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Magnite stands as the largest independent sell-side advertising platform, providing an essential bridge between publishers and advertisers. At its core, Magnite streamlines the advertising process, facilitating the buying and selling of advertising space across various channels, including connected TV (CTV), mobile, and desktop environments. By leveraging advanced technology and data analytics, Magnite offers a comprehensive suite of tools and services designed to maximize ad revenue for publishers while helping them effectively reach their target audiences. A strategic acquisition and the need for integration In 2021, Magnite made a decisive move to strengthen its position in the CTV advertising market by acquiring SpringServe, a leader in CTV ad-serving technology. While this acquisition was a strategic fit for Magnite, integrating the two companies’ data platforms presented a unique set of challenges. Magnite was operating its Snowflake data platform on AWS US West, whereas SpringServe had its presence on AWS US East. As business needs demanded more frequent data sharing across these units, the costs associated with transferring large data sets across these cloud regions also began to rise. Recognizing the inefficiencies and escalating costs of operating in separate cloud regions, Magnite decided to consolidate its operations in AWS US East. This decision was not only cost-effective but also strategically aligned with the location of many of their clients, facilitating easier data sharing between Magnite and SpringServe business units, as well as with external clients who also use Snowflake as their cloud data platform. Leveraging account replication powered by Snowgrid The major hurdle in this consolidation process was the migration of Magnite’s Snowflake account, which contained more than 1 Petabyte (PB) of data spread across numerous databases. Additionally, Magnite’s Snowflake account was integrated with an identity provider for Single Sign-On (SSO). There was a strong requirement to seamlessly migrate hundreds of users, roles, and other account-level objects, including compute resources and cloud storage integrations. Snowflake’s account replication capabilities powered by Snowgrid, dramatically simplified this whole migration experience. This powerful feature allowed Magnite to quickly establish a failover group that defined all the objects that needed to be migrated. Remarkably, the entire dataset with over 1.2 PBs was replicated in just one day. Account replication also empowers consistent application of all privileges and grants on various objects, thereby maintaining data integrity and preventing unauthorized access. A testament to efficiency and speed The migration process, including testing and setup, was completed in merely a week, significantly faster than anticipated. The incremental refreshes from US West to US East required to synchronize data were also very quick, and the final switchover occurred in minutes. The seamless experience allowed all the client applications connected to Snowflake to be completely unaware of this whole migration effort and required zero client-side code changes. The entire migration journey was owned and managed independently by a small data platform team at Magnite. “The speed of replication exceeded our expectations,” said Matt Sullivan, Director of Engineering at Magnite praised the migration. “The whole experience of setting up account replication and completing the migration was incredibly smooth and ran without a hitch. It’s a testament to Snowflake’s robust platform and the careful planning by our teams.” Magnite’s successful migration to a unified cloud region underscores the importance of agile data-management strategies in today’s competitive landscape. Unforeseen events like executive realignments, acquisitions and mergers can throw a curveball at your cloud strategy. A platform with a cross-cloud and cross-region technology layer, like Snowgrid, guarantees a seamless transition when the need arises — giving you peace of mind and future-ready data management. Learn more about how your company can migrate across cloud platforms with speed, efficiency, and minimal to no disruption with Cross-Cloud Snowgrid. The post Magnite’s Seamless Petabyte Scale Cross-Region Migration with Snowgrid appeared first on Snowflake. View the full article

