing) is now generally available for Ironwood (TPU7x). This feature enables you to incrementally provision node pools for a cube or litepod, breaking them into smaller slices (subslices) to run workloads requiring smaller topologies. Updates in this GA release include: Dynamic sub-slicing (topologies smaller than 4x4x4, such as 2x2x1, 2x2x2, 2x2x4, and 2x4x4 ): Supported in GKE version 1.36.0-gke.3712000 or later. Dynamic super-slicing (topologies 4x4x4 or larger): Supported in GKE version 1.35.2-gke.1842000 or later. Partition Health Labels: The partition state label is updated to cloud.google.com/gke-tpu-partition-[shape]-state to specify smaller subslice shapes. It also introduces UNSET and INCOMPLETE states. Support for the DEGRADED state only applies to the top-level 4x4x4 topology, and not for smaller sub-slicing topologies. You can generate optimized GKE configurations that can improve performance for specific workloads, such as Redis and MySQL, by using the gcloud CLI. The configurations are ConfigMaps and ComputeClasses that apply performance recommendations to the workloads and the nodes. These optimizations are available in Preview for GKE version 1.31.1-gke.12000 or later. You can measure the performance improvements by using open source benchmarks. For more information, see Optimize for workloads on GKE. In GKE version 1.36.0-gke.3302001 and later, you can run Arm workloads on the Autopilot container-optimized compute platform by using the general-purpose autopilot-arm and autopilot-arm-spot ComputeClasses. You can select these ComputeClasses in Autopilot or Standard clusters. GKE runs the workloads that select these ComputeClasses in Autopilot mode. This compute platform improves Pod scheduling latency, especially during autoscaling operations. For more information, see the following documents: Deploy workloads in Autopilot mode Autopilot Arm workloads
Gemini - Gemini Cloud Assist is now supported within VPC Service Controls perimeters. For more information, see VPC Service Controls supported services.
IAM - Organization Policy Service custom constraints are available for Privileged Access Manager (PAM). You can use custom constraints to restrict how users create and modify entitlements and grants. This feature is in Preview. For more information, see Use custom organization policies for Privileged Access Manager.
KMS - Preview: Cloud KMS supports quantum-safe key import. You can use the following quantum-safe import methods: HPKE_KEM_XWING_HKDF_SHA256_AES_256_GCM HPKE_KEM_ML_KEM_768_HKDF_SHA256_AES_256_GCM HPKE_KEM_ML_KEM_1024_HKDF_SHA256_AES_256_GCM For more information about quantum-safe key import, see Quantum-safe key import.
Load Balancing - Regular expression URL rewrites ( regexRewrite ) for route rules in URL maps are now available for Application Load Balancers. You can use regular expression pattern rewrite actions to rewrite URL paths by substituting or removing URL path components before forwarding requests to your backends. For more information, see Regular expression URL rewrites for route rules. This feature is in Preview.
Looker - Full details on the release page.
NetApp - The thick clone (thin clone split) feature is generally available (GA) for the Flex Unified Default-mode service level. For more information, see Manage volume clones.
Network Intelligence Center - Connectivity Tests supports testing connectivity from a Database Migration Service private connection to a Cloud SQL instance. For more information, see Test from a Database Migration Service private connection to a Cloud SQL instance.
Policy Intelligence - The Policy Troubleshooter MCP server is generally available. To learn about using the Policy Troubleshooter MCP server to let agents and AI applications troubleshoot IAM issues and errors, see Use the Policy Troubleshooter remote MCP server.
Resource Manager - Preview: Semantic tags are available in Preview. Semantic tags provide standardized key-value metadata backed by OpenTelemetry (OTel) conventions. Tags automatically replicates Environment and Criticality attributes set on App Hub services and workloads as read-only system semantic tags ( google:AppHub/environment and google:AppHub/criticality ) on underlying direct resources. You can also view available semantics and their OTel mappings in the Semantic Catalog in the Google Cloud console. For more information, see Tags overview and Create and manage tags.
Security Command Center - For the Security Command Center Standard tier, AI Protection is supported for both projects and organizations. Project-level activations for the Standard tier include access to the AI security dashboard, basic inventory view (excluding Gemini models), and baseline security findings. Some features of AI Protection are only available for the Premium and Enterprise tiers or for organization-level activations. For more information, see Configure AI Protection. Security Command Center released new Malicious Skill runtime threat detectors for Google Kubernetes Engine (GKE), Cloud Run, and Agent Platform. These detectors identify when a malicious skill (an AI agent capability) is executed or loaded. A malicious skill is any malicious binary that has been tagged as an LLM skill by Google's threat intelligence. For more information, see the following: Container Threat Detection overview Cloud Run Threat Detection overview Agent Platform overview
VPC Service Controls - Preview stage support for the following integration: Google Antigravity in Gemini Enterprise General availability support for the following integration: Gemini Cloud Assist VPC Service Controls feature: The VPC Service Controls service patterns feature is generally available. You can use service patterns to explicitly configure which Google APIs (both supported and unsupported) can be accessed from VPC networks within a service perimeter when using the private VIP ( private.googleapis.com ) or a Private Service Connect endpoint with the all-apis bundle. For more information, see VPC Service Controls service patterns.
