About this episode
Welcome to episode 275 of The Cloud Pod, where the forecast is always cloudy! Justin, Matthew and Ryan are awake and ready to bring you all the latest and greatest in cloud news, including SQream, a new partnership between OCI and AWS (yes, really) Azure Linux, and a lot of updates over at AWS. Get comfy and we’ll see you all in the cloud! Titles we almost went with this week: I SQream, You SQream, The CloudPod SQreams for AI Ice Cream ️AWS East gets Stability, but only for AI. AWS has some Lofty Goals ️Claude Learns BigQuery ✅Azure now Securely Checks the Prompts from the cloud pod Azure find out about Linux A big thanks to this week’s sponsor: We’re sponsorless! Want to get your brand, company, or service in front of a very enthusiastic group of cloud news seekers? You’ve come to the right place! Send us an email or hit us up on our slack channel for more info. AWS 00:28 Stability AI’s best image generating models now in Amazon Bedrock If you are like The CloudPod hosts, the part you care most about AI is the rapid ability to create graphics for any meme-worthy moment or funny pictures for that group chat. Luckily AWS has access to the latest image generation capability with 3 models from Stability AI . Stable Image Ultra – Produces the highest quality, photorealistic outputs perfect for professional print media and large format applications. Stable image Ultra excels at rendering exceptional detail and realism. Stable diffusion 3 large – strikes a balance between generation speed and output quality. Ideal for creating high-volume, high-quality digital assets for websites, newsletters and marketing materials. Stable Image Core – Optimized for fast and affordable image generation, great for rapidly iterating on concepts during ideation. One of the key improvements of Stable Image Ultra and Stable Diffusion 3 large compared to Stable Diffusion XL (SDXL) is text quality in generated images, with fewer errors in spelling and typography thanks to innovation diffusion transformer architecture, which implements two separate sets of weights for image and text but enables information flow between the two modalities. 02:46 Justin – “I do notice more and more that, you get it, you get the typical product shot on Amazon, but then like they’ll insert the product into different backgrounds and scenes. Like, it’s a, it’s a lamp and all of a sudden it’s on a thing and they’re like, Hmm, that doesn’t look like a real photo though. It looks like AI. So you do notice it more and more.” 04:13 AWS Network Load Balancer now supports configurable TCP idle timeout AWS Gateway Load Balancer now supports configurable TCP idle timeout We see you Amazon – trying to get two press releases for basically the same thing, not today sir! Both the AWS Network Load Balancer and Gateway Load Balancer have received a configurable TCP Idle timeout. AWS Network load balancer had a fixed value of 350 seconds, which could cause TCP handshake retries for long-lived traffic flows of some apps and add latency. Now you can configure it between 60 seconds and 6000 seconds, with the default remaining at 350. The Gateway also has a 350 second fixed value, and also gets the 60-6000 second range. Want more info on these totally different and not at all the same announcements? Check it out here . 04:53 Ryan – “Yeah, we’ve all worked at that company with that one ancient app that, you know, couldn’t handle retries. 05:44 AWS Fault Injection Service introduces additional safety control Fault Injection Service now provides additional safety control with a safety lever that, when engaged, stops all running experiments and prevents new experiments from starting. You can also prevent fault injection during certain time periods, such as sales events or product launches, or in response to application health alarms. 06:22 Ryan – “ …in my head I immediately went to like, something bad happened that caused this feature to exist. Like, I feel bad for whoever that was. Because you know it wasn’t good.” 07:14 Use Apache Spark on Amazon EMR Serverless directly from Amazon Sagemaker Studio You can now run petabyte-scale data analytics and machine learning in EMR Serverless direction from SageMaker Studio notebooks. Serverless automatically provisions and scales the needed resources, allowing you to focus on data and models without having to configure, optimize, tune or manage your clusters. 07:40 Ryan – “Yeah, is it the query that’s terrible or the underlying data? The world may never know. Or both. It’s both.” 07:57 Bedrock Agents on Sonnet 3.5 Agents for Amazon Bedrock enable developers to create generative AI-based applications that can complete complex tasks for a wide range of use cases, and deliver answers based on company knowledge sources. 08:32 Justin – “It’s just an AI bot you put onto your Slack team that, you know, answers questions based on data you’ve fed it basically. Yeah. Agents is really just a chat interface to an AI of some kind that you’ve fed data to.” 08:58 Amazon WorkSpaces Pools now allows you to bring your Windows 10 or 11 licenses If you are leveraging Amazon Workspace Pools powered by Windows 10 or 11, you can now Bring your own License (assuming you meet microsoft requirements) to support your eligible M365 apps for enterprise, providing a consistent desktop experience to their users when they switch between on-premise and virtual desktops. 