Google Cloud Next made a big splash in Las Vegas this week! From our opening keynote showcasing incredible customer momentum to exciting product announcements, we covered how AI is transforming the way that companies work. You can catch up on the highlights in our 14 minute keynote recap! Developers were front and center at our Developer keynote and in our buzzing Innovators Hive on the Expo floor (which was triple the size this year!). Our nearly 400 partner sponsors were also deeply integrated throughout Next, bringing energy from the show floor to sessions and evening events throughout the week. Last year, we talked about the exciting possibilities of generative AI, and this year it was great to showcase how customers are now using it to transform the way they work. At Next ‘24, we featured 300+ customer and partner AI stories, 500+ breakout sessions, hands-on demos, interactive training sessions, and so much more. It was a jam-packed week, so we’ve put together a summary of our announcements which highlight how we’re delivering the new way to cloud. Read on for a complete list of the 218 (yes, you read that right) announcements from Next ‘24: Gemini for Google Cloud We shared how Google's Gemini family of models will help teams accomplish more in the cloud, including: 1. Gemini for Google Cloud, a new generation of AI assistants for developers, Google Cloud services, and applications. 2. Gemini Code Assist, which is the evolution of the Duet AI for Developers. 3. Gemini Cloud Assist, which helps cloud teams design, operate, and optimize their application lifecycle. 4. Gemini in Security Operations, generally available at the end of this month, converts natural language to new detections, summarizes event data, recommends actions to take, and navigates users through the platform via conversational chat. 5. Gemini in BigQuery, in preview, enables data analysts to be more productive, improve query performance and optimize costs throughout the analytics lifecycle. 6. Gemini in Looker, in private preview, provides a dedicated space in Looker to initiate a chat on any topic with your data and derive insights quickly. 7. Gemini in Databases, also in preview, helps developers, operators, and database administrators build applications faster using natural language; manage, optimize and govern an entire fleet of databases from a single pane of glass; and accelerate database migrations. Customer Stories We shared new customer announcements, including: 8. Cintas is leveraging Google Cloud’s gen AI to develop an internal knowledge center that will allow its customer service and sales employees to easily find key information. 9. Bayer will build a radiology platform that will help Bayer and other companies create and deploy AI-first healthcare apps that assist radiologists, ultimately improving efficiency and diagnosis turn-around time. 10. Best Buy is leveraging Google Cloud’s Gemini large language model to create new and more convenient ways to give customers the solutions they need, starting with gen AI virtual assistants that can troubleshoot product issues, reschedule order deliveries, and more. 11. Citadel Securities used Google Cloud to build the next generation of its quantitative research platform that increased its research productivity and price-performance ratio. 12. Discover Financial is transforming customer experience by bringing gen AI to its customer contact centers to improve agent productivity through personalized resolutions, intelligent document summarization, real-time search assistants, and enhanced self-service options. 13. IHG Hotels & Resorts is using Gemini to build a generative AI-powered chatbot to help guests easily plan their next vacation directly in the IHG Hotels & Rewards mobile app. 14. Mercedes-Benz will expand its collaboration with Google Cloud, using our AI and gen AI technologies to advance customer-facing use cases across e-commerce, customer service, and marketing. 15. Orange is expanding its partnership with Google Cloud to deploy generative AI closer to Orange’s and its customers’ operations to help meet local requirements for trusted cloud environments and accelerate gen AI adoption and benefits across autonomous networks, workforce productivity, and customer experience. 16. WPP will leverage Google Cloud’s gen AI capabilities to deliver personalization, creativity, and efficiency across the business. Following the adoption of Gemini, WPP is already seeing internal impacts, including real-time campaign performance analysis, streamlined content creation processes, AI narration, and more. 17. Covered California, California’s health insurance marketplace, will simplify the healthcare enrollment process using Google Cloud’s Document AI, enabling the organization to verify more than 50,000 healthcare documents with a 84% verification rate per month. Workspace and collaboration The next wave of innovations and enhancements are coming to Google Workspace: 18. Google Vids, a key part of our Google Workspace innovations, is a new AI-powered video creation app for work that sits alongside Docs, Sheets and Slides. Vids will be released to Workspace Labs in June. 19. Gemini is coming to Google Chat in preview, giving you an AI-powered teammate to summarize conversations, answer questions, and more. 20. The new AI Meetings and Messaging add-on is priced at $10 per user, per month, and includes: Take notes for me, now in preview, translate for me, coming in June, which automatically detects and translates captions in Meet, with support for 69 languages, and automatic translation of messages and on-demand conversation summaries in Google Chat, coming later this year. 21. Using large language models, Gmail can now block an additional 20% more spam and evaluate 1,000 times more user-reported spam every day. 22. A new AI Security add-on allows IT teams to automatically classify and protect sensitive files in Google Drive, and is available for $10 per user, per month. 23. We’re extending DLP controls and classification labels to Gmail in beta. 24. We’re adding experimental support for post-quantum cryptography (PQC) in client-side encryption with our partners Thales and Fortanix. 25. Voice prompting and instant polish in Gmail: Send emails easily when you’re on the go with voice input in Help me write, and convert rough notes to a complete email with one click. 26. A new tables feature in Sheets (generally available in the coming weeks) formats and organizes data with a sleek design and a new set of building blocks — from project management to event planning templates witautomatic alerts based on custom triggers like a change in a status field. 27. Tabs in Docs (generally available in the coming weeks) allow you to organize information in a single document rather than linking to multiple documents or searching through Drive. 28. Docs now supports full-bleed cover images that extend from one edge of your browser to the other; generally available in the coming weeks. 29. Generally available in the coming weeks, Chat will support increased member capacity of up to 500,000 in spaces. 30. Messaging interoperability for Slack and Teams is now generally available through our partner Mio. AI infrastructure 31. The Cloud TPU v5p GA is now generally available. 32. Google Kubernetes Engine (GKE) now supports Cloud TPU v5p and TPU multi-host serving, also generally available. 33. A3 Mega compute instance powered by NVIDIA H100 GPUs offers double the GPU-to-GPU networking bandwidth of A3, and will be generally available in May. 34. Confidential Computing is coming to the A3 VM family, in preview later this year. 35. The NVIDIA Blackwell GPU platform will be available on the AI Hypercomputer architecture in two configurations: NVIDIA HGX B200 for the most demanding AI, data analytics, and HPC workloads; and the liquid-cooled GB200 NVL72 GPU for real-time LLM inference and training massive-scale models. 36. New caching capabilities for Cloud Storage FUSE improve training throughput and serving performance, and are generally available. 37. The Parallelstore high-performance parallel filesystem now includes caching in preview. 38. Hyperdisk ML in preview is a next-generation block storage service optimized for AI inference/serving workloads. 39. The new open-source MaxDiffusion is a new high-performance and scalable reference implementation for diffusion models. 40. MaxText, a JAX LLM, now supports new LLM models including Gemma, GPT3, LLAMA2 and Mistral across both Cloud TPUs and NVIDIA GPUs. 41. PyTorch/XLA 2.3 will follow the upstream release later this month, bringing single program, multiple data (SPMD) auto-sharding, and asynchronous distributed checkpointing features. 42. For Hugging Face PyTorch users, the Hugging Face Optimum-TPU package lets you train and serve Hugging Face models on TPUs. 43. Jetstream is a new open-source, throughput- and memory-optimized LLM inference engine for XLA devices (starting with TPUs); it supports models trained with both JAX and PyTorch/XLA, with optimizations for popular open models such as Llama 2 and Gemma. 44. Google models will be available as NVIDIA NIM inference microservices. 45. Dynamic Workload Scheduler now offers two modes: flex start mode (in preview), and calendar mode (in preview). 46. We shared the latest performance results from MLPerf™ Inference v4.0 using A3 virtual machines (VMs) powered by NVIDIA H100 GPUs. 47. We shared performance benchmarks for Gemma models using Cloud TPU v5e and JetStream. 48. We introduced ML Productivity Goodput, a new metric to measure the efficiency of an overall ML system, as well as an API to integrate into your projects, and methods to maximize ML Productivity Goodput. Vertex AI 49. Gemini 1.5 Pro is now available in public preview in Vertex AI, bringing the world’s largest context window to developers everywhere. 