recovery

Winsage
October 14, 2026
Microsoft has released its monthly quality updates for all supported versions of Windows 11 on the second Tuesday of October. This update marks the first Patch Tuesday update for Windows 11 version 26H2 and the end of support for version 24H2. Cumulative update KB5127648 is available for Windows 11 versions 24H2, 25H2, and 26H2, upgrading them to builds 26100.9711, 26200.9711, or 26300.9711. Key features include enhancements to File Explorer, support for Emoji 17.0, a new Tips widget, personalization improvements, an Accessibility setting for maximizing apps, precision touchpad functionality improvements, enhanced configuration options for the Copilot key, upgrades to the Windows Recovery Environment, and changes to Windows Backup. Windows 11 version 26H1 will receive cumulative update KB5127646, advancing it to build 28000.3231. This update features a redesigned Taskbar, a revamped Start menu, a new Windows Search experience, performance improvements in File Explorer, modernized progress indicators, Administrator Protection, and enhancements to the Get Started app.
Winsage
October 12, 2026
Windows 11 version 24H2 for Home and Pro systems will stop receiving security updates on October 13, 2026. After this date, these editions will not receive any updates or technical support, although they will still boot. Windows 11 Enterprise, Education, IoT Enterprise, and Enterprise multi-session editions will continue to receive support until October 12, 2027. Organizations are advised to verify their systems' versions and editions, especially for those without endpoint management systems. Windows 11 25H2 and 26H2 are available as upgrade options, with 25H2 supported until October 12, 2027, and 26H2 supported until October 10, 2028, for Home and Pro editions. The rollout of 26H2 will be phased, and safeguard holds may be implemented if compatibility issues are detected. Unmanaged Home and Pro devices on 24H2 will automatically receive 25H2, while managed devices may require IT intervention. Regular monitoring and proactive management of Windows versions are necessary to ensure compliance and avoid future deadlines.
AppWizard
October 12, 2026
On the evening of October 9, users attempting to access ChatGPT on Android devices encountered the message "This content is unavailable in this version of the app" due to an issue from OpenAI. The problem began at 21:00:39Z and lasted for three hours and 26 minutes, concluding at 00:26:44Z on October 10. OpenAI advised users to switch to the web version while they worked on a fix for older app versions. A second major incident occurred 48 minutes later, locking workspace administrators out of plugin settings from 21:48:34Z to 23:26:59Z on October 9, totaling one hour and 38 minutes. Both incidents overlapped entirely, with the Android issue persisting for an additional hour after the admin issue was resolved. As of 21:42 UTC on October 10, a third minor incident regarding "Delayed Costs data in the Compliance API" remained unresolved, having started at 17:23:18Z on October 9. OpenAI reported that some customers might experience incomplete Costs data while the backlog was addressed, with the catch-up process expected to continue through October 11. ChatGPT usage and API Platform requests were unaffected, and the overall status was designated as "Partial System Degradation." Additionally, a more significant outage occurred on September 29, lasting five hours and 22 minutes and affecting 30 components, which was more extensive than the incidents on October 9. Neither of the major incidents on October 9 impacted the API.
Tech Optimizer
October 11, 2026
Lakebase is a fully managed Postgres database designed for modern application development, featuring an architecture that separates storage and compute with a serverless compute layer. This design allows for cost efficiencies through various mechanisms: 1. **Branching**: Developers can create isolated environments for development, testing, or experimentation without duplicating storage costs, as branches share the same underlying storage. 2. **Autoscaling**: Lakebase adjusts compute resources based on activity levels, allowing users to pay only for the compute they use. It can scale down during low activity and can be suspended entirely after inactivity, reducing costs to zero. 3. **Read Replicas and High Availability**: The separation of storage and compute allows for adding read replicas and high availability without incurring additional storage costs, as these instances utilize the same storage layer. 4. **Synced Tables**: Integration with the Databricks Intelligence Platform enables efficient data syncing, allowing users to sync only the necessary working set of data, which helps avoid unnecessary storage and sync costs. 5. **Sync Modes**: There are three sync modes (Snapshot, Triggered, Continuous) for transferring data from the Lakehouse to Lakebase, each with different cost implications based on data freshness requirements. 6. **Right-sizing Compute**: Users can set the initial compute range during project provisioning to avoid over-provisioning and unnecessary costs. 7. **Monitoring and Metrics**: The Lakebase Metrics dashboard provides insights into working set size and cache utilization, helping users optimize their compute sizing and performance. 8. **Point-in-Time Restore (PITR) and Snapshots**: PITR maintains history for recovery within a configurable window, while snapshots offer discrete recovery points. Both are priced lower than standard storage, making them cost-effective options for data recovery. Lakebase costs are categorized into compute, storage, and serverless pipeline compute for syncing data. Compute is measured by CU usage, while storage includes branch storage, PITR history, and snapshot storage, all tracked separately. Users can access detailed usage and cost information through system billing tables.
Tech Optimizer
October 10, 2026
The Nebius Managed PostgreSQL team developed a solution for AI workloads using CloudNativePG and Kubernetes, resulting in improved backup and restore times by transitioning from Barman to WAL-G, reducing a 1.5 TB backup duration from over a day to two hours. Since its launch in 2025, the service supports hundreds of production clusters and manages tens of tebibytes of data. Key features include high availability, point-in-time recovery, automated failover, compressed and encrypted backups, rapid restoration, connection pooling, and strict synchronous replication for zero data loss. Kubernetes and CloudNativePG were chosen for their advantages, including out-of-the-box features and open-source distribution. Each cloud project has a separate MK8s cluster for customer isolation and security. Persistent data is stored on fault-tolerant SSD drives, enabling swift instance migration during failures. Regular physical backups are archived, allowing restoration within a seven-day window with a single click. The transition from Barman to WAL-G addressed slow backup and restoration times and resource control limitations. With WAL-G, backups and restorations for a 1.5 TB cluster improved to two hours and one hour, respectively. PgBouncer was implemented to manage database connections effectively, reducing connection storms during peak AI workload traffic. Two vector search extensions, pgvector and pgvectorscale, are available to cater to different memory and dataset needs. Benchmarking showed that Nebius performs competitively with AWS at a lower cost. The infrastructure integrates cloud engineering principles with specialized expertise to meet AI workload demands.
Tech Optimizer
October 10, 2026
In April 2026, Telangana's MeeSeva platform migrated from the Oracle database to the open-source PostgreSQL database after 15 years of reliance on Oracle. This transition aimed to reduce annual costs of approximately ₹10 crore associated with Oracle licensing and maintenance. The initiative began in 2023, and the migration was executed with less than four hours of downtime, processing around 80,000 transactions daily. The migration involved over 85 microservices, three Oracle servers, and 1,939 tables, with the process automated by the Ora2Pg tool, which handled 60-70% of the transition. The migration cost was below ₹10 lakh, and after the switch, MeeSeva processed nearly 200 million transactions without data loss. The new architecture includes automatic failover capabilities to minimize disruption.
Search