Virtual Private Cloud - Preview: You can create v2 IPv4 public advertised prefixes for bring your own IP addresses (BYOIP) that use Standard Tier IP addresses. For more information, see Network Service Tiers.
Workstation - Updated the following JetBrains preconfigured base images to version 2026.x: CLion 2026.1 GoLand 2026.2 IntelliJ Ultimate 2026.1 PhpStorm 2026.2 WebStorm 2026.1 RubyMine 2026.1 PyCharm 2026.1 Rider 2026.1
API Gateway - Route LLM requests with model routing You can now use model routing in API Gateway as a managed traffic management layer to accept OpenAI-compatible prompt requests, transcode them in-flight, and route them to specific foundation models in Gemini Enterprise Agent Platform Model Garden (including Gemini, Anthropic Claude, and OpenAI GPT models). Key benefits and capabilities include: Centralized traffic management: Consolidate AI traffic routing and lifecycle management at the network edge without hosting standalone client-side proxies. In-flight transcoding: Standardize client applications on an OpenAI-compatible REST interface while dynamically dispatching requests to diverse underlying Agent Platform Model Garden endpoints. OpenAPI 3.x configuration: Define model routing tables, explicit routing rules, and default model fallbacks using the new x-google-api-management.ai.models.routing and x-google-model-router OpenAPI 3.x extensions. For more information, see Overview of model routing and Configure model routing. Route LLM requests with model routing You can now use model routing in API Gateway as a managed traffic management layer to accept OpenAI-compatible prompt requests, transcode them in-flight, and route them to specific foundation models in Vertex AI Model Garden (including Gemini, Anthropic Claude, and OpenAI GPT models). Key benefits and capabilities include: Centralized traffic management: Consolidate AI traffic routing and lifecycle management at the network edge without hosting standalone client-side proxies. In-flight transcoding: Standardize client applications on an OpenAI-compatible REST interface while dynamically dispatching requests to diverse underlying Vertex AI Model Garden endpoints. OpenAPI 3.x configuration: Define model routing tables, explicit routing rules, and default model fallbacks using the new x-google-api-management.ai.models.routing and x-google-model-router OpenAPI 3.x extensions. For more information, see Overview of model routing and Configure model routing.
AlloyDB - AlloyDB now supports Best Matching 25 (BM25) indexes for full-text search in Preview. You can use the pg_textsearch extension to create BM25 indexes and optimize probabilistic ranking of full-text search. This feature is supported on AlloyDB instances running PostgreSQL 17 or 18. For more information, see Create and manage a BM25 index. AlloyDB integration with BigQuery lets you connect your operational and analytical data through real-time data access (lakehouse federation), periodic data synchronization, and one-time table syncs. These features are in Preview. For more information, see Choose how to access BigQuery data from AlloyDB. You can now sync tables from BigQuery into your AlloyDB instance, either as a one-time operation or on a periodic schedule. This feature (in Preview ) lets you enable operational analytics that benefit from low-latency, transactional access to your data lake. For more information, see Sync BigQuery data to AlloyDB.
Backup and DR Service - You can now change the backup plan associated with a Cloud SQL instance. This allows you to switch an instance to a different backup plan, provided the new plan uses the same backup vault and is in the same region as the instance. This feature is available through the Google Cloud console and gcloud CLI. To learn more, see Change the associated backup plan for a Cloud SQL instance.
BigQuery - The JDBC driver for BigQuery now supports OpenTelemetry for tracing and logging, which helps you monitor the performance of your database interactions and troubleshoot issues. Automatic exports to Google Cloud Observability are also available. This feature is generally available (GA). You can now use cross-cloud connections to query data in AWS, Azure, and Salesforce Data 360 from all BigQuery regions. These connections let you use more BigQuery features and are more cost efficient than standard connections that use BigQuery Omni. This feature is in Preview. Support for hybrid search (using the VECTOR_SEARCH function to combine a semantic search with a lexical (keyword) search) has been restored. Using HYBRID mode in the AI.SEARCH function has also been restored.
