Rita Zhang

https://lnkd.in/grvbsXFP New blog post. I'm showing how to: => Create an Auth Token in OCI. => Create an Object Storage Bucket in OCI. => Create a Lifecycle Policy Rule in the Object Storage Bucket. => Create a Credential in Autonomous Database. => Create a PL/SQL Procedure to: ====> Execute a Data Pump Export using DBMS_DATAPUMP. ====> Copy the Dump and Log Files to the Object Storage Bucket. ====> Manage the retention inside DATA_PUMP_DIR directory object. => Create a Scheduler Job Class. => Create a Scheduler Job. => Check the execution of the Scheduler Job. => Check the content for the Object Storage Bucket.

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Want to use Anthropic's Claude models with Microsoft.Extensions.AI? Here's how to bridge the gap until official SDK support arrives. ✨ What you'll learn: • Transform OpenAI format to Claude's Anthropic API • Handle authentication differences (x-api-key vs Bearer tokens) • Implement real-time streaming with Server-Sent Events • Work with DelegatingHandler for protocol bridging This hands-on guide includes complete code examples and a working sample you can run today. Perfect for .NET developers exploring AI integrations! 🧑‍💻 #DotNet #AzureAI #ClaudeAI #AI

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ClickHouse doesn't have built-in schema migration support. In 2026. For a database used in production by thousands of companies. https://lnkd.in/gCU-4Fry That's not a niche edge case. Schema changes are one of the most common operations in any production database. And in ClickHouse, what looks like a simple column addition can trigger a full table rewrite when you're streaming hundreds of megabytes per second. Tinybird's own migration story is telling. Their first approach to handling materialized view changes was, in their words, "bulletproof but brutally inefficient." Touch just one materialized view and you'd migrate terabytes of upstream data. For a 14TB Kafka table, that meant days-long deployments. Every database has tradeoffs. ClickHouse is genuinely fast for narrow analytical queries. But if your workload evolves (and it will), the operational cost of that evolution is worth understanding before you're 14TB deep. What's the most painful schema migration you've dealt with?

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.@Microsoft spins up @Azure HorizonDB to take on distributed Postgres rivals https://bit.ly/43CDWlL @TheRegister "PostgreSQL is really the hope of potential code compatibility between the different clouds... and it's the potential bet for something other than...”#MSIgnite #NextGenApps

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Did you know? Running Amazon EKS at a larger scale can lead to challenges related to IP address limits, impacting the number of pods that can operate on a node. 👉 https://lnkd.in/epH8e5Bn #AWS #Containers #Docker #CloudNative #PlatformEngineering #Kubernetes

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Unlock DevOps Efficiency: Azure Managed Service for Prometheus Now Integrates Native Grafana Dashboards Cloud leaders, here’s a significant update that simplifies your observability workflows. Azure’s Managed Service for Prometheus now includes **native Grafana dashboards directly within the Azure portal — at no extra cost**. This integration removes the need to toggle between different tools, enabling your teams to visualize metrics seamlessly and respond faster to operational issues. As an Azure cloud architect, I’ve seen how fragmented monitoring setups increase administrative overhead and slow down incident response. Embedding Grafana dashboards natively means your #DevOps and engineering teams gain streamlined access to powerful, customizable visualizations, all governed within Azure’s secure environment. This efficiency boost translates to sharper insights, reduced complexity, and ultimately, stronger service reliability. For CIOs and CTOs, it’s a strategic win that aligns with cloud-native principles, cutting operational friction while optimizing costs. Embracing such enhancements ensures your infrastructure monitoring keeps pace with evolving business demands without compromising governance or scalability. If observability challenges have ever felt like a bottleneck, this native integration is a game changer for simplifying and unifying your monitoring landscape. Explore how this update could impact your cloud strategy and team productivity. Read the full article here: https://lnkd.in/grvGknrE #Azure #CloudObservability #Prometheus

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New #Exascale database enables real-time failover, multicloud elasticity, and localized AI data compliance--Read the SDxCentral article on Oracle Globally Distributed Exadata Database on Exascale Infrastructure: https://lnkd.in/gCFiphnD

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Google Cloud’s June Database Digest Highlights: 🌐 Cross-region Spanner federation with BigQuery (Preview): Query data across Spanner instances in different regions without replication, enabling global insights with minimal latency. 📊 Bigtable integration with Apache Iceberg: Unlock interoperability for real-time and batch analytics by leveraging Iceberg’s open table format with Bigtable’s low-latency performance. 🤖 Vertex AI Ranking API (GA): Optimize search and recommendation systems with ML-powered ranking, reducing development time for AI-driven applications. 🚀 AlloyDB & Cloud SQL Updates (GA): Enhanced PostgreSQL-compatible performance, scalability, and reliability for mission-critical workloads. Transform your data strategy with these cutting-edge tools: https://lnkd.in/gHvvwTGV #GoogleCloud #DataEngineering #CloudDatabases #AI #BigQuery #AlloyDB

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Big design win for Timescale “Cloudflare Chooses PostgreSQL Extension Over Specialized OLAP for 100K Row/Second Analytics - InfoQ” “In a recent article from the engineering team behind the Zero Trust product suite, Cloudflare explains why it chose TimescaleDB over ClickHouse to add analytics and reporting capabilities to its internal platform. The author highlights the "phenomenal balance" between the simplicity of storing analytical data alongside configuration data and the performance of a specialized OLAP system.” https://lnkd.in/ePZKetws

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