Google Cloud Platform Newsletter

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News

New ways to migrate and scale Red Hat OpenShift on Google Cloud - Migrate and scale Red Hat OpenShift on Google Cloud with new updates like Cluster Services and OpenShift Virtualization. Optimize costs with Hyperdisk and custom machines.

DRA: A new era of Kubernetes device management with Dynamic Resource Allocation - The successor to Kubernetes Device Plugins, Dynamic Resource Allocation (DRA) takes the guesswork out of optimizing hardware resources.

Kubernetes as AI Infrastructure: Google Cloud, llm-d, and the CNCF - llm-d is officially a CNCF Sandbox project. As a key component of GKE Inference Gateway, llm-d is central to how Google Cloud supports AI inference.

Bringing dark web intelligence into the AI era - To get teams the critical data they need to make quick, accurate decisions about rising threats, we’re introducing a new dark web intelligence capability in Google Threat Intelligence.

Articles, Tutorials

Infrastructure, Networking, Security, Kubernetes

The open platform for the AI era: GKE, agents, and OSS innovation at KubeCon EU 2026 - Read about how we’re supporting the open-source Kubernetes ecosystem and Google Kubernetes Engine (GKE) at Kubecon + Cloudnativecon Europe 2026.

RSAC ’26: Supercharging agentic AI defense with frontline threat intelligence - From agentic AI defense to frontline threat intelligence to cloud security fundamentals, check out the news from Google Security at RSA Conference.

M-Trends 2026: Data, Insights, and Strategies From the Frontlines - Explore M-Trends 2026 report for frontline data on the latest cyber threats, including ransomware recovery denial and extreme persistence.

How to Build a Private API Gateway on GCP - A practical pattern for private GCP API Gateway access using an Internal Load Balancer, Cloud Run, and Private Google Access.

Granular Node Auto-Provisioning: what’s new in GKE 1.33 and 1.34 - GKE Node Auto-Provisioning (NAP) with ComputeClasses now offers a native, granular solution for managing node pools, enabling targeted, workload-specific auto-provisioning. This advancement allows dynamic resource allocation for particular workloads without broadly applying settings across an entire cluster.

1 Million Tokens Per Second: Qwen 3.5 27B on GKE with B200 GPUs - From 22K tok/s on 4x H100 to 1M+ on 96 B200s. Every failure included.

Three Kubernetes Tools That Actually Solved My Problems - My POV on how tired I am of managing On Premise Clusters.

App Development, Serverless, Databases, DevOps

Writing SQL in Data Connect - Google Cloud's Data Connect provides a comprehensive PostgreSQL solution for building secure, scalable applications using a GraphQL-based declarative syntax. To address the limitations of GraphQL for advanced database operations, Data Connect now introduces Native SQL.

Manhattan Associates powers over a billion daily API calls with Google Cloud databases - Manhattan Associates modernized their supply chain with Cloud SQL & BigQuery, processing a billion API calls daily. Learn how this enables their agentic AI suite.

This is Cloud Run: Configuration - This article provides a comprehensive guide to configuring Google Cloud Run, detailing how to tune essential settings like CPU and memory allocation, request timeouts, and scaling parameters to optimize performance for specific workloads.

Google Cloud But Locally: A Practical Guide to Community Emulators - A hands-on guide to building a realistic GCP stack on your laptop with Docker and open-source emulators.

Automating Google DMS Heterogeneous Migrations: SQL Server to AlloyDB via gCloud - This article demonstrates how to fully automate heterogeneous database migrations from SQL Server to AlloyDB using the Google Cloud CLI. It outlines steps for creating AI-powered conversion workspaces, converting and applying schemas, and initiating continuous migration jobs with Google's Database Migration Service (DMS).

Agentic Firestore: Smarter Agents with ADK and Google Remote Firestore MCP - Scaling my ADK agent with Google Managed Firestore MCP: A hybrid approach to smarter, leaner, and more modular chatbots.

Google Ads MCP in the Cloud. I Made Every Mistake So You Don’t Have To. - This article details the complex process of deploying an AI-powered Google Ads Model Context Protocol (MCP) agent on Google Cloud Run, highlighting numerous unexpected technical obstacles encountered. It provides crucial insights and solutions for common cloud deployment "gotchas," from authentication and networking to environment-specific configurations, to help others avoid similar pitfalls.

