AWS

Today, AWS announces the general availability of Amazon Elastic Compute Cloud (Amazon EC2) P5en instances, powered by the latest NVIDIA H200 Tensor Core GPUs. These instances deliver the highest performance in Amazon EC2 for deep learning and high performance computing (HPC) applications.

You can use Amazon EC2 P5en instances for training and deploying increasingly complex large language models (LLMs) and diffusion models powering the most demanding generative AI applications. You can also use P5en instances to deploy demanding HPC applications at scale in pharmaceutical discovery, seismic analysis, weather forecasting, and financial modeling.

P5en instances feature up to 8 H200 GPUs which have 1.7x GPU memory size and 1.5x GPU memory bandwidth than H100 GPUs featured in P5 instances. P5en instances pair the H200 GPUs with high performance custom 4^th Generation Intel Xeon Scalable processors, enabling Gen5 PCIe between CPU and GPU which provides up to 4x the bandwidth between CPU and GPU and boosts AI training and inference performance. P5en, with up to 3200 Gbps of third generation of EFA using Nitro v5, shows up to 35% improvement in latency compared to P5 that uses the previous generation of EFA and Nitro. This helps improve collective communications performance for distributed training workloads such as deep learning, generative AI, real-time data processing, and high-performance computing (HPC) applications. To address customer needs for large scale at low latency, P5en instances are deployed in Amazon EC2 UltraClusters, and provide market-leading scale-out capabilities for distributed training and tightly coupled HPC workloads.

P5en instances are now available in the US East (Ohio), US West (Oregon), and Asia Pacific (Tokyo) AWS Regions and US East (Atlanta) Local Zone us-east-1-atl-2a in the p5en.48xlarge size.

To learn more about P5en instances, see Amazon EC2 P5en Instances.

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With the launch of VPC Resources for Amazon VPC Lattice, you can now access all of your application dependencies through a VPC Lattice service network. You’re able to connect to your application dependencies hosted in different VPCs, accounts, and on-premises using additional protocols, including TLS, HTTP, HTTPS, and now TCP. This new feature expands upon the existing HTTP-based services support, enabling you to share a wider range of resources across your organization.

With VPC Resource support, you can add your TCP resources, such as Amazon RDS databases, custom DNS, or IP endpoints, to a VPC Lattice service network. Now, you can share and connect to all your application dependencies, such as HTTP APIs and TCP databases, across thousands of VPCs, simplifying network management and providing centralized visibility with built-in access controls.

VPC Resources are generally available with VPC Lattice in Africa (Cape Town), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Europe (Frankfurt), Europe (Ireland), Europe (Paris), Europe (Stockholm), Middle East (Bahrain), South America (Sao Paulo), US East (N. Virginia), US East (Ohio), US West (Oregon).

To get started, read the VPC Resources launch blog, architecture blog, and VPC Lattice User Guide. Learn more about VPC Lattice, visit Amazon VPC Lattice Getting Started.
 

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Latency-optimized inference for foundation models in Amazon Bedrock now available in public preview, delivering faster response times and improved responsiveness for AI applications. Currently, these new inference options support Anthropic’s Claude 3.5 Haiku model and Meta’s Llama 3.1 405B and 70B models offering reduced latency compared to standard models without compromising accuracy. As verified by Anthropic, with latency-optimized inference in Amazon Bedrock, Claude 3.5 Haiku runs faster on AWS than anywhere else. Additionally, with latency-optimized inference in Bedrock, Llama 3.1  405B and 70B runs faster on AWS than any other major cloud provider.

As more customers move their generative AI applications to production, optimizing the end-user experience becomes crucial, particularly for latency-sensitive applications such as real-time customer service chatbots and interactive coding assistants. Using purpose-built AI chips like AWS Trainium2 and advanced software optimizations in Amazon Bedrock, customers can access more options to optimize their inference for a particular use case. Accessing these capabilities requires no additional setup or model fine-tuning, allowing for immediate enhancement of existing applications with faster response times.