Billing - New filter and group-by option available in Cloud Billing Reports In Billing Reports, Cloud Billing has added the Originating products filter and Group by to provide additional options that let you analyze and understand your costs. Originating products are Google Cloud products that cause usage in another product. For example, Gemini Enterprise is an originating product when it causes usage in the Gemini Enterprise app. To help you track and analyze your AI spend, the Originating products dimension is used in the following ways: You can use the Originating products filter and group by option to configure your Cloud Billing report to track and analyze your Gemini Enterprise subscription and consumption costs. The Originating products dimension supports a new preset report for quick report configuration, called Gemini Enterprise costs by SKU. When you are viewing your costs in the Gemini Enterprise console, on the Gemini Enterprise > Usage & Spending page, the Originating products dimension supports the functionality of the costs displayed on the Gemini Enterprise Billing tab. For more information, see the following resources: Learn how to view Gemini Enterprise costs in Cloud Billing reports Learn more about analyzing billing data and cost trends with Reports Learn how to view Gemini Enterprise costs in the Gemini Enterprise console
CDN - Cloud CDN supports native image optimization at the Google network edge for global external Application Load Balancers. This feature offloads compute-intensive image transformations, such as resizing, cropping, and format conversion to reduce origin server load and egress costs. This feature is in Preview. Note: During the Preview phase, image optimization is available free of charge. Charges will apply once it becomes Generally Available (GA). For more information, see Optimize images with Cloud CDN.
Chronicle - [Spotlight Feature] Analyze feed activity with Cloud Logging This feature is in public preview. You can now monitor, debug, and troubleshoot Google SecOps SIEM ingestion pipelines and feeds using Cloud Logging. By sending, viewing, and querying ingestion and feed activity logs in Logs Explorer, you can diagnose log delivery issues, such as, missing, delayed, or failing logs, and decrease the time required to resolve ingestion anomalies. This visibility into push- and pull-based ingestion mechanisms lets you use Gemini Cloud Assist to investigate logging and metrics telemetry directly from the Google SecOps console. Additionally, you can use the Debug with logs option on the Feed management page to open Logs Explorer pre-filtered for a specific feed. For more information, see Analyze feed activity with Cloud Logging. Self-service Bindplane Enterprise license download This feature is currently in Preview. Google SecOps Enterprise Plus and Google Unified Security (GUS) customers can now download their Bindplane Enterprise (Google Edition) license key directly from the platform console under SIEM Settings > Collection Agents. For more information, see Bindplane Enterprise (Google Edition). The MANDIANT_ACTIVE_BREACH_IOC, MANDIANT_FUSION_IOC, and OPEN_SOURCE_INTEL_IOC feeds are deprecated in favor of the GTI_IOC feed. After March 18, 2027, we will be removing the MANDIANT_ACTIVE_BREACH_IOC, MANDIANT_FUSION_IOC, and OPEN_SOURCE_INTEL_IOC feeds. For more information on how to migrate, see Migrate Mandiant legacy feeds to GTI.
Chronicle SOAR - The deadline for Stage 2 of the SOAR migration to Google Cloud has been extended from September 30th to November 30th, 2026. For more information, refer to the SOAR migration guide. Release 6.3.96 is now available for all regions. Updated rich-text editor Upgraded the rich-text editor across Google SecOps, including the Cases Wall, Use Case Upload dialog, Report Template dialog, and Dashboard Editor widget. Key changes include: Simplified typography: Choose font sizes using semantic options (Small, Normal, Large, Huge). Legacy font sizes on existing text are preserved. Streamlined tables: You can insert or remove entire tables. Formatting inside table cells is no longer supported. Toolbar cleanup: Removed the Cut, Copy, and Paste buttons from the toolbar. Standard OS keyboard shortcuts remain supported. Visual alignment: Improved visual consistency between editor content during editing and after submission. Release 6.3.97 is being rolled out to the first phase of regions as listed here. This release contains internal and customer bug fixes.
Chronicle Security Operations - Full details on the release page.
Cloud Composer - The following Managed Airflow versions and builds have reached their end of support period: composer-3-airflow-2.10.5-build.11, composer-3-airflow-2.9.3-build.31, composer-2.13.9-airflow-2.9.3, and composer-2.13.9-airflow-2.10.5. New images are available in Managed Airflow (Gen 2): composer-2.17.9-airflow-2.11.1 (default) composer-2.17.9-airflow-2.10.5 New Airflow builds are available in Managed Airflow (Gen 3): composer-3-airflow-3.2.2-build.1 composer-3-airflow-3.1.8-build.3 composer-3-airflow-2.11.1-build.14 (default) composer-3-airflow-2.10.5-build.47 (Airflow 3.2.2, 3.1.8, and 2.11.1) The apache-airflow-providers-google package was upgraded to version 22.2.2. For more information about changes, see the apache-airflow-providers-google changelog. A new Managed Service for Apache Airflow release has started on August 05, 2026. Get ready for upcoming changes and features as we roll out the new release to all regions. This release is in progress at the moment. Listed changes and features might not be available in some regions yet.
Cloud Monitoring - The Telemetry API for metric ingestion is generally available (GA). You can ingest OTLP metrics into Cloud Monitoring by using an OpenTelemetry Collector, an OTLP exporter, and the Telemetry API. For more information, see OTLP metric ingestion overview.