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CSS Anchor Positioning revolutionizes visual connections between UI elements without JavaScript or extra markup. By Roland.

CSS Anchor Positioning simplifies the process of creating visual relationships between UI elements. By defining an element as an anchor and specifying its geometry elsewhere using the anchor() function, you can create connections that remain intact even as content changes. This technique reduces the need for JavaScript and simplifies markup. In the author’s demo, comment and reply elements are connected visually using only CSS, showcasing the power and flexibility of anchor positioning.

You will learn following:

• The problem
• Enter anchor positioning
• Setting up the anchors
• Drawing the connection
• Reading the code
• Why this is exciting
• Browser support (reality check)
• See it in action

CSS Anchor Positioning is a significant advancement in CSS, enabling more intuitive and flexible visual relationships between UI elements. While browser support is still evolving, this feature deserves early exploration and experimentation. Good read!

Directory Traversal is a common but dangerous vulnerability that can affect applications when file paths are built using untrusted user input, or when file paths are used with unchecked input. Python applications are not immune to directory traversal attacks. By Maikel.

Directory traversal attacks occur when Python applications access files without validating or restricting user-supplied paths. The article emphasizes the severity of this issue, as it can lead to data exposure or remote code execution. To prevent directory traversal, the author recommends validating user input, restricting file access to specific directories, and using secure path handling techniques.

The main points and learnings from the blog post:

• Directory traversal attacks exploit unchecked user input in file paths.
• Python applications should validate user input, restrict file access, and use secure path handling.
• Always create a security design based on a threat model.
• Use a reliable security checklist before using any Python program.
• When developing Python applications, follow secure programming principles and validate code using trusted tools.
• The pathlib module provides robust path resolution and verification.
• Consider eliminating directory traversal possibilities by stripping path components from user input.

The provided vulnerable code example shows a function that concatenates user-controlled input into a filesystem path without validation. The secure mitigation uses the pathlib module to resolve the path, ensuring it remains within the intended base directory and raising a ValueError if it attempts to traverse outside that boundary. The article also suggests eliminating directory traversal possibilities by stripping all path components from user input if feasible. It concludes by encouraging readers to take control of their application security risk by using tools like Python Code Audit. Nice one!

The Temporal API is a modern replacement for JavaScript’s Date object, offering better date/time handling (time zones, calendars). Chrome/Edge 144 and Firefox now support it natively. By Alexander Lehner.

The Temporal API, now natively supported in major browsers (Chrome, Edge, Firefox), offers a robust alternative to the legacy Date object, with built-in time zone and calendar support. However, since Temporal is still a TC39 Stage 3 proposal, TypeScript lacks native type definitions, causing errors like "Cannot find name ‘Temporal’" in Angular projects. This article details a three-step approach to resolve this:

1. Install the polyfill as a dev dependency — only for type access, not runtime code.
2. Declare a global Temporal type - by importing types from the polyfill and assigning them to a global constant. This tricks TypeScript into recognizing the native browser API.
3. Use types explicitly - for variables/interfaces via TemporalType imports, ensuring full type safety.

The solution avoids bundling the polyfill’s 150 kB runtime code, relying instead on native browser implementations. A demo app demonstrates practical use cases like time zone pickers and date arithmetic. Challenges include ensuring browser support (Safari lagging) and managing type imports cleanly. This method is ideal for new Angular projects targeting modern browsers. Good tutorial!

Discover how CockroachDB Serverless achieves sub-second scaling from zero using multi-region cluster virtualization, balancing performance and cost for multi-tenant environments. By Murat.

This informative piece reads about:

• CockroachDB Serverless uses logical disaggregation to achieve sub-second scaling.
• The architecture splits the database into SQL and KV processes, with a shared, multi-tenant KV layer.
• LSM trees enable efficient multi-tenancy in the KV layer.
• The design prioritizes cost-effectiveness and elasticity for small customers.
• Trade-offs include increased RPC overhead and higher caching costs.
• Admission control mechanisms manage resource contention and ensure fairness.