Latency-optimized inference is available for Anthropic’s Claude 3.5 Haiku and Meta’s Llama 3.1 405B and 70B in the US East (Ohio) Region via cross-region inference. To get started, visit the Amazon Bedrock console. For more information about Amazon Bedrock and its capabilities, visit the Amazon Bedrock product page, pricing page, and documentation.

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GROW with SAP on AWS is now available for subscription from AWS Marketplace. As a complete offering of solutions, best practices, adoption acceleration services, community and learning, GROW with SAP helps any size organization adopt cloud enterprise resource planning (ERP) with speed, predictability, and continuous innovation. GROW with SAP on AWS can be implemented in months instead of years with traditional on-premises ERP implementations.

By implementing GROW with SAP on AWS, you can simplify everyday work, grow your business, and secure your success. At the core of GROW with SAP is SAP S/4HANA Cloud, a full-featured SaaS ERP suite built on the learnings of SAP’s 50+ years of industry best practices. GROW with SAP allows your organization to gain end- to- end process visibility and control with integrated systems across HR, procurement, sales, finance, supply chain, and manufacturing. It also includes SAP Business AI-powered processes leveraging AWS to provide data-driven insights and recommendations. Customers can also innovate with generative AI using their SAP data through Amazon Bedrock models in the SAP generative AI hub. GROW with SAP on AWS takes advantage of AWS Graviton processors, which offer up to 60% less energy than comparable cloud instances for the same performance.

GROW with SAP on AWS is initially available in the US-East Region.

To subscribe to GROW with SAP on AWS, visit the AWS Marketplace listing. Or, to learn more, visit the GROW with SAP on AWS detail page.

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AWS is announcing the general availability of Amazon Elastic Compute Cloud (Amazon EC2) storage optimized I8g instances. I8g instances offer the best performance in Amazon EC2 for storage-intensive workloads. I8g instances are powered by AWS Graviton4 processors that deliver up to 60% better compute performance compared to previous generation I4g instances. I8g instances use the latest third generation AWS Nitro SSDs, local NVMe storage that deliver up to 65% better real-time storage performance per TB while offering up to 50% lower storage I/O latency and up to 60% lower storage I/O latency variability. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software enhancing the performance and security for your workloads.

I8g instances offer instance sizes up to 24xlarge, 768 GiB of memory, and 22.5 TB instance storage. They are ideal for real-time applications like relational databases, non-relational databases, streaming databases, search queries and data analytic.

I8g instances are available in the following AWS Regions: US East (N. Virginia) and US West (Oregon).

To learn more, see Amazon EC2 I8g instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs.

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Today, AWS announces the general availability of declarative policies, a new management policy type within AWS Organizations. These policies simplify the way customers enforce durable intent, such as baseline configuration for AWS services within their organization. For example, customers can configure EC2 to allow instance launches using AMIs vended by specific providers and block public access in their VPC with a few simple clicks or commands for their entire organization using declarative policies.

Declarative policies are designed to prevent actions that are non-compliant with the policy. The configuration defined in the declarative policy is maintained even when services add new APIs or features, or when customers add new principals or accounts to their organization. With declarative policies, governance teams have access to the account status report which provides insight into the current configuration for an AWS service across their organization. This helps them asses readiness to enforce configuration at scale. Administrators can provide additional transparency to end users by configuring custom error messages to redirect them to internal wikis or ticketing systems through declarative policies.

To get started, navigate to the AWS Organizations console to create and attach declarative policies. You can also use AWS Control Tower, AWS CLI or CloudFormation templates to configure these policies. Declarative policies today support EC2, EBS and VPC configurations with support for other services coming soon. To learn more see documentation and blog post.

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Amazon OpenSearch Service now offers a zero-ETL integration with Amazon Security Lake, enabling you to query and analyze security data in-place directly through OpenSearch. This integration allows you to efficiently explore voluminous data sources that were previously cost-prohibitive to analyze, helping you streamline security investigations and obtain comprehensive visibility of your security landscape. By offering the flexibility to selectively ingest data and eliminating the need to manage complex data pipelines, you can now focus on effective security operations while potentially lowering your analytics costs.