09:28 Ryan – “I doubt they’re talking about a single user. I think it’s like if you’re an IT department, you have to manage both..” 10:45 Amazon ECS now supports AWS Graviton-based Spot compute with AWS Fargate Amazon ECS now supports AWS Graviton-based compute with AWS Fargate Spot. This capability helps you run fault-tolerant arm-based applications with up to a 70% discount compared to fargate prices. And yes, this is as complicated as it seems. 11:13 Ryan – “All this means is that they finally got their inventory up on Graviton hardware in the data centers where they can start allowing it to work.” 12:33 AWS GenAI Lofts AWS pre-pandemic (in the “before times”) used to have AWS Lofts, where you could go and hang out with experts, community events would be held and overall you could pop in to get 1:1 assistance on your cloud project. After the pandemic, however, they sort of disappeared – but AWS has brought them back as the Gen AI Lofts. Unfortunately they’re not permanent lofts; they’re just pop-up events. Currently the lofts are located in San Francisco and São Paulo , with London , Paris , and Seoul opening in October. The SF one is being held in the AWS office in downtown San Francisco. 14:36 Justin – “I think it’s nice to be able to go someplace and get, you know, A) talk to people who are trying to do the same thing you’re trying to do. And number two, if they don’t know, then you can ask the expert who’s there and you can, then he can get the answer for you. Because they’re the experts and they have access to the product managers and different things. 15:31 Amazon MSK enhances cross-cluster replication with support for identical topic names Amazon MSK replicator now supports a new configuration that enables you to preserve original Kafka topic names while replicating streaming data across Amazon Managed Streaming for Kafka Clusters. Amazon MSK replicator is a feature of Amazon MSK that lets you reliably replicate data across MSK clusters in the same or different AWS regions with just a few clicks. Let’s be real. The fact that you couldn’t use the same topic name between clusters in different regions was a *problem*. We’re really glad they fixed this one. 15:56 Ryan – “I’m sure people have just been working around this with application config, based on where the workload is hosted.” 17:22 Amazon SageMaker HyperPod introduces Amazon EKS support AWS is announcing that EKS is now supported in Amazon Sagemaker Hyperpods . This purpose built infrastructure is engineering with resilience at its core for foundation model development. This allows customers to orchestrate hyperpod clusters using EKS , combining the power of K8 with Hyperpods resilient environment designed for training large models. 18:00 Ryan – “Historically these, types of jobs haven’t been really designed with resilience, right? It’s like, it could have a failure and then you have to restart a job or a series of jobs. going to take hours to complete. So it is kind of nice to see this…but it is kind of funny.” GCP 18:41 Google named a leader in the Forrester Wave: AI/ML Platforms, Q3 2024 Google is named a leader in the Forrester Wave… which is cool and we wouldn’t have even mentioned, but the Top Current offering was Palantir? Should we be concerned? Palantir apparently has one of the strongest offerings in the AI/ML space, with a vision and roadmap to create a platform that brings together humans and machines in a joint-decision making model. Uh huh… But back to Google… Google is the best positioned hyperscaler for AI. Google Vertex AI is thoughtfully designed to simplify access to Google’s portfolio of AI infrastructure at planet scale, AI models, and complementary data services. The company continues to outpace competitors in AI innovation, especially in genAI , and has a strong roadmap to expand tooling for multirole AI teams. Google has also worked hard to nurture a large set of well-incented partners that is likely to help it increase adoption of Google Vertex AI. Google has enough differentiation in AI from other hyperscalers that enterprises may decide to migrate from their existing hyperscaler to Google – or at least start a new relationship with Google Cloud. Want your own copy of the Forrester Wave? Find it here . 20:20 Justin – “Apparently Google is the best positioned hyperscaler for AI. Take that Azure.” 20:55 Matthew – “Okay, so C3AI, I haven’t actually done any research, but their stock symbol is just AI. I think they win… just hands down they win. Like game over, everyone else should just not be on the leaderboard.” 22:00 BigQuery and Anthropic’s Claude: A powerful combination for data-driven insights Google Cloud is extending their Open Platform with the preview of BigQuery ’s new integration with Anthropic Claude models on Vertex AI that connects your data in BigQuery with powerful intelligence capabilities of Claude models. BigQueries integration with Anthropic Claude models allows organizations to reimagine data driven decision making and boost productivity across a variety of tasks including: Analyzing log data for enhanced security Marketing optimization Document summarization Content localization 20:27 Justin – “If Jonathan were here – and not sleeping / napping – he would tell you that cloud’s pretty darn good. And so, this is actually pretty nice to get an alternative that’s pretty decent to Gemini, to give you some additional BigQuery options for your summarization and advanced logging analytics. Apparently.” 