50. Gemini 1.5 Pro on Vertex AI can now process audio streams including speech, and the audio portion of videos. 51. Imagen 2.0, our family of image generation models, can now be used to create short, 4-second live images from text prompts. 52. Image editing is generally available in Imagen 2.0, including inpainting/outpainting and digital watermarking powered by Google DeepMind’s SynthID. 53. We added CodeGemma, a new model from our Gemma family of lightweight models, to Vertex AI. 54. Vertex AI has expanded grounding capabilities, including the ability to directly ground responses with Google Search, now in public preview. 55. Vertex AI Prompt Management, in preview, helps teams improve prompt performance. 56. Vertex AI Rapid Evaluation, in preview, helps users evaluate model performance when iterating on the best prompt design. 57. Vertex AI AutoSxS is now generally available, and helps teams compare the performance of two models. 58. We expanded data residency guarantees for data stored at-rest for Gemini, Imagen, and Embeddings APIs on Vertex AI to 11 new countries: Australia, Brazil, Finland, Hong Kong, India, Israel, Italy, Poland, Spain, Switzerland, and Taiwan. 59. When using Gemini 1.0 Pro and Imagen, you can now limit machine-learning processing to the United States or European Union. 60. Vertex AI hybrid search, in preview, integrates vector-based and keyword-based search techniques to ensure relevant and accurate responses for users. 61. The new Vertex AI Agent Builder, in preview, lets developers build and deploy gen AI experiences using natural language or open-source frameworks like LangChain on Vertex AI. 62. Vertex AI includes two new text embedding models in public preview: the English-only text-embedding-preview-0409, and the multilingual text-multilingual-embedding-preview-0409 Core infrastructure Thomas with the Google Axion chip 63. We expanded Google Cloud’s compute portfolio, with major product releases spanning compute and storage for general-purpose workloads, as well as for more specialized workloads like SAP and high-performance databases. 64. Google Axion is our first custom Arm-based CPU designed for the data center, and will be in preview in the coming months. 65. Now in preview, the Compute Engine C4 general-purpose VM provides high performance paired with a controlled maintenance experience for your mission-critical workloads. 66. The general-purpose N4 machine series is built for price-performance with Dynamic Resource Management, and is generally available. 67. C3 bare-metal machines, available in an upcoming preview, provide workloads with direct access to the underlying server’s CPU and memory resources. 68. New X4 memory-optimized instances are now in preview, through this interest form. 69. Z3 VMs are designed for storage-dense workloads that require SSD, and are generally available. 70. Hyperdisk Storage Pools Advanced Capacity, in general availability, and Advanced Performance in preview, allow you to purchase and manage block storage capacity in a pool that’s shared across workloads. 71. Coming to general availability in May, Hyperdisk Instant Snapshots provide near-zero RPO/RTO for Hyperdisk volumes. 72. Google Compute Engine users can now use zonal flexibility, VM family flexibility, and mixed on-demand and spot consumption to deploy their VMs. As part of Google Distributed Cloud (GDC) offering, we announced: 73. A generative AI search packaged solution powered by Gemma open models will be available in preview in Q2 2024 on GDC to help customers retrieve and analyze data at the edge or on-premises. 74. GDC has achieved ISO27001 and SOC2 compliance certifications. 75. A new managed Intrusion Detection and Prevention Solution (IDPS) integrates Palo Alto Networks threat prevention technology with GDC, and is now generally available. 76. GDC Sandbox, in preview, helps application developers build and test services designed for GDC in a Google Cloud environment, without needing to navigate the air-gap and physical hardware. 77. A preview GDC storage flexibility feature can help you grow your storage independent of compute, with support for block, file, or object storage. 78. GDC can now run in disconnected mode for up to seven days, and offers a suite of offline management features to help ensure deployments and workloads are accessible and working while they are disconnected; this capability is generally available. 79. New Managed GDC Providers who can sell GDC as a managed service include Clarence, T-Systems, and WWT.and a new Google Cloud Ready — Distributed Cloud badge signals that a solution has been tuned for GDC. 80. GDC servers are now available with an energy-efficient NVIDIA L4 Tensor Core GPU. 81. Google Distributed Cloud Hosted (GDC Hosted) is now authorized to host Top Secret and Secret missions for the U.S. Intelligence Community, and Top Secret missions for the Department of Defense (DoD). From our Google Cloud Networking family, we announced: 82. Gemini Cloud Assist, in preview, provides AI-based assistance to solve a variety of networking tasks such as generating configurations, recommending capacity, correlating changes with issues, identifying vulnerabilities, and optimizing performance. 83. Now generally available, the Model as a Service Endpoint solution uses Private Service Connect, Cloud Load Balancing, and App Hub lets model creators own the model service endpoint to which application developers then connect. 84. Later this year, Cloud Load Balancing will add enhancements for inference workloads: Cloud Load Balancing with custom metrics, Cloud Load Balancing for streaming inference, and Cloud Load Balancing with traffic management for AI models. 85. Cloud Service Mesh is a fully managed service mesh that combines Traffic Director’s control plane and Google’s open-source Istio-based service mesh, Anthos Service Mesh. A service-centric Cross-Cloud Network delivers a consistent, secure experience from any cloud to any service, and includes the following enhancements: 86. Private Service Connect transitivity over Network Connectivity Center, available in preview this quarter, enables services in a spoke VPC to be transitively accessible from other spoke VPCs. 87. Cloud NGFW Enterprise (formerly Cloud Firewall Plus), now GA, provides network threat protection powered by Palo Alto Networks, plus network security posture controls for org-wide perimeter and Zero Trust microsegmentation. 88. Identity-based authorization with mTLS integrates the Identity-Aware Proxy with our internal application Load Balancer to support Zero Trust network access, including client-side and soon, back-end mutual TLS. 89. In-line network data-loss prevention (DLP), in preview soon, integrates Symantec DLP into Cloud Load Balancers and Secure Web Proxy using Service Extensions. 90. Partners Imperva, HUMAN Security, Palo Alto Networks and Traceable are integrating their advanced web protection services into Service Extensions, as are web services providers Cloudinary, Nagra, Queue-it, and Datadog. 91. Service Extensions now has a library of code examples to customize origin selection, adjust headers, and more. 92. Private Service Connect is now fully integrated with Cloud SQL, and generally available. There are many improvements to our storage offerings: 93. Generate insights with Gemini lets you use natural language to analyze your storage footprint, optimize costs, and enhance security across billions of objects. It is available now through the Google Cloud console as an allowlist experimental release. 94. Google Cloud NetApp Volumes is expanding to 15 new Google Cloud regions in Q2’24 (GA) and includes a number of enhancements: dynamically migrating files by policy to lower-cost storage based on access frequency (in preview Q2’24); increasing Premium and Extreme service levels up to 1PB in size, with throughput performance up to 3X (preview Q2’24). NetApp Volumes also includes a new Flex service level enabling volumes as small as 1GiB. 95. Filestore now supports single-share backup for Filestore Persistent Volumes and GKE (generally available) and NFS v4.1 (preview), plus expanded Filestore Enterprise capacity up to 100TiB. For Cloud Storage: 96. Cloud Storage Anywhere Cache now uses zonal SSD read cache across multiple regions within a continent (allowlist GA). 97. Cloud Storage soft delete protects against accidental or malicious deletion of data by preserving deleted items for a configurable period of time (generally available). 98. The new Cloud Storage managed folders resource type allows granular IAM permissions to be applied to groups of objects (generally available). 99. Tag-based at-scale backup helps manage data protection for Compute Engine VMs (generally available). 100. The new high-performance backup option for SAP HANA leverages persistent disk (PD) snapshot capabilities for database-aware backups (generally available). 101. As part of Backup and DR Service Report Manager, you can now customize reports with data from Google Cloud Backup and DR using Cloud Monitoring, Cloud Logging, and BigQuery (generally available). Databases 102. Database Studio, a part of Gemini in Databases, brings SQL generation and summarization capabilities to our rich SQL editor in the Google Cloud console, as well as an AI-driven chat interface. 103. Database Center lets operators manage an entire fleet of databases through intelligent dashboards that proactively assess availability, data protection, security, and compliance issues, as well as with smart recommendations to optimize performance and troubleshoot issues. 