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Improving Lakebase Postgres compute cache
Tech Optimizer
September 11, 2026

Improving Lakebase Postgres compute cache

Lakebase Postgres employs a disaggregated storage model that enhances data management through efficient caching, utilizing an object store like S3 for backups. The caching operates on two layers: within distributed storage for optimizing write and read performance, and on the Postgres compute side for ultra-fast access to frequently accessed pages. Traditional Postgres caching involves shared buffers and the OS page cache, which leads to double buffering and inefficiencies. Lakebase Postgres addresses these issues by implementing a local file cache (LFC) and larger shared buffers, allowing for more effective memory utilization without the drawbacks of the OS page cache. The shared buffers are set to a maximum of 1 GB, while the LFC can utilize up to 75% of DRAM. The introduction of huge pages reduces memory management overhead and improves performance, resulting in significant throughput increases and reduced latency in production environments. Recent enhancements have shown up to 2× throughput improvements and substantial reductions in CPU usage. The focus is now on extending these benefits to autoscaling Postgres computes, with plans to implement dynamic shared buffers and autoscaling huge pages.
Pterodactyl Multi-Game Cloud Server: 13 Steps [2026]
AppWizard
September 6, 2026

Pterodactyl Multi-Game Cloud Server: 13 Steps [2026]

In 2026, hosting game servers has become more efficient, allowing multiple game servers to run on a single cloud VPS using Pterodactyl Panel, which utilizes Docker containers for isolation. Pterodactyl is a free, open-source game server management panel that gained popularity due to its user-friendly interface and robust architecture. The latest stable release, v1.12.0, was launched in January 2026, with newer deployment templates available as of August 2026. To set up Pterodactyl, prerequisites include a cloud VPS with specific CPU and RAM requirements, Ubuntu 24.04 LTS, PHP 8.3, MariaDB 11.8.8 or newer, Redis 8.10.0 or newer, Docker Engine, a registered domain for SSL, SteamCMD dependencies, and at least 80 GB SSD storage. The installation process involves provisioning the VPS, installing necessary software, configuring Pterodactyl, setting up Nginx with SSL, and deploying game servers. Common pitfalls include under-provisioning RAM for resource-intensive games, neglecting firewall settings, and allowing backup retention to grow uncontrollably. Troubleshooting may involve addressing PHP-FPM issues, connection problems, and ensuring proper resource allocation. Advanced scaling may require multiple VPS nodes, and security measures like two-factor authentication can help protect the server. Pterodactyl is free to use commercially and can run multiple game containers on a single node.
Windows 11's Project Zenith cuts clutter for developers and promises a "distraction-free" experience
Winsage
September 4, 2026

Windows 11’s Project Zenith cuts clutter for developers and promises a “distraction-free” experience

Microsoft is launching Project Zenith, which optimizes Windows 11 for developers by preinstalling essential applications and configuring settings tailored for coding. Key features include File Explorer displaying file extensions, hidden files, and the complete path in the title bar. Developer-class devices will run models with over 30 billion parameters locally and will come with tools like Windows Terminal and Visual Studio Code pinned to the Taskbar, along with preinstalled applications such as GitHub Copilot and PowerToys. To qualify as a developer-class device, a system must have a minimum of 64 GB of unified memory and at least 250 GB/s memory bandwidth. Initially, these enhancements will be available on AMD's Ryzen AI Halo devices, with plans for broader availability. All Windows 11 devices will benefit from overall improvements, including reduced memory usage and enhanced functionality in Search and File Explorer.
Fake Software Installers Disable Windows Update and Weaken Microsoft Defender
Winsage
September 2, 2026