Using the powerful analytics and visualization capabilities in OpenSearch Service, you can perform deeper investigations, enhance threat hunting, and proactively monitor your security posture. Pre-built queries and dashboards using the Open Cybersecurity Schema Framework (OCSF) can further accelerate your analysis. The built-in query accelerator boosts performance and enables fast-loading dashboards, enhancing your overall experience. This integration empowers you to accelerate investigations, uncover insights from previously inaccessible data sources, optimize analytics efficiency and costs, with minimal data migration.

OpenSearch Service zero-ETL integration with Security Lake is now generally available in 13 regions globally: Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe (London), US East (Ohio), US East (N. Virginia), US West (Oregon), South America (São Paulo), Europe (Paris), and Canada (Central).

To learn more on using this capability, see the OpenSearch Service Integrations page and the OpenSearch Service Developer Guide. To learn more about how to configure and share Security Lake, see the Get Started Guide.
 

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Amazon Web Services announces a new integrated analytics experience and zero-ETL integration between Amazon CloudWatch and Amazon OpenSearch Service for customers to get the best of both services. CloudWatch customers can now leverage OpenSearch’s Piped Processing Language (PPL) and OpenSearch SQL. Additionally, CloudWatch customers can accelerate troubleshooting with out-of-the-box curated dashboards for vended logs like Amazon Virtual Private Cloud (VPC), AWS CloudTrail, and AWS Web Application Firewall (WAF). OpenSearch customers can now analyze CloudWatch Logs without having to duplicate data.

With this integration, CloudWatch Logs customers have two more query languages for log analytics, in addition to CloudWatch Logs Insights QL. Customers can use SQL to analyze data, correlate logs using JOINS, sub-queries, and use SQL functions, namely, JSON, mathematical, datetime, and string functions for intuitive log analytics. They can also use the OpenSearch PPL to filter, aggregate and analyze their data. With a few clicks, CloudWatch Logs customers can create OpenSearch dashboards for VPC, WAF, and CloudTrail logs to monitor, analyze, and troubleshoot using visualizations derived from the logs. OpenSearch customers no longer have to copy logs from CloudWatch for analysis, or create ETL pipelines. Now, they can use OpenSearch Discover to analyze CloudWatch logs in-place, build indexes and dashboards on CloudWatch Logs.

This is now available in the regions where OpenSearch Service direct query is available. Please read pricing and free tier details on Amazon CloudWatch Pricing, and OpenSearch Service Pricing. To get started, please refer to Amazon CloudWatch Logs vended dashboard and Amazon OpenSearch Service Developer Guide.
 

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Amazon Web Services is announcing general availability for next generation high density Storage Optimized I7ie instances. Designed for large storage I/O intensive workloads, I7ie instances are powered by 5th generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.2 GHz, offering up to 40% better compute performance and 20% better price performance over existing I3en instances. I7ie instances have the highest local NVMe storage density in the cloud for storage optimized instances and offer up to twice as many vCPUs and memory compared to prior generation instances. Powered by 3rd generation AWS Nitro SSDs, I7ie instances deliver up to 65% better real-time storage performance, up 50% lower storage I/O latency, and 65% lower storage I/O latency variability compared to I3en instances.

I7ie are high density storage optimized instances, ideal for workloads requiring fast local storage with high random read/write performance at very low latency consistency to access large data sets. I7ie instances also deliver 40% better compute performance to run more complex queries without increasing the storage density per vCPU. Additionally, the 16KB torn write prevention feature, enables customers to eliminate performance bottlenecks.

I7ie instances deliver up to 100Gbps of network bandwidth and 60Gbps of bandwidth for Amazon Elastic Block Store (EBS).

I7ie instances are available in the following AWS Regions: US East (N. Virginia, Ohio), US West (Oregon), Europe (Frankfurt, London), and Asia Pacific (Tokyo). Customers can use these instances with On Demand and Savings Plan purchase options. To learn more, visit the I7ie instances page.

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Today, AWS announces the general availability of Amazon MemoryDB Multi-Region, a fully managed, active-active, multi-Region database that lets you build multi-Region applications with up to 99.999% availability and microsecond read and single-digit millisecond write latencies. MemoryDB is a fully managed, Valkey- and Redis OSS-compatible database service providing multi-AZ durability, microsecond read and single-digit millisecond write latency, and high throughput. Valkey is an open source, high performance, key-value data store—stewarded by Linux Foundation—and is a drop-in replacement of Redis OSS.  