104. Database Migration Service is also integrated with Gemini in Databases, including assistive code conversion (e.g., from Oracle to PostgreSQL) and explainability features. Likewise, AlloyDB gains a lot of new functionality: 105. AlloyDB AI lets gen AI developers build applications that accurately query data with natural language, just like they do with SQL; available now in AlloyDB Omni. 106. AlloyDB AI now includes a new pgvector-compatible index based on Google’s approximate nearest neighbor algorithms, or ScaNN; it’s available as a technology preview in AlloyDB Omni. 107. AlloyDB model endpoint management makes it easier to call remote Vertex AI, third-party, and custom models; available in AlloyDB Omni today and soon on AlloyDB in Google Cloud. 108. AlloyDB AI “parameterized secure views” secures data based on end-users’ context; available now in AlloyDB Omni. Bigtable, which turns 20 this year, got several new features: 109. Bigtable Data Boost, a pre-GA offering, delivers high-performance, workload-isolated, on-demand processing of transactional data, without disrupting operational workloads. 110. Bigtable authorized views, now generally available, allow multiple teams to leverage the same tables and securely share data directly from the database. 111. New Bigtable distributed counters in preview process high-frequency event data like clickstreams directly in the database. 112. Bigtable large nodes, the first of other workload-optimized node shapes, offer more performance stability at higher server utilization rates, and are in private preview. Memorystore for Redis Cluster, meanwhile: 113. Now supports both AOF (Append Only File) and RDB (Redis Database)-based persistence and has new node shapes that offer better performance and cost management. 114. Offers ultra-fast vector search, now generally available. 115. Includes new configuration options to tune max clients, max memory, max memory policies, and more, now in preview. Firestore users, take note: 116. Gemini Code Assist now incorporates assistive capabilities for developing with Firestore. 117. Firestore now has built-in support for vector search using exact nearest neighbors, the ability to automatically generate vector embeddings using popular embedding models via a turn-key extension, and integrations with popular generative AI libraries such as LangChain and LlamaIndex. 118. Firestore Query Explain in preview can help you troubleshoot your queries. 119. Firestore now supports Customer Managed Encryption Keys (CMEK) in preview, which allows you to encrypt data stored at-rest using your own specified encryption key. 120. You can now deploy Firestore in any available supported Google Cloud region, and Firestore’s Scheduled Backup feature can now retain backups for up to 98 days, up from seven days. 121. Cloud SQL Enterprise Plus edition now offers advanced failover capabilities such as orchestrated switchover and switchback Data analytics 122. BigQuery is now Google Cloud’s single integrated platform for data to AI workloads, with BigLake, BigQuery’s unified storage engine, providing a single interface across BigQuery native and open formats for analytics and AI workloads. 123. BigQuery better supports Iceberg, DDL, DML and high-throughput support in preview, while BigLake now supports the Delta file format, also in preview. 124. BigQuery continuous queries are in preview, providing continuous SQL processing over data streams, enabling real-time pipelines with AI operators or reverse ETL. The above-mentioned Gemini in BigQuery enables all manner of new capabilities and offerings: 125. New BigQuery integrations with Gemini models in Vertex AI support multimodal analytics and vector embeddings, and fine-tuning of LLMs. 126. BigQuery Studio provides a collaborative data workspace, the choice of SQL, Python, Spark or natural language directly, and new integrations for real-time streaming and governance; it is now generally available. 127. The new BigQuery data canvas provides a notebook-like experience with embedded visualizations and natural language support courtesy of Gemini. 128. BigQuery can now connect models in Vertex AI with enterprise data, without having to copy or move data out of BigQuery. 129. You can now use BigQuery with Gemini 1.0 Pro Vision to analyze both images and videos by combining them with your own text prompts using familiar SQL statements. 130. Column-level lineage in BigQuery and expanded lineage capabilities for Vertex AI pipelines will be in preview soon. Other updates to our data analytics portfolio include: 131. Apache Kafka for BigQuery as a managed service is in preview, to enable streaming data workloads based on open source APIs. 132. A serverless engine for Apache Spark integrated within BigQuery Studio is now in preview. 133. Dataplex features expanded data-to-AI governance capabilities in preview. Developers & operators Gemini Code Assist includes several new enhancements: 134. Full codebase awareness, in preview, uses Gemini 1.5 Pro to make complex changes, add new features, and streamline updates to your codebase. 135. A new code transformation feature available today in Cloud Workstations and Cloud Shell Editor lets you use natural language prompts to tell Gemini Code Assist to analyze, refactor, and optimize your code. 136. Gemini Code Assist now has extended local context, automatically retrieving relevant local files from your IDE workspace and displaying references to the files used. 137. With code customization in private preview, Gemini Code Assist lets you integrate private codebases and repositories for hyper-personalized code generation and completions, and connects to GitLab, GitHub, and Bitbucket source-code repositories. 138. Gemini Code Assist extends to Apigee and Application Integration in preview, to access and connect your applications. 139. We extended our partnership with Snyk to Gemini Code Assist, letting you learn about vulnerabilities and common security topics right within your IDE. 140. The new App Hub provides an accurate, up-to-date representation of deployed applications and their resource dependencies. Integrated with Gemini Cloud Assist, App Hub is generally available. Users of our Cloud Run and Google Kubernetes Engine (GKE) runtime environments can look forward to a variety of features: 141. Cloud Run application canvas lets developers generate, modify and deploy Cloud Run applications with integrations to Vertex AI, Firestore, Memorystore, and Cloud SQL, as well as load balancing and Gemini Cloud Assist. 142. GKE now supports container and model preloading to accelerate workload cold starts. 143. GPU sharing with NVIDIA Multi-Process Service (MPS) is now offered in GKE, enabling concurrent processing on a single GPU. 144. GKE support GCS FUSE read caching, now generally available, using a local directory as a cache to accelerate repeat reads for small and random I/Os. 145. GKE Autopilot mode now supports NVIDIA H100 GPUs, TPUs, reservations, and Compute Engine committed use discounts (CUDs). 146. Gemini Cloud Assist in GKE is available to help with optimizing costs, troubleshooting, and synthetic monitoring. Cloud Billing tools help you track and understand Google Cloud spending, pay your bill, and optimize your costs; here are a few new features: 147. Support for Cloud Storage costs at the bucket level and storage tags is included out of the box with Cloud Billing detailed data exports to BigQuery. 148. A new BigQuery data view for FOCUS allows users to compare costs and usage across clouds. 149. You can now convert cost management reports into BigQuery billing queries right from the Cloud Billing console. 150. A new Cloud FinOps Anomaly Detection feature is in private preview. 151. FinOps hub is now generally available, adds support to view top savings opportunities, and a preview of our FinOps hub dashboard lets you to analyze costs by project, region, or machine type. 152. A new CUD Analysis solution is available across Google Compute Engine resource families including TPU v5e, TPU v5p, A3, H3, and C3D. 153. There are new spend-based CUDs available for Memorystore, AlloyDB, BigTable, and Dataflow. Security Building on natural language search and case summaries in Chronicle, Gemini in Security Operations is coming to the entire investigation lifecycle, including: 154. A new assisted investigation feature, generally available at the end of this month, that guides analysts through their workflow in Chronicle Enterprise and Chronicle Enterprise Plus. 155. The ability to ask Gemini for the latest threat intelligence from Mandiant directly in-line — including any indicators of compromise found in their environment. 156. Gemini in Threat Intelligence, in public preview, allows you to tap into Mandiant’s frontline threat intelligence using conversational search. 157. VirusTotal now automatically ingests OSINT reports, which Gemini summarizes directly in the platform; generally available now. 158. Gemini in Security Command Center, which now lets security teams search for threats and other security events using natural language in preview, and provides summaries of critical- and high-priority misconfiguration and vulnerability alerts, and summarizes attack paths. 159. Gemini Cloud Assist also helps with security tasks, via: IAM Recommendations, which can provide straightforward, contextual recommendations to remove roles from over-permissioned users or service accounts; Key Insights, which help during encryption key creation based on its understanding of your data, your encryption preferences, and your compliance needs; and Confidential Computing Insights, which recommends options for adding confidential computing protection to sensitive workloads based on your data and your compute usage. Other security news includes: 160. The new Chrome Enterprise Premium, now generally available, combines the popular browser with Google threat and data protection, Zero Trust access controls, enterprise policy controls, and security insights and reporting. 