Why Your Pub/Sub Dead Letter Topic Isn’t Working in Cloud Run Jobs - Explicit NACKs don’t behave the way you think — here’s what actually works.

Accessing Google APIs Privately with Private Service Connect - Google Cloud's Private Service Connect offers a solution for accessing Google APIs privately, bypassing the compliance issues that arise when Private Google Access resolves to public IP addresses. It provides actual RFC1918 private IP addresses for Google APIs within your Virtual Private Cloud, ensuring traffic stays entirely private.

A Developer’s Guide to the AppOptimize API: Natively Supported vs. Custom Code - The Google Cloud AppOptimize API empowers developers to programmatically retrieve project and application-scoped cost and usage data, with native support for various dimensions and App Hub integration for cross-project aggregation. While it simplifies core cost reporting, developers must write custom code for functionalities like applying credits, managing custom tags, or complex multi-project analysis.

Big Data, Analytics, ML&AI

What Enterprise Data Engineering Actually Looks Like (vs What I Expected) - After 1.5 years building production pipelines at a Fortune Global 500 company, here’s what I wish someone had told me.

How to build production-ready AI agents with Google-managed MCP servers - In this guide, we show you how to build agents securely on our Google-managed MCP servers.

Easy as a green run: How Vail Resorts built an AI assistant to automate personalized recommendations - Vail Resorts developed "My Epic Assistant," an AI-powered digital concierge leveraging Google Cloud's Gemini models, to provide personalized recommendations and real-time support for skiers and snowboarders. This innovative system helps guests with everything from season pass selection to on-mountain information, enhancing their experience and significantly reducing the need for human agent escalations.

Five techniques to reach the efficient frontier of LLM inference - Learn the 5 essential techniques—including intelligent L7 routing, quantization, and speculative decoding—to move your LLM inference workloads closer to the efficient frontier, maximizing throughput and minimizing latency without increasing your hardware budget. Discover how to stop overpaying for every token.

How I Finally Killed My Massive BigQuery CASE Statements - Clean up your data with AI.SIMILARITY and AI.EMBED.

Stop Searching, Start Reading: Building a Hybrid Macro-to-Micro RAG Pipeline on BigQuery - How sequential vector + vectorless retrieval achieves both massive scale and reasoning-level precision — with SQL you can run today.

Architectural Blueprint: Data Decoupling Principles and Patterns - This architectural blueprint details data decoupling as the strategic separation of data storage from monolithic repositories into independent, domain-specific stores. It proposes a Dual-Plane Architecture, a Metadata Control Plane, and a phased delivery strategy to manage complexities like consistency and integration.

Building a High-Performance Lakehouse: Advanced ETL with BigQuery and Apache Iceberg - High-performance data warehouse like Google BigQuery or data lakehouse built on open formats like Apache Iceberg?

How FM Logistic tackled the traveling salesman problem at warehouse scale with AlphaEvolve - In a warehouse spanning eight football fields, with more than 17,700 picking locations, this Polish company was able to optimize package sorting thanks to AI tools from Google DeepMind.

A developer’s guide to training with Ironwood TPUs - Learn about the key techniques and tools within the JAX and MaxText ecosystem to improve training efficiency on Ironwood TPUs.

How to Get Your ADK Agent into Google's Official Community Showcase

Agent-User Interaction Protocol (AG-UI) with Agent Development Kit (ADK) - This article details the Agent-User Interaction Protocol (AG-UI), an open and lightweight standard for connecting agent backends to frontends. It provides practical guidance on integrating AG-UI with Google's Agent Development Kit (ADK), demonstrating methods for both starting fresh with a template and adding AG-UI to an existing ADK agent.

AI Cost Tracking on GCP: A Practical Guide to Vertex AI, Gemini API, and Model Spend - AI spending on Google Cloud Platform is rapidly growing but often hidden within billing exports across services like Vertex AI and Gemini API. This practical guide details how to uncover these costs, understand pricing models, allocate spending by model and team, and implement optimization strategies to avoid common cost traps.

Building a Semantic Intelligence Layer for the AI Data Stack - Combining OpenMetadata and MCP Toolbox to build context-rich, production-ready data agents.

All You Need to Know About Securing Sensitive Data in BigQuery: Encryption, Masking, and Best Practices - A Practical Guide to Protecting Your Data with GCP Tools and Techniques.

