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GitHub Copilot auto model selection now offers three tiers: efficiency, balance, and intelligence. Choose the tier that reflects how you want auto to weigh cost, quality, and response time for… The post Configure cost and quality in Copilot auto model selection appeared first on The GitHub Blog.
When something breaks in production, the questions that matter most are also the toughest to answer from metrics alone: who was affected, what did they actually see, and is this worth waking someone up for? Answering those questions requires a fuller picture of the issue and its impact on your users. That’s where Digital Experience Monitoring (DEM) in Grafana Cloud comes in. By combining Frontend Observability and Synthetic Monitoring, DEM connects real user experiences with proactive testing,
Part 1 showed how row lock contention degrades Amazon Aurora PostgreSQL throughput. In Part 2, use Amazon CloudWatch Database Insights and its Lock Tree to pinpoint blocking sessions, then resolve contention with query termination, timeout parameters, and architectural patterns such as SKIP LOCKED and row splitting that restore throughput.
Row lock contention can collapse database throughput during a flash sale even when CPU and I/O look healthy. In Part 1 of this series, learn how PostgreSQL row locking works and how to monitor lock contention in Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL using system views, the pgrowlocks extension, and the log_lock_waits parameter.
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WordPress has announced it's launching an automated security review for every release of a plugin before it's distributed through the WordPress.org update API so as to analyze it for potential security issues and ensure there are no risks involved. "New plugins are reviewed before they enter the directory, but updates ship continuously after that," David Perez, WordPress Official Plugin
BigQuery now features a suite of augmented analytics Table-Valued Functions (TVFs) designed to automate complex data analysis at scale. Augmented analytics combines AI, ML and statistical methods to automate insight discovery and pattern explanation. These functions allow you to diagnose why metrics changed, uncover underlying trends and relationships across the data, and even isolate the true impact of business decisions. These TVFs run directly where your data lives, which helps speed up anal
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