161. Applied threat intelligence in Google Security Operations, now generally available, automatically applies global threat visibility and applies it to each customer’s unique environment. 162. Security Command Center Enterprise is now generally available and includesMandiant Hunt, now in preview. 163. Identity and Access Management Privileged Access Manager (PAM), now available in preview, provides just-in-time, time-bound, and approval-based access elevations. 164. Identity and Access Management Principal Access Boundary (PAB) is a new, identity-centered control now in preview that enforces restrictions on IAM principals. 165. Cloud Next-Gen Firewall (NGFW) Enterprise is now generally available, including threat protection from Palo Alto Networks. 166. Cloud Armor Enterprise is now generally available and offers a pay-as-you-go model that includes advanced network DDoS protection, web application firewall capabilities, network edge policy, adaptive protection, and threat intelligence. 167. Sensitive Data Protection integration with Cloud SQL is now generally available, and is deeply integrated into the Security Command Center Enterprise risk engine. 168. Key management with Autokey is now in preview, simplifying the creation and management of customer encryption keys (CMEK). 169. Bare metal HSM deployments in PCI-compliant facilities are now available in more regions. 170. Regional Controls for Assured Workloads is now in preview and is available in 32 cloud regions in 14 countries. 171. Audit Manager automates control verification with proof of compliance for workloads and data on Google Cloud, and is in preview. 172. Advanced API Security, part of Apigee API Management, now offers shadow API detection in preview. As part of our Confidential Computing portfolio, we announced: 173. Confidential VMs on Intel TDX are now in preview and available on the C3 machine series with Intel TDX. For AI and ML workloads, we support Intel AMX, which provides CPU-based acceleration by default on C3 series Confidential VMs. 174. Confidential VMs on general-purpose N2D machine series with AMD Secure Encrypted Virtualization-Secure Nested Paging (SEV-SNP) are now in preview. 175. Live Migration on Confidential VMs is now in general availability on N2D machine series across all regions. 176. Confidential VMs on the A3 machine series with NVIDIA Tensor Core H100 GPUs will be in private preview later this year. Migration 177. The Rapid Migration Program (RaMP) now covers migration and modernization use cases that span across applications and the underlying infrastructure, data and analytics. For example, as part of RaMP for Storage: Storage egress costs from Amazon S3 to Google Cloud Storage are now completely free. Cloud Storage's client libraries for Python, Node.js, and Java now support parallelization of uploads and downloads from client libraries. Migration Center also includes several excellent new additions: 178. Migration use case navigator, for mapping out how to migrate your resources (servers, databases, data warehouses, etc.) from on-prem and other clouds directly into Google Cloud, including new Cloud Spend Estimators for rapid TCO assessments of on-premises VMware and Exadata environments. 179. Database discovery and assessment for Microsoft SQL Server, PostgreSQL and MySQL to Cloud SQL migrations. Google Cloud VMware Engine, an integrated VMware service on Google Cloud now offers: 180. The intent to support VMware Cloud Foundation License Portability 181. General availability of larger instance type (ve2-standard-128) offerings. 182. Networking enhancements including next-gen VMware Engine Networking, automated zero-config VPC peering, and Cloud DNS for workloads. 183. Terraform Infrastructure as Code Automation. Migrate to Virtual Machines helps teams migrate their workloads. Here’s what we announced: 184. A new Disk Migration solution for migrating disk volumes to Google Cloud. 185. Image Import (preview) as a managed service. 186. BIOS to UEFI Conversion in preview, which automatically converts bootloaders to the newer UEFI format. 187. Amazon Linux Conversion in preview, for converting Amazon Linux to Rocky Linux in Google Compute Engine. 188. CMEK support, so you maintain control over your own encryption keys. When replatforming VMs to containers in GKE or Cloud Run, there’s: 189. The new Migrate to Containers (M2C) CLI, which generates artifacts that you can deploy to either GKE or Cloud Run. 190. M2C Cloud Code Extension, in preview, which migrates applications from VMs to containers running on GKE directly in Visual Studio. Here are the enhancements to our Database Migration Service: 191. Database Migration Service now offers AI-powered last-mile code conversion from Oracle to PostgreSQL. 192. Database Migration Service now performs migration from SQL Server (on any platform) to Cloud SQL for SQL Server, in preview. 193. In Datastream, SQL Server as a source for CDC performs data movement to BigQuery destinations. Migrating from a mainframe? Here are some new capabilities: 194. The Mainframe Assessment Tool (MAT) now powered by gen AI analyzes the application codebase, performing fit assessment and creating application-level summarization and test cases. 195. Mainframe Connector sends a copy of your mainframe data to BigQuery for off-mainframe analytics. 196. G4 refactors mainframe application code (COBOL, RPG, JCL etc.) and data from their original state/programming language to a modern stack (JAVA). 197. Dual Run lets you run a new system side by side with your existing mainframe, duplicating all transactions and checking for completeness, quality and effectiveness of the new solution. Partners & ecosystem 198. Partners showcased more than 100 solutions that leverage Google AI on the Next ‘24 show floor. 199. We announced the 2024 Google Cloud Partner of the Year winners. 200. Gemini models will be available in the SAP Generative AI Hub. 201. GitLab announced that its authentication, security, and CI/CD integrations with Google Cloud are now in public beta for customers. 202. Palo Alto Networks named Google Cloud its AI provider of choice and will use Gemini models to improve threat analysis and incident summarization for its Cortex XSIAM platform. 203. Exabeam is using Google Cloud AI to improve security outcomes for customers. 204. Global managed security services company Optiv is expanding support for Google Cloud products. 205. Alteryx, Dynatrace, and Harness are launching new features built with Google Cloud AI to automate workflows, support data governance, and enable users to better observe and manage the data. 206. A new Generative AI Services Specialization is available for partners who demonstrate the highest level of technical proficiency with Google Cloud gen AI. 207. We introduced new Generative AI Delivery Excellence and Technical Bootcamps, and advanced Challenge Labs in generative AI. 208. The Google Cloud Ready - BigQuery initiative has 21 new partners: Actable, AgileData, Amplitude, Boostkpi, CaliberMind, Calibrate Analytics, CloudQuery, DBeaver, Decube, DinMo, Estuary, Followrabbit, Gretel, Portable, Precog, Retool, SheetGo, Tecton, Unravel Data, Vallidio, and Vaultree 209. The Google Cloud Ready - AlloyDB initiative has six new partners: Boostkpi, DBeaver, Estuary, Redis, Thoughtspot, and SeeBurger 210. The Google Cloud Ready - Cloud SQL initiative has five new partners: BoostKPI, DBeaver, Estuary, Redis, and Thoughtspot 211. Crowdstrike is integrating its Falcon Platform with Google Cloud products. Members of our Google for Startups program, meanwhile, will be interested to learn that: 212. The Google for Startups Cloud Program has a new partnership with the NVIDIA Inception startup program. The benefits include providing Inception members with access to Google Cloud credits, go-to-market support, technical expertise, and fast-tracked onboarding to Google Cloud Marketplace. 213. As part of the NVIDIA Inception partnership, Google for Startups Cloud Program members can join NVIDIA Inception and gain access to technological expertise, NVIDIA Deep Learning Institute course credits, NVIDIA hardware and software, and more. Eligible members of the Google for Startups Cloud Program also can participate in NVIDIA Inception Capital Connect, a platform that gives startups exposure to venture capital firms interested in the space. 214. The new Google for Startups Accelerator: AI-First program for startups building AI solutions based in the U.S. and Canada has launched, and its cohort includes 15 AI startups: Aptori, Augmend, Backpack Healthcare, BrainLogic AI, Cicerai, CLIKA, Easel AI, Findly, Glass Health, Kodif, Liminal, mbue, Modulo Bio, Rocket Doctor, and Sibli. 215. The Startup Learning Center provides startups with curated content to help them grow with Google Cloud, and will be launching an offering for startup developers and future founders via Innovators Plus in the coming months Finally, Google Cloud Consulting, has the following services to help you build out your Google Cloud environment: 216. Google Cloud Consulting is offering no-cost, on-demand training to top customers through Google Cloud Skills Boost, including new gen AI skill badges: Prompt Design in Vertex AI, Develop Gen AI Apps with Gemini and Streamlit, and Inspect Rich Documents with Gemini Multimodality and Multimodal RAG. 217. The new Isolator solution protects healthcare data used in collaborations between parties using a variety of Google Cloud technologies including Chrome Enterprise Premium, VPC Service Controls, Chrome Enterprise, and encryption. 218. Google Cloud Consulting’s Delivery Navigator is now generally available to all Google Cloud qualified services partners. Phew. What a week! On behalf of Google Cloud, we’re so grateful you joined us at Next ‘24, and can’t wait to host you again next year back in Las Vegas at the Mandalay Bay on April 9 - 11 in 2025! View the full article