Various

The new AI literacy: Insights from student developers - Discover how UC Berkeley student developers use AI as a strategic learning partner, rather than a shortcut, to prepare for their tech careers.

Closing the knowledge gap with agent skills - To bridge the gap between static model knowledge and rapidly evolving software practices, Google DeepMind developed a "Gemini API developer skill" that provides agents with live documentation and SDK guidance. Evaluation results show a massive performance boost, with the gemini-3.1-pro-preview model jumping from a 28.2% to a 96.6% success rate when equipped with the skill. This lightweight approach demonstrates how giving models strong reasoning capabilities and access to a "source of truth" can effectively eliminate outdated coding patterns.

Jump to play: Building with Gemini & MediaPipe - The provided workflow streamlines motion-controlled game development by using Gemini Canvas to rapidly prototype mechanics like the MediaPipe Pose Landmarker through high-level prompting. Developers can refine these prototypes in Google AI Studio by optimizing for low-latency "lite"; models and stable tracking points, such as shoulder landmarks, to ensure responsive gameplay. The process concludes by using Gemini Code Assist to refactor experimental code into a modular, production-ready application capable of supporting various multimodal inputs.

Build a smart financial assistant with LlamaParse and Gemini 3.1 - This blog post introduces a workflow for extracting high-quality data from complex, unstructured documents by combining LlamaParse with Gemini 3.1 models. It demonstrates an event-driven architecture that uses Gemini 3.1 Pro for agentic parsing of dense financial tables and Gemini 3.1 Flash for cost-effective summarization.

Slides, Videos, Audio

Security Podcast - #268 Weaponizing the Administrative Fabric: Cloud Identity and SaaS Compromise in M Trends 2026.

GCP Bytes Podcast - #37 In this episode we discuss; Server upgrade and AI, Windsurf IDE, DDR5 1+1 Kits, German Government, GDG, Supermicro, Google Partner Chief, VMWare, Strait Of Hormuz, Wiz Deal, Firebase Studio, Google and DOD, AI Overviews opt out, Chrome Zero Day, AI Driven Attacks, NemoClaw, Palantir AI, DC Build Expectations, US AI Power.

Releases

Compute Engine - Feature: Preview: The instance flexibility policy of a managed instance group (MIG) lets you override the minimum CPU platform and disk definition that is specified in the MIG's instance template. With these overrides, you can select machine types that run on different CPU platforms and that have different architectures. For more information, see About instance flexibility in MIGs. Feature: Generally available: The maximum throughput for a Hyperdisk Balanced High Availability disk is increased to 2,400 MiB/s from 1,200 MiB/s. Hyperdisk Balanced High Availability provides high availability block storage for mission-critical workloads by synchronously replicating data between two zones within a region. For more information, see Hyperdisk Balanced High Availability overview. Security: A vulnerability (CVE-2026-23268) about CrackArmor was discovered and has been addressed. For more information, see the GCP-2026-015 security bulletin.

VPC Service Controls - Feature: Preview stage support for the following integration: Oracle Database@Google Cloud Feature: Preview stage support for the following integration: Oracle Database@Google Cloud Feature: General availability support for the following integration: Oracle Database@Google Cloud

Agent Assist - Feature: Agent Assist offers Gemini Enterprise for Customer Experience tools for AI coach in GA. These tools enable virtual agents to connect with external systems to retrieve, update, format, or analyze information.

Cloud Deploy - Feature: You can now provide user-defined actions using tasks. This includes deploy hooks, deployment verification, analysis, and custom target types. This feature is generally available. Feature: You can now analyze the performance of your deployed applications using the monitoring platform of your choice and automatically trigger actions such as rollbacks. This feature is generally available.

