The hottest Cloud Computing Substack posts right now

And their main takeaways
Category
Top Technology Topics

The Tech Buffet #21: Deploy A Production-Ready Streamlit App with Cloud Run and Cloud Build

The Tech Buffet • 99 implied HN points • 22 Mar 24
🕹 Technology Cloud Computing
  1. Cloud Run lets you deploy containerized applications without worrying about server management. You only pay when your code is actively running, making it a cost-effective option.
  2. Using Pulumi as an Infrastructure as Code tool simplifies the process of setting up and managing cloud resources. It allows you to deploy applications by writing code instead of manually configuring settings.
  3. Automating your deployment with Cloud Build ensures your app updates easily whenever you make code changes. This saves time and effort compared to manually deploying each time.

I spent 6 hours understanding the design principles of BigQuery. Here's what I found

VuTrinh. • 159 implied HN points • 20 Jan 24
🕹 Technology Cloud Computing
  1. BigQuery uses SQL again after moving away from it, making data analysis fast and easy. Users can now analyze huge datasets quickly without complex coding.
  2. It separates storage and compute resources, allowing for better performance and flexibility. This means you can scale them independently, which is very efficient.
  3. Dremel's serverless architecture means you don’t need to manage servers. You just use SQL, and everything else is automatically handled for you.

The Sequence AI of the Week #773: The Week Google Turned Gemini Into an Agent Runtime

TheSequence • 28 implied HN points • 17 Dec 25
🕹 Technology Cloud Computing
  1. Google moved from just releasing models to shipping an agent runtime that coordinates and runs agents, making Gemini a platform for agent workflows.
  2. The Interactions API (Beta) and the Gemini Deep Research Agent (Preview) were released together, signaling a deliberate architectural pivot and providing both the runtime and a managed agent that uses it.
  3. Real agent systems are stateful, tool-heavy, and long-running, so most engineering effort goes into planners, tool routing, memory, retries, auditing, and UIs — the LLM call itself is the smallest piece.

A Closer Look Into Databricks's Photon Engine

VuTrinh. • 79 implied HN points • 13 Apr 24
🕹 Technology Cloud Computing
  1. Photon engine uses columnar data layout to manage memory efficiently, allowing it to process data in batches. This helps in speeding up data operations.
  2. It supports adaptive execution, which means the engine can change how it processes data based on the input. This can significantly improve performance, especially when data has many NULLs or inactive rows.
  3. Photon integrates with Databricks runtime and Spark SQL, allowing it to enhance existing workloads without completely replacing the old system, making transitions smoother.

GroupBy #34: Hybrid Transactional/Analytical Storage, From Predictive to Generative – How Michelangelo Accelerates Uber’s AI Journey

VuTrinh. • 59 implied HN points • 07 May 24
🕹 Technology Cloud Computing
  1. Hybrid transactional/analytical storage combines different types of data processing. This helps companies like Uber manage their data more efficiently.
  2. The shift from predictive to generative AI is changing how companies use machine learning. Uber's Michelangelo platform shows how this new approach can improve AI applications.
  3. Data reliability and observability are important for businesses as their data grows. Companies need tools to quickly find and fix data issues to keep their operations running smoothly.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Issue #4 - The Five Minute History of Data

The Data Ecosystem • 59 implied HN points • 05 May 24
🕹 Technology Cloud Computing
  1. Data is generated and used everywhere now, thanks to smart devices and cheaper storage. This means businesses can use data for many purposes, but not all those uses are helpful.
  2. Processing data has become much easier over the years. Small companies can now use tools to analyze data without needing a team of experts, although some guidance is still necessary.
  3. Analytics has shifted from just looking at past data to predicting future trends. This helps companies make better decisions, and AI is starting to take over some of these tasks.