In Kubernetes, persistent volumes were initially managed by in-tree plugins, but this approach hindered development and feature implementation since in-tree plugins were compiled and shipped as part of k8s source code. To address this, the Container Storage Interface (CSI) was introduced, standardizing storage system exposure to containerized workloads. CSI drivers for standard volumes like Google Cloud PersistentDisk were developed and are continuously evolving. The implementation for in-tree plugins is being transitioned to CSI drivers. If you have a Google Kubernetes Engine (GKE) cluster(s) that is still using the in-tree volumes, please follow the instructions below to learn how to migrate to CSI provisioned volumes. Why migrate? There are various benefits to using a gce-pd CSI Driver, including improved deployment automation, customer managed keys, volume snapshots and more. In GKE version 1.22 and later, CSI Migration is enabled. Existing volumes that use the gce-pd provider managed through CSI drivers via transparent migration in the kubernetes controller backend. No changes are required to any StorageClass. You must use the pd.csi.storage.gke.io provider in the StorageClass to enable features like CMEK or volume snapshots. An example of a storage Class with an in-tree storage plugin and a CSI driver. code_block <ListValue: [StructValue([('code', 'apiVersion: storage.k8s.io/v1\r\nkind: StorageClass\r\n...\r\nprovisioner: kubernetes.io/gce-pd <--- in-tree\r\nprovisioner: pd.csi.storage.gke.io <--- CSI provisioner'), ('language', ''), ('caption', <wagtail.rich_text.RichText object at 0x3ebc86d6f1c0>)])]> [Please perform the below actions in your test/dev environment first] Before you begin: To test migration, create a GKE cluster. Once the cluster is ready, check the provisioner of your default storage class. If it’s already a CSI provisioner pd.csi.storage.gke.io then change it to gce-pd (in-tree) by following these instructions Refer to this page if you want to deploy a stateful PostgreSQL database application in a GKE cluster.. We will refer to this sample application throughout this blog. Again, make sure that a storage class (standard) with gce-pd provisioner creates the volumes (PVCs) attached to the pods. As a next step, we will backup this application using Backup for GKE (BfG) and restore the application while changing the provisioner from gce-pd (in-tree) to pd.csi.storage.io (the CSI driver). Create a backup Plan Please follow this page to ensure you have BfG enabled on your cluster. When you enable the BfG agent in your GKE cluster, BfG provides a CustomResourceDefinition that introduces a new kind of Kubernetes resource: the ProtectedApplication. For more on ProtectedApplication, please visit this page. A sample manifest file: code_block <ListValue: [StructValue([('code', 'kind: ProtectedApplication\r\napiVersion: gkebackup.gke.io/v1alpha2\r\nmetadata:\r\n name: postgresql\r\n namespace: blog\r\nspec:\r\n resourceSelection:\r\n type: Selector\r\n selector:\r\n matchLabels:\r\n app.kubernetes.io/name: postgresql-ha\r\n components:\r\n - name: postgresql\r\n resourceKind: StatefulSet\r\n resourceNames: ["db-postgresql-ha-postgresql"]\r\n strategy:\r\n type: BackupAllRestoreAll\r\n backupAllRestoreAll: {}'), ('language', ''), ('caption', <wagtail.rich_text.RichText object at 0x3ebc86d6f2e0>)])]> If Ready to backup status shows as true, your application is ready for backup. code_block <ListValue: [StructValue([('code', '❯ kubectl describe protectedapplication postgresql\r\n......\r\nStatus:\r\n Ready To Backup: true'), ('language', ''), ('caption', <wagtail.rich_text.RichText object at 0x3ebc86d6f400>)])]> Let’s create a backup plan following these instructions. Up until now, we have only created a backup plan and haven’t taken an actual backup. But before we start the backup process, we have to bring down the application. Bring down the Application We have to bring down the application right before taking its backup (This is where the Application downtime starts). We are doing it to prevent any data loss during this migration. My application is currently exposed via a service db-postgresql-ha-pgpool with the following selectors: We’ll patch this service by overriding above selectors with a null value so that no new request can reach the database. Save this file as patch.yaml and apply it using kubectl. code_block <ListValue: [StructValue([('code', 'spec:\r\n selector:\r\n app.kubernetes.io/instance: ""\r\n app.kubernetes.io/name: ""\r\n app.kubernetes.io/component: ""'), ('language', ''), ('caption', <wagtail.rich_text.RichText object at 0x3ebc86d6ff10>)])]> code_block <ListValue: [StructValue([('code', '❯ kubectl patch service db-postgresql-ha-pgpool --patch-file patch.yaml\r\nservice/db-postgresql-ha-pgpool patched'), ('language', ''), ('caption', <wagtail.rich_text.RichText object at 0x3ebc865c8370>)])]> You should no longer be able to connect to your app (i.e., database) now. Start a Backup Manually Navigate to the GKE Console → Backup for GKE → Backup Plans Click Start a backup as shown below. Restore from the Backup We will restore this backup to a Target Cluster. Please note that you do have an option to select the same cluster as your source and your target cluster. The recommendation is to use a new GKE cluster as your target cluster. Restore process completes in following two steps: Create a restore plan Restore a backup using the restore plan Create a restore plan You can follow these instructions to create a restore plan. While adding the transformation rule(s) , we will change the storage class from standard to standard-rwo. Add transformation rules → Add Rule (Rename a PVC’s Storage Class) Please see this page for more details. Next, review the configuration and create a plan. Restore backup using the (previously created) restore plan When a backup is restored, the Kubernetes resources are re-created in the target cluster. Navigate to the GKE Console → Backup for GKE → BACKUPS tab to see the latest backup(s). Select the backup you took before bringing down the application to view the details and click on SET UP A RESTORE. Fill all the mandatory fields and click RESTORE. Once done, switch the context to the target cluster and see how BfG has restored the application successfully in the same namespace. The data was restored into new PVCs (verify with kubectl -n blog get pvc). Their storageclass is gce-pd-gkebackup-de, which is a special storageclass used to provision volumes from the backup. Let’s get the details of one of the restored volumes to confirm BfG has successfully changed the provisioner from in-tree to CSI New volumes are created by the CSI provisioner. Great! Bring up the application Let’s patch the service db-postgresql-ha-pgpool back with the original selectors to bring our application up. Save this patch file as new_patch.yaml and apply using kubectl. We are able to connect to our database application now. Note: This downtime will depend on your application size. For more information, please see this link. Use it todayBackup for GKE can help you reduce the overhead of this migration with a minimal downtime. It can also help you prepare for disaster recovery. View the full article

