Total Articles: 17 from 7 sources
AWS News
1. Amazon SQS turns 20: Two decades of reliable messaging at scale
URL: https://aws.amazon.com/blogs/aws/amazon-sqs-turns-20-two-decades-of-reliable-messaging-at-scale/
Published: 2026-07-13 18:13
Summary:
On July 13, 2006, we launched Amazon Simple Queue Service (Amazon SQS) as one of the first three services available to customers, alongside Amazon EC2 and Amazon S3 We had learned firsthand that distributed systems need a reliable way to pass messages between components without creating tight dependencies If one service called another directly and […]
2. AWS Weekly Roundup: AWS Builder Center at 1 year, Network Scanning in Security Hub, Loom for AWS, and more (July 13, 2026)
Published: 2026-07-13 16:18
Summary:
AWS Builder Center turned one year old last week Launched on July 9, 2025, the platform has grown from a community hub with Wishlist voting, community profiles, and a toolbox into a full ecosystem with sandbox environments, workshops, Spaces, and a Builders’ Library To mark the anniversary, Rick Suttles published a full feature timeline covering […]
3. AWS Weekly Roundup: Claude Sonnet 5 on AWS, Amazon WorkSpaces for AI agents, AWS service availability updates, and more (July 6, 2026)
Published: 2026-07-06 15:46
Summary:
A couple of editions ago I wrote about what I find so energizing about working with startups Last week I got a fresh dose of it: I spent a few days with the AWS Startups team, listening to stories of founders talking about the problems they’re actually solving One story that stayed with me came […]
Dropbox Engineering
1. How we used DSPy to turn AI evaluations into better responses in Dash chat
Published: 2026-06-25 16:30
Summary:
We used DSPy to improve LLM judges and optimize our chat experience, creating an evaluation-driven feedback loop that produced better outputs.
GitHub Blog
1. The cost of saying yes has changed
URL: https://github.blog/engineering/the-cost-of-saying-yes-has-changed/
Published: 2026-07-17 16:46
Summary:
The cost of writing code dropped; the cost of owning it didn’t A framework for deciding which changes are actually cheap in the AI era The post The cost of saying yes has changed appeared first on The GitHub Blog.
2. GitHub for Beginners: Your roadmap to mastering the GitHub essentials
Published: 2026-07-15 17:29
Summary:
This beginner’s guide explains version control, repositories, and pull requests—plus everything else you need to start working confidently on GitHub The post GitHub for Beginners: Your roadmap to mastering the GitHub essentials appeared first on The GitHub Blog.
3. Better tools made Copilot code review worse. Here’s how we actually improved it.
Published: 2026-07-10 15:57
Summary:
How migrating Copilot code review to shared Unix-style code exploration tools reduced review cost by reshaping agent workflows around pull request evidence The post Better tools made Copilot code review worse Here’s how we actually improved it. appeared first on The GitHub Blog.
Google Developers
1. DiffusionGemma: The Developer Guide
URL: https://developers.googleblog.com/diffusiongemma-the-developer-guide/
Published: 2026-07-19 10:24
Summary:
DiffusionGemma is an experimental text-generation model built on the Gemma 4 architecture that uses diffusion-based parallel generation instead of token-by-token autoregression, enabling much faster inference, bidirectional context awareness, and real-time self-correction while remaining deployable on consumer GPUs Its architecture generates and refines 256-token blocks in parallel through iterative denoising, allowing it to handle complex constraint-based tasks such as Sudoku more effectively than traditional language models and demonstrating strong gains from fine-tuning The model integrates with vLLM and other popular inference frameworks, giving developers access to a new non-autoregressive approach that combines high performance, efficient long-context scaling, and straightforward customization and deployment.
2. Enhance Security and Trust: New Session Metadata in Sign in with Google
Published: 2026-07-19 10:24
Summary:
Google is enhancing Sign in with Google by introducing new OIDC standard claims—specifically auth_time and amr (Authentication Methods Reference) to provide developers with deeper session metadata These updates allow verified apps to verify the “freshness” of a user’s login and the specific authentication methods used (such as MFA or hardware keys), enabling more dynamic, risk-based access controls By leveraging these federated identity signals, platforms can better prevent account takeover and fraud while implementing granular security policies like step-up authentication for sensitive actions.
3. Unlocking the Power of the TPU Stack: Introducing our new Developer Hub
Published: 2026-07-19 10:24
Summary:
Google has officially launched the TPU Developer Hub, a centralized educational resource designed to help model builders and developers maximize the performance of Google Cloud TPUs The hub offers code-first resources, open-source recipes, and deep-dive documentation covering hardware architecture, software optimization, debugging, parallelism, and networking These materials are tailored for both human developers and AI-assisted tools to streamline everything from large-scale training to low-latency inference workloads.