From Dynamo to DynamoDB : Unveiling the Titans of Tech

Mindful Matrix • 119 implied HN points • 18 Feb 24
🕹 Technology Cloud Computing
  1. Dynamo and DynamoDB are two names often seen in databases, but they have significant differences. Dynamo set the foundation, and DynamoDB evolved into a practical, scalable, and reliable service.
  2. Key differences between Dynamo and DynamoDB include their Genesis, Consistency Model, Data Modeling, Operational Model, and Conflict Resolution approaches.
  3. Dynamo focuses on eventual consistency, while DynamoDB offers both eventual and strong consistency. Dynamo is a simple key-value store, while DynamoDB supports key-value and document data models.

VTEX scales to 150 million metrics using Amazon Managed Service for Prometheus

VTEX’s Tech Blog • 99 implied HN points • 10 Mar 24
🕹 Technology Cloud Computing
  1. VTEX successfully scaled its monitoring system to handle 150 million metrics using Amazon's Managed Service for Prometheus. This helped them keep track of their numerous services efficiently.
  2. By adopting this system, VTEX cut its observability expenses by about 41%. This shows that smart choices in technology can save money.
  3. The new architecture allows VTEX to respond to problems faster and reduces the chances of system failures. It increased the reliability of their metrics, making everyday operations smoother.

Software Supply Chain Security in DevSecOps & CI/CD

Resilient Cyber • 259 implied HN points • 27 Sep 23
🕹 Technology Cloud Computing
  1. Software supply chain attacks are increasing, making it essential for organizations to protect their software development processes. Companies are looking for ways to secure their software from these attacks.
  2. NIST has issued guidance to help organizations improve software supply chain security, especially in DevSecOps and CI/CD environments. Following NIST's recommendations can help mitigate risks and ensure safer software delivery.
  3. The complexity of modern software environments makes security challenging. It's important for organizations to implement strict security measures throughout the development lifecycle to prevent attacks and ensure the integrity of their software.

Data Science Weekly - Issue 510

Data Science Weekly Newsletter • 279 implied HN points • 31 Aug 23
🕹 Technology Cloud Computing
  1. Autonomous drones can now race at human champion levels using deep reinforcement learning. This shows how advanced technology can mimic skilled human behavior in competitive sports.
  2. Google is rapidly developing its AI capabilities and plans to surpass GPT-4 by a significant margin soon. This could lead to more powerful AI tools for various applications.
  3. Reinforced Self-Training (ReST) is a new method for improving language models by aligning their outputs with human preferences. It offers better translation quality and can be done efficiently with less data.

Data's final format

Data People Etc. • 391 implied HN points • 09 Dec 24
🕹 Technology Cloud Computing
  1. Apache Iceberg™ is a popular way to manage data, offering features like scalability and openness. However, using it can feel complicated and less exciting than expected.
  2. CSV format is an easy and humble way to manage data, requiring no special knowledge or complex setups. It’s simple and widely understood, making it a go-to choice for many.
  3. The transformation of data management, like Iceberg™, is like building a transcontinental railroad. It's a huge effort aimed at improving the way we process and use information in the modern world.

Who cares about AuthZ? We went to KubeCon!

Permit.io’s Substack • 79 implied HN points • 28 Mar 24
🕹 Technology Cloud Computing
  1. Fine-grained authorization is becoming really important as more developers talk about it. People see that better security can happen with smooth developer experiences.
  2. The rise of cloud-native architecture and big data means we need better ways to manage authorization decisions. It helps reduce decision fatigue and improves security.
  3. Tools like Policy as Code and various authorization engines are helping different teams work together better. This can lead to faster and more efficient development processes.

A detailed guide to running dbt Core in Production in AWS on ECS

The Orchestra Data Leadership Newsletter • 79 implied HN points • 28 Mar 24
🕹 Technology Cloud Computing
  1. A detailed guide to running dbt Core in production in AWS on ECS is outlined, focusing on achieving cost-effective and reliable execution.
  2. Running dbt in production is not highly compute-intensive, as it primarily serves as an orchestrator, making it more cost-efficient compared to running Python code that utilizes compute resources.
  3. By setting up dbt Core on ECS in AWS and using Orchestra, you can achieve a scalable, cost-effective solution for self-hosting dbt Core with full visibility and control.