You can now use AWS PrivateLink to privately access the AWS Migration Hub Refactor Spaces APIs from your virtual private cloud (Amazon VPC). AWS PrivateLink provides private connectivity between VPCs, AWS services, and your on-premises networks. Starting today, you can manage your Refactor Spaces resources using AWS PrivateLink and meet your organization’s security and compliance requirements. To use AWS PrivateLink, create an interface VPC endpoint for Refactor Spaces in your VPC using the Amazon VPC console, SDK, or CLI. You can also access the VPC endpoint from on-premises environments or from other VPCs using AWS VPN, AWS Direct Connect, or VPC Peering. View the full article

Today, AWS announced the ability to toggle routes on and off when using AWS Migration Hub Refactor Spaces. This feature lets customers create inactive routes which can be activated after creation once the route’s targeted service is ready to receive traffic. Customers can use route toggling to fine-tune their routing approach and deliver just-in-time route changes as applications are incrementally refactored. View the full article

AWS Database Migration Service (AWS DMS) now supports IBM Db2 z/OS as a source for the full load operational mode. Using AWS Schema Conversion Tool (SCT), you can convert schemas and code objects from IBM DB2 z/OS to Aurora MySQL, Aurora PostgreSQL, MySQL and PostgreSQL targets. Once you have the schema and objects in a format compatible with target database you can utilize AWS DMS to migrate data from IBM DB2 running on the z/OS operating system to any AWS DMS supported targets. View the full article

