data processing Archives

Winsage

August 6, 2026

Windows 11 could soon get significantly faster with Microsoft’s new performance tools

Microsoft has introduced a preview of the Event Tracing for Windows Model Context Protocol (ETW MCP) to enhance Windows performance analysis. This server integrates artificial intelligence to streamline the analysis of Windows Event Tracing (ETW) logs. The ETW MCP allows developers to use tools like GitHub Copilot to examine Event Trace Log (ETL) files, answer queries about the logs, and identify performance issues without manual data sifting. The MCP provides structured, read-only access to processed trace information, enabling developers to query insights such as CPU usage and execution paths. Current features of the ETW MCP include trace processing, querying, multi-trace comparison, symbol-aware analysis, critical path analysis, and regions of interest. The ETW MCP is designed for headless environments and automation, while a forthcoming WPA MCP will provide similar AI-assisted analysis within a graphical interface. The ETW MCP preview is available as the Microsoft.Windows.EventTracing.MCP NuGet package, and Microsoft is seeking developer feedback for further enhancements.

AppWizard

August 5, 2026

Developers: Beware of Ad Libraries that Betray Your Users’ Location

Advertising companies provide software development kits (SDKs) for mobile app monetization, which often automatically transmit users' location data to ad systems and location data brokers, raising privacy concerns. Many developers and users may be unaware of this data sharing. When developers allow SDKs to collect location data, it poses risks beyond targeted ads, including potential misuse by agencies like ICE and global surveillance. Location data brokers harvest precise movements of individuals, often without their consent, through mobile applications. Some apps directly collaborate with data brokers, while others leak data through advertising SDKs during real-time bidding (RTB) auctions. An incident in 2025 revealed that many apps unknowingly contributed to a location data broker's database. Developers must understand their SDKs' location-sharing practices to mitigate risks. Advertising SDKs can collect location data automatically once users grant permission, without specific permissions for the SDKs themselves. Precise location data can be collected when apps have location permissions, leading to potential privacy violations. Several SDKs have been identified as collecting location data by default, increasing the risk of unintentional data leaks. The Electronic Frontier Foundation (EFF) found that four advertising SDKs collect users' location data by default when location permissions are granted. InMobi encourages location sharing for higher revenue, while BidMachine updated its documentation after EFF's inquiry, confirming precise location data collection. Verve's SDK also collects location data by default but presents a cautious narrative in its Play Store guidance. Huawei's SDK recommends obtaining location permissions to enhance revenue, with default location sharing occurring if permissions are granted. Location data can be shared without users' knowledge or meaningful consent, complicating informed consent issues. The focus on four SDKs does not imply that others adequately protect location data, as many have faced criticism for similar practices. Studies indicate that SDKs often encourage increased data collection through design and documentation, leading to minimal control for developers over data transmission. The EFF's analysis highlights that advertising SDKs incentivize location data sharing through default settings and unclear documentation. Developers should assess third-party SDKs and disable unnecessary data collection. Regulators must hold developers accountable for unlawful data sharing, while legislators should enact laws to protect location privacy and address online behavioral advertising, which drives data tracking.

AppWizard

July 24, 2026

Ultrahuman’s new ‘Emerald’ update is a massive overhaul of how the app works

Ultrahuman has released the "Emerald" update for its companion app, featuring a new design and enhanced user experience for Ultrahuman Ring PRO and other devices. The update introduces the "UltraSphere," a decision-making engine that provides personalized "Next Best Actions" based on factors like location, weather, and circadian rhythms. It utilizes health metrics such as heart rate variability, skin temperature, and movement patterns, and can incorporate blood glucose levels for users with Ultrahuman M1 or M2 Live devices. The update also includes new tabs for health insights, such as the "Sleep Screener," which consolidates sleep data, and the "Longevity Tab," which aggregates health markers related to lifespan. The "Windows" feature offers insights into time-sensitive data. Workout tracking has been improved with better automatic detection and heart rate algorithms, increasing VO2 Max accuracy by 21%. Users can connect third-party devices for seamless workout tracking. All health data processing now occurs on-device, allowing access to insights without network connectivity. The Emerald update is being rolled out globally and is available on the Google Play Store and Apple App Store.

Tech Optimizer

July 21, 2026

I Built My Second ETL Pipeline. This Time, I Started Thinking Like a Data Engineer

The author transitioned from a data analyst role to a data engineer, creating a 12-month self-study roadmap focused on learning by building projects. The first project was a GitHub ETL pipeline, which evolved from a simple Python script to a more complex system using SQLite and GitHub Actions for automation. The author realized that the challenges of data engineering lay in system design and orchestration rather than just writing ETL logic. For the second project, the author built an automated RSS ingestion pipeline to explore engineering decisions in creating a reliable data pipeline. The project emphasized the importance of separating application responsibilities from orchestration tasks, leading to the use of Docker for consistent execution environments and Kestra for orchestration. The author validated each component of the project incrementally: first the Python ETL, then PostgreSQL, followed by Docker, and finally Kestra. This approach ensured that each layer functioned correctly before adding complexity. The final architecture included distinct responsibilities for each component: Python for data processing, PostgreSQL for data storage, Docker for execution, and Kestra for orchestration. The author learned that effective engineering involves considering system reliability, error handling, and observability, shifting the focus from merely writing code to designing entire systems. The experience transformed the author's mindset, emphasizing the importance of incremental building and the separation of execution and orchestration responsibilities.

Tech Optimizer

July 12, 2026

What Is Serverless PostgreSQL?