Looker - Announcement: To enhance security, the Looker language SDKs and the Looker API /login endpoint are being modified. They will exclusively accept passing credentials in the HTTP request body and will no longer support using URL query parameters. Release date: This update is expected to take effect with the Looker 26.18 release in October 2026. Potential impact: Any scripts or applications currently passing credentials in the URL query parameters in the Looker SDK libraries, or directly calling the /login API endpoint, will fail after this update. Who is affected: All customers using Looker SDKs, custom scripts, or applications that call the /login API endpoint directly. Action required: We have sent a message to your affected customers. However, to help avoid service disruptions, please recommend that they evaluate their environment and take the following actions before October 2026: Upgrade SDKs: Upgrade the Looker SDKs to version 26.4 or later as soon as possible. Update custom scripts: Modify any scripts or applications that rely on passing Looker API credentials in URL query parameters so that they will pass credentials in the HTTP request body. Test the environment: Validate these changes in an environment that can identify these potential misconfigurations. Fixed: An issue has been fixed where the LookML Assistant could return a 404 error. This feature now performs as expected. Fixed: An issue has been fixed where the LookML dashboards folder could fail to display the complete list of LookML dashboards. This feature now performs as expected. Fixed: An issue has been fixed where visualization tooltips on dashboards could use incorrect background or text colors. This feature now performs as expected. Fixed: An issue has been fixed where tabs could be automatically added to existing dashboards. This feature now performs as expected. Announcement: Looker 26.6 is expected to include the following changes, features, and fixes: Expected Looker (original) deployment start: Sunday, March 22, 2026 Expected Looker (original) final deployment and download available: Sunday, April 5, 2026 Expected Looker (Google Cloud core) deployment start: Monday, March 23, 2026 Expected Looker (Google Cloud core) final deployment: Friday, April 3, 2026 Breaking: Tabbed dashboards with unsupported layouts will now display a warning message prompting users to update to a new layout. Fixed: An issue has been fixed where creating or updating database connections that use OAuth (such as Snowflake or BigQuery) could fail with the error JDBC Parameter Validation Failed. This feature now performs as expected. Fixed: When no theme is selected, the Theme picker will now display "Default" rather than "None". Fixed: An issue has been fixed where dashboard themes were not applying color collections correctly. This feature now performs as expected. Fixed: An issue has been fixed where buttons on dashboards that used the extension framework could unnecessarily add /embed/ to link URLs. This feature now performs as expected. Fixed: An issue has been fixed where the font and background color picker was not accessible when you edited visualizations on merge queries. This feature now performs as expected. Fixed: An issue has been fixed where opening the Interaction Details dialog on the Historical Analytics Interactions Search dashboard in a new window could result in a 401 error. This feature now performs as expected. Fixed: An issue has been fixed where searching for content could return a 500 error. This feature now performs as expected. Fixed: An issue has been fixed where pressing Enter to confirm IME composition when writing a message in Conversational Analytics would prematurely submit the message. This feature now performs as expected. Feature: As part of Looker 26.6, Conversational Analytics now offers new modes for asking questions. Fast mode allows you to get answers more quickly. Thinking mode allows you to ask more complex questions and test your agent's capabilities. Feature: As part of Looker 26.6, Conversational Analytics will now ask you questions to clarify any ambiguities in your original query.

Chronicle - Announcement: New parser documentation now available on the release page.

Billing - Change: Billing account permissions now streamline access to Google payments profiles and payments accounts We've launched a billing IAM permissions update that simplifies and streamlines Cloud Billing account access to the associated Google payments profiles and accounts, for users who have the billing.accounts.updatePaymentInfo permission on their Cloud Billing account. Prior to this update: While working in the Cloud Billing console, to access and edit the associated Google payments profile and account information, all Cloud Billing account users needed two sets of permissions: Identity and Access Management (IAM) permissions on the Cloud Billing account to access and manage the billing account. Edit or Admin access permissions on the associated Google payments profile in order to add and edit payment methods, make a manual payment, and update payments profile info such as the business name, address, tax info, and payments account settings. After this permissions update: Cloud Billing account users with the billing.accounts.updatePaymentInfo permission on the billing account can access and edit Google payments profile and account information directly from the Cloud Billing console, without needing additional permissions on the payments profile itself. This includes users with the Billing Account Administrator role ( roles/billing.admin ) and those granted this permission via a custom role. Note that this permissions update applies only to Cloud Billing accounts associated with an Organization (or Business) Google payments profile type. You can verify your account type on the Payment settings page in the Cloud Billing console. With the billing.accounts.updatePaymentInfo permission on the billing account, users can do the following: View payments history and documents related to the associated Google payments profile. Add and edit payment methods on a self-serve (online) billing account. Make a manual payment to a self-serve (online) billing account. Update payments profile info such as the business name, address, tax info, and payments account settings. Billing account users with the billing.accounts.updatePaymentInfo permission won't have the Manage users or Admin with all permissions level of access on the Google payments profile. To fully manage a payments profile and gain Manage users and Admin permissions, billing account users still require additional Google payments user permissions granted on the associated payments profile.

