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Aspia classifies every insured field by capacity, volatility, and structural floor from 10 years of continuous observation, independent of the carrier's own risk assessment. When a cedant can demonstrate field-level governance, treaty pricing reflects it. When they can't, the gap is yours to carry. This is already in operation: one major reinsurer requires systematic monitoring as a governance condition of their agricultural treaty.

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We’re excited to share that AWS has officially published AutoMQ’s Partner Success Story featuring FunPlus. AutoMQ is an AWS Differentiated Partner and is available on AWS Marketplace, so AWS customers can subscribe to AutoMQ directly through their existing cloud procurement workflow. The newly published AWS Partner Success Story highlights FunPlus, a global interactive entertainment company behind games such as State of Survival, King of Avalon, Guns of Glory, and DC: Dark Legion. For gaming platforms running high-throughput Kafka workloads on AWS, cost is often hidden in the network path, not only in broker instances. The FunPlus case shows how AutoMQ on AWS helps reduce that pressure: 1️⃣ Reduce cross-AZ traffic fees by changing the Kafka storage and replication model. 2️⃣ Keep Kafka-compatible APIs so existing producers, consumers, and stream processing jobs continue to work. 3️⃣ Run a cloud-native Kafka architecture on AWS while aligning infrastructure spend more closely with workload growth. 🔎 The result: 𝟓𝟎% 𝐥𝐨𝐰𝐞𝐫 𝐊𝐚𝐟𝐤𝐚 𝐜𝐨𝐬𝐭 by reducing cross-AZ traffic fees. 👉 Read the AWS Partner Success Story: https://lnkd.in/gHau9fnp Subscribe on AWS Marketplace: https://lnkd.in/gi_xPM9H For more Kafka and AutoMQ engineering insights, follow AutoMQ on LinkedIn or join the AutoMQ Slack community: https://lnkd.in/gk8txSCU #Kafka #ApacheKafka #AWS #AWSMarketplace #StreamingData #GamingInfrastructure #AutoMQ

"ASA’s Neurodiversity Training helped our leaders build the skills to support neurodiverse staff and ensure they are set up for success.”

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Imagine a material MIFIDPRU figure is challenged tomorrow. Could you quickly produce the source data, calculation logic, adjustments, assumptions, reconciliations, approvals and reporting history? If gathering that evidence would mean pulling together spreadsheets, emails and information from different teams, there may be gaps worth addressing. How defensible is your MIFIDPRU reporting?

A MIFIDPRU number changes. The important question is: why? Was the source data corrected? Did an assumption change? Was the calculation methodology updated? A strong reporting process doesn't just produce the latest figure. It preserves the evidence needed to understand and explain how that figure changed. Make every MIFIDPRU number defensible.