Fake Software Installers Disable Windows Update and Weaken Microsoft Defender

An active malware campaign is using counterfeit software-download websites to distribute malicious installers, primarily targeting users seeking popular software. This campaign has significantly affected China-based operations of multinational corporations and Chinese-speaking users. The malware, once executed, can establish persistence, undermine security measures, and communicate with attacker-controlled infrastructure. Victims span various sectors, including healthcare, manufacturing, gaming, technology, logistics, government, and education. Microsoft associates this campaign with a Chinese threat cluster called Silver Fox, known for using spoofed vendor download pages to spread Gh0st RAT and ValleyRAT. The malicious websites are hosted on .com.cn and .hl.cn domains, featuring Chinese-language content. The downloaded files are dynamically generated, and upon execution, they deploy a wrapper installer that initiates the malware payload. The malware achieves persistence through scheduled tasks and interferes with Windows Update services. The campaign establishes command-and-control communication over non-standard ports, with two identified domains linked to the activity. Microsoft Defender has detected the threat and initiated containment procedures. Kaspersky reported a related malicious installer exploiting a legitimate adware application to execute a backdoor, which captures keystrokes and clipboard contents. ValleyRAT, a sophisticated implant, can collect system information, reboot the computer, capture screenshots, and transmit logs. The attackers are motivated by cyber espionage and financial gain, targeting organizations globally. A subgroup within GoldenEyeDog, known as CuboidalCanine, has also been linked to the use of ValleyRAT, particularly in the gambling industry. In June 2026, Chinese authorities addressed cybercrime cases involving a new variant of the Silver Fox trojan.
Microsoft shares detailed guide for IT admins on saving massive internet data on Windows 11
Winsage
August 20, 2026

Microsoft shares detailed guide for IT admins on saving massive internet data on Windows 11

Microsoft has released a guide for IT administrators focused on optimizing Windows deployments and reducing bandwidth usage through Windows Delivery Optimization configured via Microsoft Intune. Delivery Optimization uses a peer-to-peer sharing system, allowing devices to download content from each other instead of solely from Microsoft servers, which helps reduce internet strain for organizations with many Windows PCs. Administrators can create specific peer groups based on network topology and control bandwidth usage for downloads, with options to set different limits for business and off-hours. Microsoft also introduced Connected Cache, which stores frequently accessed content locally to further minimize bandwidth consumption. A statistic shared by Microsoft indicates that using Delivery Optimization can significantly reduce internet traffic, as a 1 GB update for 10,000 devices could otherwise generate 10 TB of internet traffic. The guide recommends starting with a small seeder ring of devices to populate peer caches before wider deployment. Microsoft provides specific policy settings for Delivery Optimization, including default and recommended values for settings such as download mode, peer selection, cache size, minimum file size for caching, cache age, and monthly upload data cap. Proper configuration of Delivery Optimization is suggested to benefit organizations managing large numbers of devices.
Migrate Amazon Aurora PostgreSQL across major versions with active Debezium CDC connectors using native logical replication
Tech Optimizer
August 18, 2026

Migrate Amazon Aurora PostgreSQL across major versions with active Debezium CDC connectors using native logical replication

Organizations using Debezium Change Data Capture (CDC) connectors on Amazon Aurora PostgreSQL-Compatible Edition face challenges during major database version upgrades. In-place upgrades require downtime, while blue/green deployments disrupt CDC event pipelines. A method using PostgreSQL's native logical replication allows migration between a source cluster (current version) and a target cluster (new major version) without a full connector re-snapshot. This approach minimizes risks of data loss and allows existing Debezium connectors to operate on the source during synchronization. The cutover process involves disabling the replication subscription, synchronizing sequences, creating a new Debezium replication slot on the target, and redirecting the connector, resulting in a brief pause for Kafka consumers. Prerequisites for this method include enabling logical replication on the source cluster, ensuring the target cluster is provisioned in the same VPC, and confirming that tables participating in CDC have primary keys. The process involves configuring parameter groups, creating publications, and establishing subscriptions for logical replication. During cutover, application writes are halted, and replication lag must be monitored to ensure it reaches zero before proceeding. After the cutover, ongoing monitoring of replication health and Kafka consumer offsets is necessary. Common failure scenarios include Aurora writer failover, Debezium connector stalls, large messages exceeding Kafka limits, DDL changes during synchronization, and long-running transactions blocking lag drain. Each scenario has specific symptoms, detection methods, and resolutions. Post-migration, organizations should establish monitoring for replication lag growth and Kafka consumer offset divergence. Automation can streamline the migration process for organizations managing multiple clusters, utilizing AWS Cloud Development Kit (CDK) constructs for cluster provisioning, schema replication, and cutover orchestration. After verifying stable operation on the target cluster, the old Debezium connector and source cluster can be decommissioned. Limitations include the absence of failover slots on Aurora PostgreSQL 17 and the need to handle TOAST columns appropriately.
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