With MemoryDB Multi-Region, you can build highly available multi-Region applications for increased resiliency. It offers active-active replication so you can serve reads and writes locally from the Regions closest to your customers with microsecond read and single-digit millisecond write latency. MemoryDB Multi-Region asynchronously replicates data between Regions and typically propagates data within a second. It automatically resolves update conflicts and corrects data divergence issues, so you can focus on building your application.       

Get started with MemoryDB Multi-Region from the AWS Management Console or using the latest AWS SDK or AWS Command Line Interface (AWS CLI). First, you need to identify the set of AWS Regions where you want to replicate your data. Then choose an AWS Region to create a new multi-Region cluster and a regional cluster. Once the first regional cluster is created, you can add up to four additional Regions to the multi-Region cluster.  

MemoryDB Multi-Region is available for Valkey in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), and Europe (London). To learn more, please visit the MemoryDB features page, getting started blog, and documentation. For pricing, please refer to the MemoryDB pricing page.

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Amazon S3 is announcing the general availability of Storage Browser for S3, an open source component that you can add to your web applications to provide your end users with a simple interface for data stored in S3. With Storage Browser for S3, you can provide authorized end users, such as customers, partners, and employees, with access to easily browse, download, and upload data in S3 directly from your own applications. Storage Browser for S3 is available in the AWS Amplify React and JavaScript client libraries.

With the general availability of Storage Browser for S3, your end users can now search for their data based on file name and can copy and delete data they have access to. Additionally, Storage Browser for S3 now automatically calculates checksums of the data your end users upload and blocks requests that do not pass these durability checks.

We welcome your contributions and feedback on our roadmap, which outlines the plan for adding new capabilities to Storage Browser for S3. Storage Browser for S3 is backed by AWS Support, which means customers with AWS Business and Enterprise Support plans get 24/7 access to cloud support engineers. To learn more and get started, visit the AWS News Blog and the UI documentation.
 

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Amazon S3 updates the default behavior of object upload requests with new data integrity protections that build upon S3’s existing durability posture. The latest AWS SDKs now automatically calculate CRC-based checksums for uploads as data is transmitted over the network. S3 independently verifies these checksums and accepts objects after confirming that data integrity was maintained in transit over the public internet. Additionally, S3 now stores a CRC-based whole-object checksum in object metadata, even for multipart uploads, which helps you to verify the integrity of an object stored in S3 at any time.

S3 has always validated the integrity of object uploads from the S3 API to storage by calculating MD5 checksums and allowed customers to provide their own pre-calculated MD5 checksums for integrity validation. S3 also supports five additional checksum algorithms, CRC64NVME, CRC32, CRC32C, SHA-1, and SHA-256, for integrity validations on upload and download. Using checksums for data validation is a best practice for data durability, and this new default behavior adds additional data integrity protections with no changes to your applications and at no additional cost.

Default checksum protections are rolling out across all AWS Regions in the next few weeks. To get started, you can use the AWS Management Console or the latest AWS SDKs to upload objects. To learn more about checksums in S3, visit the AWS News Blog and the S3 User Guide.

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Amazon EC2 introduces Allowed AMIs, a new account-wide setting that enables you to limit the discovery and use of Amazon Machine Images (AMIs) within your AWS accounts. You can now simply specify the AMI owner accounts or AMI owner aliases permitted within your account, and only AMIs from these owners will be visible and available to you to launch EC2 instances.

Prior to today, you could use any AMI explicitly shared with your account or any public AMI, regardless of its origin or trustworthiness, putting you at risk of accidentally using an AMI that didn’t meet your organization’s compliance requirements. Now with Allowed AMIs, your administrators can specify the accounts or owner aliases whose AMIs are permitted for discovery and use within your AWS environment. This streamlined approach provides guardrails to reduce the risk of inadvertently using non-compliant or unauthorized AMIs. Allowed AMIs also supports an audit-mode functionality to identify EC2 instances launched using AMIs not permitted by this setting, helping you identify non-compliant instances before the setting is applied. You can apply this setting across AWS Organizations and Organizational Units using Declarative Policies, allowing you to manage and enforce this setting at scale.