23:50 Cut through the noise with new log scopes for Cloud Observability GCP is introducing log scopes for cloud logging – a significant advancement in managing and analyzing your orgs logs. Log scopes are a named collection of logs of interest within the same or different projects. They are groups of log views that control and grant permissions to a subset of logs in a log bucket . Combined with metric scopes , log scopes let you define a set of correlated telemetry for your application, which can then be used for faster troubleshooting or referencing for insights. Some example use cases from the press release: Use Case 1: Correlating metrics with logs from the same application when an organization uses a centralized log storage architecture. Use Case 2: Correlating metrics with logs for isolated environments such as development, staging and production across projects. 24:35 Ryan – “ …that second one is the one I’m most interested in just because it’s, you know, for all kinds of reasons, we’ve separated workloads out and put them into different projects and for blast radius and security concerns and all those things, but it becomes much more challenging to sort of correlate a transaction through many, many different services spread out through multiple projects. And so there’s sort of two ways you tackle that. One is just re-consolidate all the logs together, and that can get expensive and generate this condition where you’re sorting through a whole bunch of noise. Or it’s like you just look it up everywhere and you manually construct it back together, which just doesn’t work and no one does. That’s what we used to do when all the logs were on server hard disks. So this is really neat to be able to tag them all together, really, and then search on them from that tag, which I think is pretty neat.” 25:59 Introducing backup vaults for cyber resilience and simplified Compute Engine backups Google is enhancing Google Cloud Backup and DR service with some new capabilities: New Backup Vault storage feature, which delivers immutable (preventing modification) and indelible (preventing deletion) backups, securing your backups against tampering and unauthorized deletion A centralized backup management experience, which delivers a fully managed end-to-end solution, making data protection effortless, and supporting direct integration into resource management flows Integration within the compute engine vm creation experience, empowering application owners to apply backup policies when VMs are initially created. These are all good quality of life improvements. 26:26 Ryan – “Yeah, I mean, the backup policy is specifically when VMs are created is definitely something that, you know, I would like to see more features in that direction.” Azure 28:31 Azure CLI docker container base Linux image is now Azure Linux Starting with version 2.64.0 of Azure CLI, the base linux distribution of Azure CLI is now Azure Linux. There is no impact to your az commands; shell commands specific to alpine will not work (apk) and Github actions that use specific alpine components or commands. You also have to trust that Microsoft Azure Linux is secure and as great as Alpine. Insert your favorite side eye meme here. 30:05 Justin – “…it’s a supply chain problem. It’s – how do you tell the government that you’re sure that nothing in your, you know, in your Linux operating system is compromised by a third party nation state? The answer is, well, we own all of the source and we build our own version of Linux from that source and we review it all. And that’s how you solve this problem.” 33:45 General availability of Prompt Shields in Azure AI Content Safety and Azure OpenAI Service Azure is announcing the GA of Prompt Shields in Azure AI Content safety and Azure OpenAI service, a robust AI security feature announced in March 2024 . Prompt Shields seamlessly integrate with Azure OpenAI service content filters and are available in Azure AI content safety, providing a robust defense against different types of prompt injection attacks. By leveraging advanced machine learning algorithms and natural language processing, prompt shields effectively identify and mitigate potential threats in user prompts and third party data. 34:15 GA release of Protected Material Detection in Azure AI Content Safety and Azure OpenAI Service Protected material detection is an additional GA feature of AI content safety and Azure Open AI service. This feature addresses outputs that could potentially violate copyright. Many customers and end users are apprehensive about the risk of IP Infringement claims when integrating and using generative AI. To address this, the feature specifically targets model completions and scans for matches against an index of third party text content to detect the usage of third-party text content, including songs, news articles, recipes and selected web content. 34:33 Ryan – “I mean, it’s not really for its accuracy. It’s about the mitigation of risk when you get sued. Like, you can say, well, I tried, I turned all the checkboxes… I do think these kinds of features… will be in every product eventually.” 37:02 M-Series announcements – GA of Mv3 High Memory and details on Mv3 Very High Memory virtual machines Microsoft has released the third version of the M-Series (Mv#) powered by 4th generation Intel Xeon processors (Sapphire Rapids) across the board. These high memory VMs give customers faster insights, more uptime, lower total cost of ownership and improved price-performance for their most demanding workloads. What workloads do you ask? SAP Hana. Duh. The systems can scale for workloads from 6TB to 16TB, with up to 40% throughput over the Mv2 high memory. 