AWS Database Migration Service (AWS DMS) has expanded functionality by adding support for Babelfish for Aurora PostgreSQL as a target. Babelfish for Aurora PostgreSQL is a new translation layer for Amazon Aurora PostgreSQL-Compatible Edition that enables Aurora to understand commands from applications written for Microsoft SQL Server. Using AWS DMS, you can now perform full load migrations to Babelfish for Aurora PostgreSQL with minimal downtime. View the full article

AWS Database Migration Service (AWS DMS) now supports virtual private cloud (VPC) endpoints as sources and targets. AWS DMS can now connect to any AWS service with VPC endpoints so long as explicitly defined routes to the services are defined in their AWS DMS VPC. View the full article

You can now use AWS Application Migration Service (AWS MGN) for use cases that are subject to System and Organization Controls (SOC) reporting. You can also now install the AWS Application Migration Service agent on your source servers using AWS Identity and Access Management (IAM) temporary security credentials with limited permissions. AWS Application Migration Service allows you to quickly migrate and modernize applications on AWS. View the full article

Amazon Relational Database Service (Amazon RDS) for SQL Server now supports TDE enabled database migrations using Native Backup/Restore for Microsoft SQL Server. Previously, you would need to disable TDE on your on-premises TDE enabled SQL Server database in order to migrate to Amazon RDS. View the full article

AWS Application Migration Service is announcing support for new automated application modernizations. AWS Application Migration Service allows you to quickly rehost applications on AWS. It automatically converts your source servers from physical, virtual, or cloud infrastructure to run natively on AWS. View the full article

Largescale cloud migration is no mean feat, especially for organisations operating in heavily regulated sectors.…The post Bring ease and speed to application-centric cloud migration appeared first on DevOpsGroup. View the full article

Just ask George R.R. Martin: the hardest thing when starting to write a book is the inertia of the beginning – what are the first words of the first page? The same roadblock applies when you decide to migrate your IT infrastructure to Kubernetes: the most challenging part is getting started. View the full article

AWS Database Migration Service (AWS DMS) helps you migrate databases to AWS quickly and securely. With this launch, AWS DMS now supports Amazon S3 folder partitions based on transaction commit dates when using Amazon S3 as a target. Using date-based folder partitioning, you can write data from a single source table to a time-hierarchy folder structure in Amazon S3. By partitioning the S3 folder, you can better manage your S3 objects, limit the size of each S3 folder, and optimize data lake queries or other subsequent operations. View the full article

AWS Database Migration Service (AWS DMS) has expanded functionality by adding support for Amazon Aurora Serverless (PostgreSQL-compatible edition) as a target. Amazon Aurora Serverless (PostgreSQL-compatible edition) is an on-demand, auto-scaling configuration where the database will automatically start up, shut down, and scale capacity up or down based on your application's needs. Using AWS DMS, you can now perform live migrations from any AWS DMS supported sources to Amazon Aurora Serverless (PostgreSQL-compatible edition) with minimal downtime. View the full article

Starting today, you can launch R5, C5, and T3 instance types when using AWS Database Migration Service (DMS) to migrate your databases. You can easily scale up to these new instance classes by modifying your existing replication instance through the AWS DMS, AWS CLI, or AWS SDK. View the full article

Starting today, you can easily move your database migration tasks from one replication instance to another. To move, select the migration task and provide the target replication instance details. You can access this feature using AWS DMS Console, AWS CLI, or AWS SDK. Once the migration task is moved to the target replication instance, you can resume your migration from where you left off. View the full article

Customers using the AWS Migration Hub to discover, plan, and track their migrations now have access to Migration Hub network visualization. Migration Hub network visualization is for migration experts and non-experts who want to quickly organize and validate their on-premises discovery data, and to build their migration plan. View the full article

At a recent online virtual event with Kong, Paul Curtis (@pfcurtis_NY), Weaveworks’ Principle Solutions Architect demonstrated how you can use Weave Kubernetes Platform and GitOps to make your transition from running legacy applications on Virtual Machines onto Kubernetes much simpler... View the full article

Organizations need to take a considered and gradual approach to cloud migration to ensure security and compliance For businesses to succeed in 2021 and beyond, agility and responsiveness are critical. Data is the new currency, and businesses need to be able to access theirs instantly and securely to make the rapid-fire business decisions that will […] The post 20/20 Network Visibility: Making Cloud Migration a Success appeared first on DevOps.com. View the full article

Starting today, you can privately connect your Amazon Virtual Private Cloud (VPC) to AWS Database Migration Service (DMS) without requiring an internet gateway, NAT device, VPN connection, or AWS Direct Connect connection. View the full article

AWS Database Migration Service (AWS DMS) has expanded functionality by adding support for Amazon DocumentDB 4.0 as a target. Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. As a document database, Amazon DocumentDB makes it easy to store, query, and index JSON data. Using DMS, you can now perform live migrations to Amazon DocumentDB 4.0 from MongoDB replica sets, sharded clusters, or any AWS DMS supported source including Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle, SAP ASE and Microsoft SQL Server databases with minimal downtime. View the full article

AWS Database Migration Service (AWS DMS) has expanded functionality by adding support for Amazon DocumentDB (with MongoDB compatibility) as a source. Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. As a document database, Amazon DocumentDB makes it easy to store, query, and index JSON data. View the full article

AWS Database Migration Service (AWS DMS) helps you migrate databases to AWS quickly and securely. With this launch, AWS DMS now supports parallel full load with the range segmentation option when using Amazon DocumentDB (with MongoDB compatibility) and MongoDB as a source. You can accelerate the migration of large collections by splitting them into segments and loading and unloading the segments in-parallel in the same migration task. This feature could improve the migration performance by up to 3x. View the full article

AWS Server Migration Service (AWS SMS) adds support for application monitoring using Amazon CloudWatch Application Insights. With the integration of AWS SMS with Amazon CloudWatch Application Insights, you can start monitoring applications in Amazon CloudWatch as soon as the application migration is complete in AWS SMS. View the full article