Allowed AMI setting only applies to public AMIs and AMIs explicitly shared with your AWS accounts. By default, this setting is disabled for all AWS accounts. You can enable it by using the AWS CLI, SDKs, or Console. To learn more, please visit our documentation.

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Today at re:Invent, AWS announced Amazon Elastic Kubernetes Service (Amazon EKS) Auto Mode, a new feature that fully automates compute, storage, and networking management for Kubernetes clusters. Amazon EKS Auto Mode simplifies running Kubernetes by offloading cluster operations to AWS, improves the performance and security of your applications, and helps optimize compute costs. 

You can use EKS Auto Mode to get Kubernetes conformant managed compute, networking, and storage for any new or existing EKS cluster. This makes it easier for you to leverage the security, scalability, availability, and efficiency of AWS for your Kubernetes applications. EKS Auto Mode removes the need for deep expertise, ongoing infrastructure management, or capacity planning by automatically selecting the best EC2 instances to run your application. It helps optimize compute costs while maintaining application availability by dynamically scaling EC2 instances based on demand. EKS Auto Mode provisions, operates, secures, and upgrades EC2 instances within your account using AWS-controlled access and lifecycle management. It handles OS patches and updates and limits security risks with ephemeral compute, which strengthens your security posture by default.

EKS Auto Mode is available today in all AWS Regions, except AWS GovCloud (US) and China Regions. You can enable EKS Auto Mode in any EKS cluster running Kubernetes 1.29 and above with no upfront fees or commitments—you pay for the management of the compute resources provisioned, in addition to your regular EC2 costs. 

To get started with EKS Auto Mode, use the EKS API, AWS Console, or your favorite infrastructure as code tooling to enable it in a new or existing EKS cluster. To learn more about EKS Auto Mode and how it can streamline your Kubernetes operations, visit the EKS Auto Mode feature page and see the AWS News launch blog.

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Amazon Connect now offers new capabilities to proactively engage your customers in a personalized manner. These features help non-technical business users create customer segments using prompts and drive trigger-based campaigns to deliver timely, relevant communications to the right audiences.

Use new segment AI assistant in Amazon Connect Customer Profiles to build audiences using natural language queries and receive recommendations based on trends in the customer data. Identify segments such as customers with an increase in support cases over the last quarter, or whose have reduced purchases in the last month, using easy-to-use prompts. Use new trigger-based campaigns based on real-time customer events on Amazon Connect outbound campaigns to proactively drive outbound communications in just a few clicks. Engage customers with timely, relevant communications via their preferred channels, responding instantly to behaviors such as abandoned shopping carts or frequent visits to specific help pages.

With Amazon Connect Customer Profiles and Amazon Connect outbound campaigns, only pay-as-you-go for customer profiles utilized daily, outbound campaigns processing and for associated channels usage. Both features of Amazon Connect are available in US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), Canada (Central), Europe (Frankfurt) and Europe (London) AWS regions. In addition, segment AI assistant is available in Asia Pacific (Seoul), Asia Pacific (Tokyo) and Asia Pacific (Singapore) AWS regions, with trigger based campaigns also available in Africa (Cape Town) AWS region. To learn more, visit our webpages for Customer Profiles and for outbound campaigns.

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Amazon Connect Contact Lens now provides you with the ability to automatically categorize your contacts using generative AI, making it easy to identify top drivers, customer experience, and agent behavior for your contacts. You can provide criteria to categorize contacts in natural language (e.g., did the customer try to make a payment on their balance?). Contact Lens then automatically labels contacts that meet the match criteria, and provides relevant points from the conversation. In addition, you can receive alerts and generate tasks on categorized contacts, and search for contacts using the automated labels. This feature helps supervisors easily categorize contacts for scenarios such as identifying customer interest in specific products, assessing customer satisfaction, monitoring whether agents exhibited professional behavior on calls, and more.