Datastore - Feature: Regional and Multi-Regional endpoints for the Datastore API are now Generally Available ( GA ). You can use a Regional or a Multi-Regional endpoint to ensure that your application's requests are transmitted, stored and processed in the same region or multi-region as your database's location. To learn more, see the Datastore regional endpoints guide. You can also use Private Service Connect regional endpoints and Private Service Connect backends to connect to the regional and the multi-regional endpoints of the Datastore API.

Cloud Firestore - Feature: Regional and Multi-Regional endpoints for the Firestore API are now Generally Available ( GA ). You can use a Regional or a Multi-Regional endpoint to ensure that your application's requests are transmitted, stored and processed in the same region or multi-region as your database's location. To learn more, see the Firestore regional endpoints guide. You can also use Private Service Connect regional endpoints and Private Service Connect backends to connect to the regional and the multi-regional endpoints of the Firestore API.

BigQuery - Feature: You can clean, transform, and enrich data from files in Cloud Storage and Google Drive in your BigQuery data preparations. For more information, see Prepare data with Gemini. This feature is generally available (GA). Feature: The following functions are now generally available (GA): AI.EMBED: create embeddings from text or image data. AI.SIMILARITY: compute the semantic similarity between pairs of text, pairs of images, or across text and images. Feature: You can now use the BigQuery Data Transfer Service remote MCP server to enable AI agents to create, manage, and run data transfers. This feature is in Preview. Feature: You can now use the BigQuery Migration Service MCP server to perform SQL translation tasks, including translating SQL queries into GoogleSQL syntax, generating DDL statements from SQL input queries, and getting explanations of SQL translations. This feature is in preview. Feature: You can use the BigQuery migration assessment for Snowflake to assess the complexity of migrating from Snowflake to BigQuery. This feature is generally available (GA). Announcement: The Gemini for Google Cloud API (cloudaicompanion.googleapis.com) is now enabled for existing BigQuery projects in the European jurisdiction. Feature: In BigQuery Data Transfer Service, you can monitor resource-level status reporting for Hive managed tables to track progress and view granular error details for individual tables. This feature is in preview. Feature: You can now use Cloud resource connections with EXPORT DATA statements to reverse ETL BigQuery data to Spanner. This feature is generally available (GA).

Cloud NGFW - Feature: Secure tags with a purpose-data attribute specifying a VPC network or an organization now support VPC networks that are connected using VPC Network Peering. For more information, see Secure tags for firewalls. This feature is available in General Availability. Feature: You can use the URL filtering service to filter your workload traffic by using domain and Server Name Indication (SNI) information available in the egress HTTP(S) messages. For more information, see URL filtering service overview. This feature is available in General Availability.

Document AI - Feature: Custom classifier models pretrained-classifier-v1.6-2026-03-09 and pretrained-classifier-v1.6-pro-2026-03-09 are available in Preivew. Feature: Custom splitter models pretrained-splitter-v1.6-2026-03-09 and pretrained-splitter-v1.6-pro-2026-03-09 are available in Preview. Feature: Custom splitter model pretrained-splitter-v1.5-2025-07-14 is available in General Availability (GA).

Bigtable - Feature: You can manage Bigtable tiered storage configuration in Google Cloud console and view tiered storage metrics in system insights. For more information, see Create and manage tables. Announcement: Bigtable client for Java has modernized its Admin API. For detailed migration steps and code examples, see Upgrading client libraries.

Dataproc - Announcement: New Dataproc on Compute Engine subminor image versions: 2.1.112-debian11, 2.1.112-rocky8, 2.1.112-ubuntu20, 2.1.112-ubuntu20-arm 2.2.80-debian12, 2.2.80-rocky9, 2.2.80-ubuntu22, 2.2.80-ubuntu22-arm 2.3.27-debian12, 2.3.27-ml-ubuntu22, 2.3.27-rocky9, 2.3.27-ubuntu22, 2.3.27-ubuntu22-arm

Cloud Storage - Announcement: Anywhere Cache has been renamed to Rapid Cache.

Cloud Monitoring - Feature: The Telemetry API's supports up to 60,000 metric-ingestion requests per minute per region. The regional quota replaces the global quota. To learn more, see Telemetry API quotas and limits for metric ingestion.