Meta Engineering
1. Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization
Published: 2026-07-15 17:00
Summary:
Hierarchical Interest Representation is a research area for Meta Ads The innovations in Hierarchical Interest Representation are […] Read More The post Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization appeared first on Engineering at Meta.
2. Modernizing the Meta Ads Service With an Open-Source Kernel Scheduler
Published: 2026-07-13 16:00
Summary:
TL; DR At Meta’s scale, a few milliseconds of latency degradation can have a significant negative impact on ads performance When a Linux kernel upgrade risked regressing latency across Meta’s ad serving fleet, we turned to sched_ext — the upstream, BPF-based extensible scheduling framework — to build a scheduling policy customized to the Ads delivery […] Read More The post Modernizing the Meta Ads Service With an Open-Source Kernel Scheduler appeared first on Engineering at Meta.
3. Meta’s AI Storage Blueprint at Scale
URL: https://engineering.fb.com/2026/07/01/data-infrastructure/metas-ai-storage-blueprint-at-scale/
Published: 2026-07-01 16:00
Summary:
During the past year or so, the time between new-frontier-model releases has gone down from months to weeks Reliable and fast access to storage is important to both the speed and computational cost of this AI innovation The post Meta’s AI Storage Blueprint at Scale appeared first on Engineering at Meta.
Netflix TechBlog
1. In-House LLM Serving at Netflix
Published: 2026-07-17 21:32
Summary:
Serving Architecture OverviewDesign Decisions and ImplementationFour decisions shape this platform — engine, packaging, API surface, and rollout — presented in dependency order, since each one constrains the next.vLLM as the Paved-Path EngineThe platform was originally built on TensorRT-LLM, a performant inference engine at the time and already integrated with Triton — the compute backend in use within MSS.By summer 2025, two things had shifted: open-source engines had largely closed the performance gap with specialized stacks, and our workload mix had broadened to include embedding generation, prefill-only inference for ranking and retrieval, autoregressive decoding, and custom models with non-trivial per-step constraint logic The platform has to pin compatible versions when baking the service image, and prevent model authors from overriding the vLLM version at packaging time.Custom model logic We git-subtreed and patched the frontend to translate response_format into vLLM’s guided decoding parameters at request time.Deployment StrategiesWith API surface and engine in place, the question that remains is how new versions roll out without dropping requests
2. Building Service Topology at Scale: Architecture, Challenges, and Lessons Learned
Published: 2026-07-13 22:44
Summary:
Instead of batch jobs that process historical data, we continuously ingest flow records from multi-region Kafka streams and IPC metrics as Server-Sent Events, process them through reactive pipelines with backpressure handling, and provide near real-time topology updates, typically within tens of minutes, compared to the hours-old or day-old data that batch processing approaches provide.This wasn’t just about freshness, it was essential for our use cases When data arrives with the right partitioning, you can aggregate directly; when it doesn’t (like network flows requiring intermediary resolution), you need shuffle/redistribution stages.Dynamic Load Distribution: How Hashing Works with Auto-ScalingHow do we decide which instance receives which aggregator when our Auto Scaling Groups dynamically add or remove instances GC logs showed pauses consuming significant CPU time, in some cases, more than our business logic.Root Cause: Multiple factors contributed: objects accumulating in heap while waiting for 5-minute aggregation windows to complete, unnecessary conversions between different object types as data flowed through stages, and immutability overhead, following Scala best practices, we used immutable data structures for aggregators, but every update created new objects, overwhelming the garbage collector at millions of records per second.Investigation: Heap dumps and GC logs revealed flow log objects retained beyond their useful lifetime, unnecessary intermediate conversion objects, and constant creation/disposal of immutable aggregator versions
3. GenPage: Towards End-to-End Generative Homepage Construction at Netflix
Published: 2026-06-29 13:01
Summary:
This sequence includes the full structured homepage layout, with multiple rows and the entities inside them, so the model can generate the page holistically rather than scoring each row or entity in isolation.Figure 2 At a high level, WBC turns generation into token-level value prediction: given the user context and the tokens generated so far, the model learns to estimate the value of generating each possible next row or entity token.This objective is easier to optimize than page-level RL WBC post-training loss as we progressively enrich the user context tokens
Stripe Engineering
1. Four travel and hospitality trends from HITEC 2026
URL: https://stripe.com/blog/trends-from-hitec
Published: 2026-06-23 00:00
Summary:
More than 6,000 hospitality executives and operators gathered in San Antonio last week for the HITEC conference The big topic: whether the industry’s AI investment is actually working Across four days and over 50 meetings, four trends stood out.
Generated on 2026-07-19 10:24:54