416 VCPU, 6tb of memory and a max of 64 data disks. The largest configuration is 832 VCPU and 16TB of memory. Oracle 39:00 Breaking boundaries in ML development: SQream on OCI Oracle says that now is an exciting time to be developing AI and ML solutions. With investors and customers expecting AI and ML innovation at a dizzying pace, companies struggle moving from AI Proof of Concept to Production, with the issue quite often being the efficient handling and preparing of massive amounts of data – a critical step that bottlenecks everything else in the dev process. Oracle is pleased to share breakthrough technologies like SQream on OCI to improve the outcomes by transforming legacy processes by accelerating data preparation and reducing development cycles by over 90%. With these advancements, organizations can streamline their workflows and expedite AI deployments, ultimately enabling them to achieve their strategic objectives more effectively. Data Preparation: It involves labor-intensive, manual processes that are time-consuming, prone to errors, and often require multiple iterations, from manual scripting for data collection to painstaking efforts in data cleaning and complex custom scripting for integrating and transforming disparate datasets, manual processes can lead to significant delays. SQream on OCI dramatically impacts these tasks, streamlining and automating the processes by leveraging GPU-accelerated technology. Also with SQream, data scientists can quickly experiment with different feature sets and validate their effectiveness faster. SQream on OCI revolutionizes your team dynamics by enhancing collaboration, boosting morale and productivity, and optimizing human resource allocation. SQream also optimizes your hardware utilization leading to reduced operational costs. 40:46 Ryan – “I also think that every one of their claims is complete nonsense. I, cause it’s Oracle and it’s like, there’s no way.” 42:11 Oracle and Amazon Web Services Announce Strategic Partnership Open World is happening this week, and they dropped a ton of announcements today, which we’ll cover next week. *But* Sometimes a story is so important we must talk about it now. Folks, hell has not frozen over, nor are pigs flying. Oracle and AWS today announced the launch of Oracle Database@AWS, a new offering that allows customers to access Oracle Autonomous Database service within AWS. Oracle Database@AWS will provide customers with a unified experience between OCI and AWS offering a simplified database administration, billing, and unified customer support system. In addition, customers will be able to seamlessly connect enterprise data in their Oracle Database to apps running on Ec2, AWS analytics services, or AI and ML services including Bedrock. With direct access to Oracle Exadata database services on AWS, including Oracle Autonomous database on dedicated infrastructure and workloads running on RAC clusters, Oracle Database@AWS allows customers to bring together all of their enterprise data to drive breakthrough innovations. “We are seeing huge demand from customers that want to use multiple clouds,” said Larry Ellison, Oracle Chairman and CTO . “To meet this demand and give customers the choice and flexibility they want, Amazon and Oracle are seamlessly connecting AWS services with the very latest Oracle Database technology, including the Oracle Autonomous Database. With Oracle Cloud Infrastructure deployed inside of AWS data centers, we can provide customers with the best possible database and network performance.” “As far back as 2008, customers could run their Oracle workloads in the cloud, and since then, many of the world’s largest and most security-sensitive organizations have chosen to deploy their Oracle software on AWS,” said Matt Garman, CEO at AWS . “This new, deeper partnership will provide Oracle Database services within AWS to allow customers to take advantage of the flexibility, reliability, and scalability of the world’s most widely adopted cloud alongside enterprise software they rely on.” Customers can also benefit from the following with Oracle Database@AWS Zero-ETL integration between Oracle Database services and AWS Analytics services. Customers will be able to seamlessly and securely connect and analyze data across Oracle Database services and applications they already have running on AWS to get faster, deeper insights without having to build pipelines. Flexible options to simplify and accelerate migrating their Oracle databases to the cloud, including compatibility with proven migration tools such as Oracle Zero Downtime Migration. A simplified procurement experience via AWS Marketplace that enables customers to purchase Oracle Database services using their existing AWS commitments and use their existing Oracle license benefits, including Bring Your Own License (BYOL) and discount programs such as Oracle Support Rewards (OSR). A fully unified support experience from both AWS and Oracle as well as guidance through reference architectures, landing zones, and other collateral for customers to successfully build and run their most trusted enterprise applications in the cloud. Seamless integration with Amazon Simple Storage Service (Amazon S3) for an easy and secure way to perform database backups and restoration, and to aid with disaster recovery. 44:47 Matthew- “Half of these features already existed between just RDS Oracle and AWS I feel like, and the other half just use are a good way to kill all your EDP pricing – EDP that you have to finish by the end of the year.” Closing And that is the week in the cloud! Visit our website, the home of the Cloud Pod where you can join our newsletter, slack team, send feedback or ask questions at theCloud Pod.net or tweet at us with hashtag #theCloudPod