Cloud Trace - Feature: The Telemetry API supports trace ingestion of up to 2.4GB per minute for the following regions: asia-east1, asia-northeast1, asia-southeast1, and asia-south1 europe-west1, europe-west2, europe-west3, and europe-west4 us-central1, us-east4, and us-west1. For all other regions, the Telemetry API supports trace ingestion of up to 300 MB per minute. These regional byte-based quotas replace a global quota which limited the number of requests per minute. To learn more, see Telemetry API limits and quotas.

Contact Center AI Platform - Complete details on the release page.

Cloud Router - Feature: Cloud Router supports named sets in Preview for BGP route policies. Named sets are used to group together expressions of either communities or BGP prefixes, allowing them to be managed or referenced as a single entity. For more information, see BGP route policies overview.

AlloyDB - Feature: Database server compatibility with PostgreSQL version 18 is now generally available ( GA ): You can create AlloyDB clusters with PostgreSQL 18 compatibility. You can upgrade existing AlloyDB clusters running PostgreSQL major versions 14, 15, 16, or 17 to PostgreSQL major version 18 with one click. You can use Database Migration Service to migrate databases to AlloyDB. Feature: The following AlloyDB AI features are available in Preview: You can now use the ai.hybrid_search() function, which fuses results from each search type into a single list using the Reciprocal Rank Fusion (RRF) algorithm. For more information, see Run hybrid vector similarity search. AlloyDB supports the rum extension for complex full-text search operations. The rum extension extends standard GIN indexes by storing positional information directly in the index. This enables faster phrase searches and relevance ranking without needing to access the table data. For more information, see Create and manage a RUM index. Change: When no major version is specified, AlloyDB for PostgreSQL now defaults to PostgreSQL major version 17 for new clusters.

Cloud Spanner - Feature: The Spark Spanner connector supports writing a Spark Dataframe to a Spanner table using the Spark data source API. For more information, see Use the Spark Spanner connector.

GKE new features - Feature: To provide more controls over the control plane version upgrade, you can now do the following: Configure a frequency of disruption from auto-upgrades by using the cluster disruption budget. For more information, see Control the frequency of disruption from auto-upgrades. Continue using an existing control plane patch for a longer period, which facilitates large-scale upgrade and downgrade operations. For more information, see Patch version support.

Error Reporting - Feature: You can use the Error Reporting API MCP server to let agents and AI applications interact with your error data. This feature is in Preview.

Cloud SQL MySQL - Feature: MySQL 8.0.44 is now the default minor version for Cloud SQL for MySQL 8.0. For more information about minor version support in Cloud SQL for MySQL, see MySQL 8.0.

Memorystore for Redis Cluster - Feature: In addition to the per-instance CA mode, Memorystore for Redis Cluster offers the following new CA modes: Shared CA: a managed, regionalized CA infrastructure. For each region, you can download a single CA certificate bundle. This bundle is valid for all clusters located in a region that you configure to use the shared CA. Using a shared CA reduces the number of certificates that clients need to manage. This CA mode is available in Preview. Customer-managed CA: use your own CA pool that's hosted on Certificate Authority Service. If your client applications are configured to trust this CA, then your applications can connect to a cluster without you having to download and install additional CA certificates. This gives you greater control and helps you meet compliance requirements. This CA mode is available in Preview. Feature: Memorystore for Redis Cluster supports version 1.0 of JSON documents. This feature is available in Preview.

Cloud Composer - Announcement: Cloud Composer 2 environments can no longer be created in Melbourne (australia-southeast2). We're switching this region to supporting only Cloud Composer 3 environments. Existing Cloud Composer 2 environments in this region aren't affected by this change.

Workload Manager - Feature: Generally available: Workload Manager supports deploying Oracle Database workloads on Google Cloud using the Guided Deployment Automation. For more information, see Overview of Oracle Database workload deployment.

Security Command Center - Announcement: Risk Engine has launched enhanced heuristics to help identify default high-value resources. If you are using the default high-value resource set, you might observe changes in the exposure scores of their findings, resources, and issues. For information about these changes, see Default high-value resource set.

Chronicle SOAR - Announcement: Release 6.3.80 is now available for all regions. Announcement: Release 6.3.81 is being rolled out to the first phase of regions as listed here. This release contains internal and customer bug fixes.