Nebius Part 1: the Smooth (Developer) Operator

Interconnected • 277 implied HN points • 17 Feb 25
🕹 Technology Cloud Computing
  1. Nebius is focused on creating a smooth experience for developers. They make it easy for developers to start using their platform without unnecessary steps, which is important for building cool AI projects.
  2. The company has a strong background thanks to its roots in Yandex, which gives it experience in running cloud services effectively. This experience helps Nebius offer a wide range of cloud solutions, not just GPU rentals.
  3. While some may worry about Nebius's Russian connections, the company has distanced itself from that past. With significant funding and a solid road ahead, it seems ready to grow and succeed free from those burdens.

Microsoft builds the bomb

benn.substack • 1508 implied HN points • 26 May 23
🕹 Technology Cloud Computing
  1. The modern data stack aimed to revolutionize how technology is built and sold, focusing on modularity and specialized tools.
  2. Microsoft introduced Fabric as an all-in-one data and analytics platform to address the issue of fragmentation in the modern data stack.
  3. Fabric from Microsoft presents a unified solution but may risk limiting choice and innovation in the data industry.

The Next Wave Of AI Computing

Startup Pirate by Alex Alexakis • 235 implied HN points • 10 Mar 23
🕹 Technology Cloud Computing
  1. Artificial intelligence has come a long way since Alan Turing, with AI chips being a key component for advanced computations.
  2. Edge computing moves computing power closer to where data is generated, enabling faster responses for AI applications like self-driving cars.
  3. Axelera AI is focusing on AI chips for edge computing and advancing technology for applications like computer vision in the physical world.

If It Fits, Gemma Sits 💎

Sector 6 | The Newsletter of AIM • 99 implied HN points • 23 Feb 24
🕹 Technology Cloud Computing
  1. Google has integrated its new model, Gemini, into Google Workspace, showing its focus on developing AI tools for users.
  2. While Google has released a model called Gemma, it is not truly open-source, which raises questions about its commitment to the open-source community.
  3. This year, Google is heavily promoting its Gemini brand, including recent updates and changes to its existing AI products like Bard.

Import AI 352: Asteroids and AI policy; privacy-preserving AI benchmarks; and distributed inference

Import AI • 159 implied HN points • 11 Dec 23
🕹 Technology Cloud Computing
  1. Preparing for potential asteroid impacts requires coordination, strategic planning, and societal engagement.
  2. Distributed systems like LinguaLinked challenge traditional AI infrastructure assumptions, enabling local governance of AI models.
  3. Privacy-preserving benchmarks like Hashmarks allow for secure evaluation of sensitive AI capabilities without revealing specific information.

The Tech Buffet #17: 9 Effective Techniques To Boost Retrieval Augmented Generation (RAG) Systems

The Tech Buffet • 139 implied HN points • 02 Jan 24
🕹 Technology Cloud Computing
  1. Make sure the data you use for RAG systems is clean and accurate. If you start with bad data, you'll get bad results.
  2. Finding the right size for document chunks is important. Too small or too large can affect the quality of the information retrieved.
  3. Adding metadata to your documents can help organize search results and make them more relevant to what users are looking for.

I spent another 8 hours understanding the design of Amazon Redshift. Here's what I found.

VuTrinh. • 79 implied HN points • 16 Mar 24
🕹 Technology Cloud Computing
  1. Amazon Redshift is designed as a massively parallel processing data warehouse in the cloud, making it effective for handling large data sets efficiently. It changes how data is stored and queried compared to traditional systems.
  2. The system uses a unique compilation service that generates specific code for queries, which helps speed up processing by caching compiled code. This means Redshift can reuse code for similar queries, reducing wait times.
  3. Redshift also uses machine learning techniques to optimize operations, such as predicting resource needs and automatically adjusting performance settings. This allows it to scale effectively and maintain high performance during heavy workloads.