Serverless PostgreSQL is a fully managed cloud database model that separates compute and storage, allowing them to scale independently and automatically based on demand. It eliminates the need for manual infrastructure provisioning and capacity planning, charging only for active usage. Unlike traditional PostgreSQL setups, which require continuous resource allocation and manual scaling, serverless PostgreSQL provisions resources on demand and can scale down to zero during idle periods. Serverless PostgreSQL integrates with serverless compute platforms, enabling analytical queries to access the same data within a unified architecture. Key differences between traditional and serverless PostgreSQL include manual versus automatic provisioning and scaling, fixed versus usage-based billing, and high versus reduced operational overhead. Lakebase architecture is an emerging model that combines transactional databases with lakehouse foundations, allowing operational and analytical workloads to coexist on a single platform. This architecture minimizes data duplication and simplifies access, enhancing data management and analysis. Serverless PostgreSQL operates on a cloud-native architecture that enhances efficiency by allowing compute and storage to scale autonomously. It features scale-to-zero behavior, where compute resources are suspended when inactive and reactivated upon new queries. Major providers include Databricks Lakebase, Amazon Aurora Serverless v2, and Neon, each offering varying capabilities and integrations. Pricing for serverless PostgreSQL typically includes charges for compute resources, storage, and data transfer, with costs fluctuating based on workload activity. Cold start latency is a performance consideration, as reactivating compute resources can introduce delays. Strategies to mitigate this include keeping resources partially active or selecting providers with minimal cold start impacts. Serverless PostgreSQL is well-suited for OLTP workloads, while lakebase architecture is better for AI development, variable workloads, and environments requiring rapid iteration. Setting up serverless PostgreSQL involves choosing a provider, creating a database instance, and configuring access settings. It can also be used alongside serverless compute platforms for analytics, further extending its capabilities.

Tech Optimizer

July 11, 2026

Microsoft closes RoguePlanet vulnerability in Defender: SYSTEM privileges via the antivirus engine

A vulnerability known as RoguePlanet was identified in Microsoft Defender, tracked as CVE-2026-50656. This flaw allows local privilege escalation to the NT AUTHORITYSYSTEM account, requiring an attacker to have local code execution capabilities. It can be exploited through methods such as opening malicious email attachments. The vulnerability is categorized under CWE-59: “Improper Link Resolution Before File Access” and involves a race condition that affects the Defender engine's operations. RoguePlanet was disclosed by security researcher Nightmare-Eclipse on June 10, 2026, and confirmed by various security firms. Microsoft released a fix in version 1.1.26060.3008 of the Microsoft Malware Protection Engine, which should be installed automatically in standard Windows configurations. Users can verify their engine version using PowerShell. The vulnerability affects both Windows 10 and Windows 11 systems with the June 2026 security updates, and disabling real-time protection does not reliably mitigate it.

Tech Optimizer

July 6, 2026

MacPaw Moonlock antivirus review

MacPaw launched Moonlock as a standalone antivirus application in October 2025, building on its existing malware removal module from CleanMyMac. Moonlock focuses on educating users about malware rather than overwhelming them with technical details, following a 'care, not scare' philosophy. Research indicated that 66% of Mac users faced cyber threats last year, with a 67% increase in macOS backdoor variants in 2025. Moonlock Lab has identified new malware variants and maintains a strict zero-logs policy for its VPN. The application requires macOS 13 or later and 515MB of disk space, operates efficiently without significant performance impact, and necessitates a MacPaw account for installation. Support includes a knowledge base and email inquiries, but lacks live chat or phone options. Moonlock competes with ClamXAV, which is cheaper but lacks some features, and Intego Mac Internet Security X9, which offers a network monitor. Moonlock is priced at .95 per year for a single device, nearly double ClamXAV’s price for three devices, but includes additional features like a VPN and network inspection. It also provides a 30-day money-back guarantee.

Tech Optimizer

June 24, 2026

EDB converges analytics on Postgres to support AI agents

EDB's per-core pricing model offers predictable costs compared to consumption-based cloud data platforms, aiding organizations in budgeting. However, predictable billing does not guarantee lower costs, as high-speed operational data processing requires more expensive hardware than lakehouse storage solutions. EDB's architecture, built on a unified Postgres-Iceberg foundation, streamlines data governance by reducing the need for multiple specialized data stores, leading to fewer platforms to manage and enhancing operational efficiency and data governance protocols.

Tech Optimizer

June 23, 2026

Millisecond Latency at Scale: Why Our ML Feature Store Runs on Snowflake Postgres

Organizations are consolidating their fragmented database environments with Snowflake Postgres, phasing out outdated systems and simplifying multivendor setups without extensive code rewrites. Ericsson migrated four legacy databases to Snowflake Postgres, achieving a 99% reduction in data processing time. SimCorp's transition to Snowflake Postgres resulted in a tenfold increase in disk operation speeds. Sigma Computing provides real-time analytics using Snowflake Postgres, eliminating the need for external systems. BlueCloud supports low-latency transactional workloads and analytics on a single platform. Superblocks enables developers to create full-stack applications using Snowflake CoCo, leveraging SQL tools against live data. Snowflake Postgres is approximately four times faster than Databricks Lakebase and has a 99.95% published uptime SLA. It operates on Postgres 18 and accommodates up to 64 TB of storage, surpassing Lakebase's 16 TB limit. Snowflake Postgres simplifies management with in-place major version upgrades and supports standard logical replication, enhancing flexibility for data movement and integration.

AppWizard

June 19, 2026

Pixel Screenshots just moved away from using on-device AI only, but is it less private?

The Pixel Screenshots app has transitioned from relying solely on on-device AI to a hybrid model that incorporates cloud processing. The latest update, version 1.26.134.11, reflects this change by revising the app's settings to indicate that AI processing may occur on-device or in the cloud. Google emphasizes that user privacy will be prioritized, utilizing a “secure, isolated environment” for processing. The update is currently rolling out and may not yet be available to all users in the Play Store.