This feature is supported in the English language and is available in two AWS regions including US East (N. Virginia) and US West (Oregon). To learn more, please visit our documentation and our webpage. This feature is included within Contact Lens conversational analytics price at no additional cost. For information about Contact Lens pricing, please visit our pricing page.

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Amazon Q in Connect, a generative AI powered assistant for customer service, now enables customers to natively configure AI guardrails to implement safeguards based on their use cases and responsible AI policies. Contact center administrators can configure company-specific guardrails for Amazon Q in Connect to filter harmful and inappropriate responses, redact sensitive personal information, and limit incorrect information in the responses due to potential large language model (LLM) hallucination.

For end-customer self-service scenarios, guardrails can be used to ensure Amazon Q in Connect responses are constrained to only company-related topics and maintain professional communication standards. Additionally, when agents leverage Amazon Q in Connect to help solve customer issues, these guardrails can prevent accidental exposure of personally identifiable information (PII) to agents. Contact center administrators will have the flexibility to configure these guardrails and selectively apply them to different contact types.

For region availability, please see the availability of Amazon Connect features by Region. To learn more about Amazon Q in Connect, please visit the website or see the help documentation.
 

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Today, AWS announces the preview of Amazon Elastic VMware Service (Amazon EVS). Amazon EVS is a new, native AWS service to run VMware Cloud Foundation (VCF) within your Amazon Virtual Private Cloud (Amazon VPC). 

Amazon EVS automates and simplifies deployments and provides a ready-to-use VMware Cloud Foundation (VCF) environment on AWS. This allows you to quickly migrate VMware-based virtual machines to AWS using the same VCF software and tools you already use in your on-premises environment. 

With Amazon EVS, you can now take advantage of the scale, resilience, and performance of AWS together with familiar VCF software and tools. You have the choice to self-manage or leverage AWS Partners to manage and operate your EVS deployments. With this, you keep complete control over your VMware architecture and can optimize your deployments to meet the unique demands of your applications. Amazon EVS provides the fastest path to migrate and operate VMware workloads on AWS.

Amazon EVS is currently available in preview for pre-selected customers and partners. To learn more about Amazon EVS and how it can help accelerate your VMware workload migration to AWS, visit the Amazon EVS product page or contact us.

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Amazon Connect now allows you to compare intraday forecasts against previously published forecasts, review projected daily performance, and receive predictions for effective staffing, all available within the Amazon Connect Contact Lens dashboards. With intraday forecasts, you receive updates every 15 minutes with predictions for rest-of-day contact volumes, average queue answer time, average handle time, and, now, effective staffing. These forecasts allow you to take proactive actions to improve customer wait time and service level. For example, contact center managers can now track agent utilization at the queue level, enabling them to identify potential imbalances or staffing shortages and take action before wait times are impacted.

This feature is available in all AWS Regions where Amazon Connect forecasting, capacity planning, and agent scheduling is available. To learn more see the Amazon Connect Administrator Guide.

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Today, AWS introduces an enhanced version of SaaS Quick Launch for Databricks Data Intelligence Platform in AWS Marketplace, delivering a streamlined Databricks workspace deployment experience on AWS. Databricks is a unified data analytics platform that enables organizations to accelerate data-driven innovation. SaaS Quick Launch for Databricks automates installation and configuration steps, simplifying the process of launching Databricks workspaces on AWS, where data professionals manage notebooks, clusters, and data engineering jobs.

Previously, deploying Databricks on AWS required manual configuration and knowledge of AWS infrastructure provisioning tools. Now all users, including data engineers, data scientists, and business analysts, can quickly and easily deploy Databricks on AWS through AWS Marketplace in three guided steps. When subscribing to Databricks in AWS Marketplace, customers can use the new streamlined deployment experience to rapidly configure, deploy, and access their Databricks workspaces and accelerate their data analytics, machine learning, and data science initiatives on AWS. Through this simplified process, the necessary AWS resources are automatically provisioned and integrated with Databricks following AWS best practices for security and high availability.

This streamlined deployment experience in AWS Marketplace is currently available for all AWS Regions supported by Databricks.

To get started with the new streamlined deployment experience for Databricks, visit Databricks Data Intelligence Platform in AWS Marketplace.

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