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DZone.com Feed Recent posts on DZone.com Apache Phoenix: Global Secondary Indexes With Tunable Consistency 6 Oct 2026, 19:00 by Viraj Jasani Apache Phoenix provides an open-source SQL interface over Apache HBase, combining the power of NoSQL horizontal scaling and sharding with SQL simplicity for low-latency and high-throughput OLTP operations on petabyte-scale data.  Phoenix complements HBase by providing capabilities such as Global Secondary Indexes (GSIs), Atomic and Conditional updates, change data capture (CDC) streams, Updatable views, and multi-tenancy support across tables, indexes, and views. Furthermore, it supports server-side push-down execution for complex OLAP joins and grouping operations. ‍ Building and Serving a Custom Model With Azure ML, Then Wiring It Into a Foundry Agent 6 Oct 2026, 18:00 by Jubin Soni, FBCS The Foundry model catalog covers a lot of ground, but it doesn't cover everything. If you need a model trained on your own proprietary, tabular data, a churn predictor built on your actual customer history, a fraud score trained on your actual transaction patterns, that's not a model catalog problem. That's a real machine learning problem, and on Microsoft's stack it belongs to Azure Machine Learning, a genuinely separate platform from Foundry with its own SDK, its own workspace concept, and its own deployment model. This is a hands-on build of the whole path: train a model with Azure ML's SDK, register it, deploy it behind a managed endpoint, and then wire that endpoint into a Foundry agent as a function tool, so a conversational agent can call your custom model mid-conversation the same way it would call any other tool. ‍ Resume the Evaluation, Not the Entire Batch: Build a Checkpoint-Aware AI Job Controller With Temporal 6 Oct 2026, 17:00 by Akhil Madineni Large AI evaluations rarely fail at convenient boundaries. A batch may contain tens of thousands of prompts, retrieval cases, tool-use scenarios, or judge-model comparisons, and each case can involve expensive network calls plus result persistence. Restarting the entire batch after a worker crash wastes inference spend and can change the meaning of the run when model outputs are nondeterministic.  Temporal provides durable orchestration, but durability alone does not create application-level checkpoints. A reliable controller needs an explicit recovery boundary: completed evaluation cases stay completed, retries restart from a durable cursor, and the workflow remains small enough to replay efficiently. ‍ Building IoT Time-Series Applications With Java and Apache IoTDB 6 Oct 2026, 16:00 by Otavio Santana Apache IoTDB is well-suited for environments where time-series data from connected devices and industrial systems is generated continuously and requires efficient querying. Typical use cases include monitoring temperature, pressure, vibration, energy usage, machine status, and device telemetry. This approach also applies to manufacturing, smart infrastructure, fleet monitoring, utilities, and edge computing. IoTDB stands out for its focus on large-scale time-series workloads from devices and industrial systems. It is purpose-built for high-frequency data ingestion, historical analysis, and time-based queries. This makes it ideal for applications that require insight into both the current state and historical trends of devices or processes. ‍ Beyond @Transactional: Solving the Dual-Write Problem in Distributed Microservices 6 Oct 2026, 15:00 by Rahul Tewari The Illusion of a Single Database In a traditional monolithic application, maintaining data consistency is straightforward. If you need to create a new order and update warehouse inventory, you wrap the logic inside a single database transaction: Java   @Transactional public void placeOrder(OrderRequest request) { orderRepository.save(request.toOrder()); inventoryRepository.decrementStock(request.getItemId(), request.getQuantity()); } ‍ OpenSearch Heap Sizing: Swap, Page Cache, and the 50% Rule 6 Oct 2026, 14:00 by Maxim Muzafarov OpenSearch is an open-source, distributed search and analytics suite derived as a fork of Elasticsearch and maintained under the Apache 2.0 license. When it comes to memory configuration, the guidance is often reduced to a few rules of thumb: swapoff -a, vm.swappiness=1, or bootstrap.memory_lock, and allocating 50% of available memory to the JVM heap while leaving the rest for Lucene and the filesystem page cache, OpenSearch off-heap caches, network buffers, and other system needs. These recommendations are repeated throughout documentation, blog posts, and operational guides, yet their origins and the mechanisms that justify these specific values are rarely examined. Undoubtedly, they provide a reasonable and safe starting point or a safe upper bound in most of the cases, but a safe default is not necessarily an optimal configuration. ‍ ‍ You are receiving this email because you subscribed to this feed at blogtrottr.com. By using Blogtrottr, you agree to our terms. If you no longer wish to receive these emails, you can unsubscribe from this feed, edit this subscription, or manage all your subscriptions.