𝗔𝗱𝗼𝗯𝗲 is running AutoMQ in production across 𝟰𝟬+ 𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀 in place of vanilla Kafka. Pranshu Jain at Adobe just shared this production data point. What stood out to me is how focused the change was: existing Kafka clients stayed untouched, while Kafka data moved from broker-local disks to object storage. According to Pranshu, that removed most of the infrastructure cost around the Kafka layer, along with the 2 a.m. rebalancing pages. The broader architecture is equally interesting: 𝘈𝘶𝘵𝘰𝘔𝘘 → 𝘖𝘱𝘦𝘯𝘛𝘦𝘭𝘦𝘮𝘦𝘵𝘳𝘺 → 𝘝𝘪𝘤𝘵𝘰𝘳𝘪𝘢𝘔𝘦𝘵𝘳𝘪𝘤𝘴 + 𝘚𝘪𝘨𝘕𝘰𝘻 → 𝘔𝘊𝘗 → 𝘰𝘱𝘦𝘯 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘮𝘱𝘳𝘦𝘴𝘴𝘪𝘰𝘯 → 𝘊𝘭𝘢𝘶𝘥𝘦 𝘰𝘯 𝘈𝘮𝘢𝘻𝘰𝘯 𝘉𝘦𝘥𝘳𝘰𝘤𝘬 → 𝘈𝘐𝘖𝘱𝘴 Across the overall observability stack, the #Datadog bill was 𝗿𝗲𝗱𝘂𝗰𝗲𝗱 𝗯𝘆 𝗿𝗼𝘂𝗴𝗵𝗹𝘆 𝟳𝟬% this quarter. Prompt caching cut inference spend by more than half. That architecture is a natural fit for observability. The workload is data-intensive and cost-sensitive, and telemetry volumes can change quickly, making elastic scaling a regular requirement rather than an edge case. AutoMQ's S3-backed, stateless Diskless Kafka architecture addresses these pressures: durable data sits in object storage rather than on broker-local disks, while compute can scale without moving large volumes of partition data. We're seeing more companies adopt AutoMQ for observability, and a clear pattern is emerging: Diskless Kafka is becoming a core architectural pattern for modern observability data stacks. It's also exciting to see Adobe use Kafka as the streaming backbone for an observability + AI stack, connecting high-volume telemetry with AIOps. Congratulations to Pranshu and the Adobe team, and thank you for sharing the architecture. 👉 See Pranshu's original post for the full implementation: https://lnkd.in/p/dEGrAAmm 🌐 Go under the hood of AutoMQ's diskless Kafka architecture: Kafka-compatible streaming backed by object storage, designed to reduce data movement and broker-local disk operations: https://lnkd.in/gmXZJaUd How are you using Kafka to build a modern observability platform? I'd be interested to compare approaches across telemetry ingestion, storage, query, and AIOps. #AutoMQ #Kafka #Observability #AIOps #Adobe #Datadog

Considering that 20% of the population is #Neurodivergent (e.g. #Autism, #ADHD, #Dyslexia, #Dyspraxia), it is inevitable that many people in your organisation belong to the ‘world’s biggest minority group’ – that’s over five million Australians, and over 1.6 billion people worldwide. In our latest blog post, our Learning and Development Manager, Brendon Eglinton, shares his insights on how our Neurodiversity Training Program (https://lnkd.in/ghC2fSQJ) has helped more workplaces become neuroinclusive by implementing our lived experience tips and tricks, which are all low or no-cost. We’ve even had people in the audience disclose their #Neurodivergence for the very first time because they were in a safe environment! 'A common thread is the realisation that neurodiversity in the workplace is not that bloody hard! Many begin unaware or hold preconceptions about autism, ADHD, dyslexia and other neurodivergent elements. Sharing who we are helps participants personalise and relate during the learning experience.' Read more here: https://lnkd.in/grRXFTJZ #Sustainability #UNSDG #SustainableDevelopment #GIS #GeographicInformationSystems #MechanicalEngineering #DigitalEngineering #CivilEngineering #ElectricalEngineering #Neurodiversity #NeurodiversityInTheWorkplace #NeurodiversityAtWork #Diversity #DiversityAndInclusion #NeurodiversityTraining #SocialEnterprise #Spatial #SpatialData #SpatialIntelligence #Geospatial #Engineering #SocialImpact #NeurodiversityTraining

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Between them, Supper co-founders Lowell Putnam and Andrew Salamon have nearly a dozen exits. View this webinar to learn about decision frameworks, when OKRs help (vs. hurt), and how to make your board a true advantage: https://lnkd.in/eckNBQFB Unlock a practical “operating system” for running a startup.

Between them, Supper co-founders Lowell Putnam and Andrew Salamon have nearly a dozen exits. Watch this webinar recording to learn about their decision frameworks, when OKRs help (vs. hurt), and how to make your board a true advantage: https://lnkd.in/evqTP65R Unlock a practical “operating system” for running a startup.

Independent research from BARC shows why observability is becoming non-negotiable in 2025. Get the roadmap for building programs that actually work.