It is a comprehensive overview of CockroachDB Serverless’ innovative architecture, highlighting its strengths in rapid scaling and cost-effectiveness for multi-tenant environments. While it acknowledges the trade-offs, such as increased RPC overhead and caching costs, the sophisticated admission control mechanisms demonstrate a practical approach to managing resource contention. This makes it a significant contribution to the field of serverless databases, offering a viable solution for small customers seeking elasticity and low costs. Good read!

This comprehensive article explores the intersection of machine learning and physics, proposing novel models and architectures that incorporate physical laws and geometric principles for more efficient, transparent, and robust AI systems. By Hyperbole.

Blog post reads about:

• PIML integrates physical knowledge and geometric principles into ML models
• By incorporating physical laws and symmetries, PIML can create more efficient, transparent, and robust AI systems
• The article covers various models and architectures, including Kuramoto models, directional statistics, and deep learning on non-Euclidean spaces
• PIML has potential applications in supervised learning, reinforcement learning, unsupervised learning, and latent space modeling
• Practical examples demonstrate the effectiveness of PIML in solving real-world problems

A novel approach is described that integrates physical knowledge and geometric principles. The proposed models and architectures have the potential to create more efficient, transparent, and robust AI systems that are better suited for a wide range of applications. While the concepts presented are advanced and require a strong background in mathematics and physics, the practical examples demonstrate the real-world relevance of these ideas. Nice one!

AWS details its response to recent npm supply chain attacks, emphasizing proactive detection, rapid response, and collaborative threat intelligence sharing. By Nikki Pahliney, Chi Tran, Albin Vattakattu, Charlie Bacon, Dan Dutrow, David Magnotti, Jeff Laskowski, Stephen Goodman, and Ryan Tick.

The article touches these topics:

• AWS demonstrates a rapid, systematic approach to npm supply chain incident response.
• Generative AI is being utilized for malware analysis and indicator expansion.
• Collaboration with the Open Source Security Foundation (OpenSSF) is critical.
• Continuous monitoring and anomaly detection are key to early threat identification.
• Layered security controls (scanning, monitoring, credential management) are essential.
• Maintaining an inventory of open-source dependencies is a vital preventative measure.
• These attacks often focus on credential harvesting and unauthorized access.

This article provides valuable insights into a real-world, large-scale response to a significant security challenge. While supply chain attacks aren’t new, the frequency and scale described represent an escalation, and AWS’s detailed response offers a practical blueprint for organizations to improve their own security posture. Interesting read!

The FDAP stack – Flight, DataFusion, Arrow, and Parquet – represents a significant shift in database development, prioritizing modularity and leveraging existing open-source technologies for modern analytic systems. By gotopia.tech.

The main points:

• The FDAP stack (Flight, DataFusion, Arrow, Parquet) is a modular approach to building databases.
• Columnar storage with Apache Arrow optimizes data processing for analytics.
• Parquet provides efficient columnar storage and compression for large datasets.
• Apache DataFusion offers an optimized SQL query engine.
• The trend toward disaggregated databases (S3 as the primary storage) is a key architectural shift.
• Iceberg represents a future vision of unified data access across diverse systems.

This blog post represents a valuable overview of the emerging trends in database development, particularly for developers working with modern analytic workloads. While the concepts are complex, the clear explanations and practical examples make it accessible. The shift towards modularity and leveraging open-source technologies is a significant advancement, though its ultimate impact will depend on broader adoption and continued innovation within the ecosystem – it’s more of an incremental step than a revolutionary one. Good read!

JavaScript ES2026 delivers significant JavaScript improvements, addressing longstanding issues with dates, math precision, resource management, and module loading. By Mary Branscombe.

ES2026 is poised to be a significant release for JavaScript, addressing several long-standing developer pain points. The headline feature is the Temporal API, a comprehensive replacement for JavaScript’s notoriously problematic Date object that simplifies date/time handling with built-in timezone and calendar support.

The main sections of the blog post:

• ES2026 solves JavaScript headaches with dates, math and modules
• What’s already approved for ECMAScript 2026?
• Improving internationalization and localization
• Finalizing asynchronous code and resource management
• The long-awaited temporal API: A fix for JavaScript’s Date Object
• Optimizing performance with deferred module imports

Other significant additions include Math.sumPrecise for more accurate floating-point arithmetic, Array.fromAsync for handling asynchronous iterables, and Explicit Resource Management that provides deterministic cleanup of resources using using blocks. The language also gains better internationalization support through Intl Locale improvements, Iterator.concat for chaining sequences, and import defer for optimizing startup performance in large applications. These features, many of which are already implemented in browsers, represent substantial improvements to JavaScript’s core functionality and developer experience. Nice one!

This guide provides a deep technical comparison of AWS, GCP, and Azure load balancers, detailing their L4/L7 architectures, performance characteristics, and optimal use cases. Learn to select the right service for microservices, global applications, and high-throughput workloads, with a special focus on protocols like GENEVE and flow hashing. By Piyush Jajoo.

The author’ focus is on:

Key Points:

• AWS offers the most diverse portfolio, with the NLB providing the lowest latency and the GWLB enabling unique security appliance insertion via GENEVE encapsulation.
• GCP excels in true global load balancing with anycast IPs, leveraging its private backbone and Maglev for high-performance, globally distributed applications.
• Azure provides a balanced mix, with Azure Front Door standing out as a powerful global service that integrates CDN, WAF, and load balancing into one offering.
• Layer 7 (Application) balancers are ideal for HTTP/HTTPS traffic, offering content-based routing (path/host), SSL termination, and WAF integration.
• Layer 4 (Transport) balancers are chosen for extreme performance (sub-millisecond latency), non-HTTP protocols (TCP/UDP), and when preserving the client’s source IP is critical.
• The Flow Hash Algorithm is the stateless engine behind L4 load balancing, ensuring all packets of a connection reach the same backend using a 5-tuple hash; consistent hashing minimizes flow remapping during scaling.
• GENEVE is a modern tunneling protocol used by AWS GWLB to encapsulate traffic, allowing security appliances to inspect packets transparently without breaking the original network context.
• Choosing the right load balancer involves matching the OSI layer to your traffic, evaluating global vs. regional needs, and considering integrated features like WAF and CDN.

This is an exceptionally valuable resource, consolidating complex, provider-specific documentation into a clear, comparative framework. It offers significant practical guidance for architects, enabling informed decisions that balance performance, cost, and feature sets. The deep dives into underlying protocols like GENEVE and flow hashing elevate it beyond a simple feature list, making it a definitive reference for cloud load balancing. Good read!

Stream Azure Security Center alerts and recommendations to Azure Monitor for enhanced visibility, custom dashboards, and automated responses to security events. By Charbel Nemnom.

Interesting points discussed:

• Setting up continuous export to Azure Monitor
• Configure Azure Monitor alerts rules (default)
• View alerts in Azure Monitor
• Configure Azure Monitor alerts rules (update)
• Verify Azure Monitor alerts rules

Author focuses on leveraging Azure Security Center’s continuous export feature to send security alerts and recommendations to Azure Monitor. This moves past the standard Azure Security Center dashboard, allowing for more advanced analysis and automation. The process involves enabling continuous export to a Log Analytics workspace, selecting the data types and severity levels to export, and then utilizing Azure Monitor’s built-in capabilities to create alert rules. These rules can be customized to trigger actions based on specific security events. The article provides step-by-step instructions, including creating custom queries to view exported data and configuring action groups for automated responses (e.g., email notifications). This significantly enhances security monitoring and response capabilities within Azure environments.

This article provides a clear and practical guide to a valuable integration. While the concept of exporting security data isn’t new, streamlining the process and providing automated rule creation within Azure Monitor represents a significant usability improvement. This integration empowers DevOps and security teams to leverage the power of Azure Monitor for more sophisticated security monitoring and incident response, solidifying Microsoft’s commitment to cloud security automation. Good read!