GroupBy #31: Migrating a Trillion Entries of Uber’s Ledger Data from DynamoDB to LedgerStore, Grab Experiment Decision Engine

VuTrinh. • 59 implied HN points • 16 Apr 24
🕹 Technology Cloud Computing
  1. Uber successfully migrated over a trillion entries of its ledger data to a new database called LedgerStore without causing disruptions. This shows how careful planning can make big data moves smooth.
  2. Airbnb has open-sourced a machine learning feature platform called Chronon, which helps manage data and makes it easier for engineers to work with different data sources. This promotes collaboration and innovation in the tech community.
  3. The GrabX Decision Engine boosts experimentation on online platforms by providing tools for better planning and analyzing experiments. This can lead to more informed decisions and improved outcomes in projects.

Time to First Token

Kesav’s Lab • 8 implied HN points • 26 Jan 26
🕹 Technology Cloud Computing
  1. Using an inference provider gets you serverless endpoints, streaming, and time-to-first-token optimizations fast and is great for experimentation, but it sacrifices control over data residency and token logging. Building your own infra gives maximum control and compliance but is costly, slow to provision, and requires tradeoffs between speed, quality, and price.
  2. Provisioning large GPU instances is as much political and logistical as it is technical — expect weeks of lead time, enterprise support, and close coordination with cloud vendors to get high-end capacity. Tools like managed notebooks speed prototyping, but real deployments involve lots of debugging and operational overhead.
  3. TechBio workloads need specialized compute and tight lab-in-the-loop integration, which opens a market for domain-specific inference platforms that help fine-tune models and evaluate clinical viability. Because downstream clinical validation is slow and expensive, models that focus on toxicology and clinical outcomes are especially valuable for capturing real-world ROI.

5 SIEM Capabilities for Detection Engineering

Detection at Scale • 59 implied HN points • 15 Apr 24
🕹 Technology Cloud Computing
  1. Detection Engineering involves moving from simply responding to alerts to enhancing the capabilities behind those alerts, leading to reduced fatigue for security teams.
  2. Key capabilities for supporting detection engineering include a robust data pipeline, scalable analytics with a security data lake, and embracing Detection as Code framework for sustainable security insights.
  3. Modern SIEM platforms should offer an API for automated workflows, BYOC deployment options for cost-effectiveness, and Infrastructure as Code capabilities for stable long-term management.

These 7 Software Engineering Skills Give You an Unfair Advantage

Brain Bytes • 119 implied HN points • 17 Jan 24
🕹 Technology Cloud Computing
  1. Thinking like a hacker helps in identifying and fixing security flaws before they are exploited, crucial in today's cybersecurity landscape.
  2. Understanding different devices through cross-platform critical thinking gives a competitive edge and promotes reusability of business logic.
  3. Scripting and automation for repetitive tasks enhances productivity by ensuring consistency, accuracy, and freeing up time for more complex work.

($) Oracle Cloud: the Largest "Chinese Cloud" in America?

Interconnected • 123 implied HN points • 16 Jun 25
💼 Business Cloud Computing
  1. Larry Ellison, the founder of Oracle, recently became one of the richest people in the world after Oracle's stock price surged due to strong earnings. This happened because of a positive outlook for Oracle's cloud computing growth, fueled by increased demand for AI infrastructure.
  2. Oracle is securing a lot of contracts from companies with ties to China, like Temu and TikTok, even as other American businesses shy away from China. This strategy is helping Oracle grow in a challenging market.
  3. The recent growth in Oracle's sales isn't just from AI; they are getting significant deals from various clients moving to their cloud services, which reflects a strong demand for their technology.

DevEx: Better than an ExDev (And your Ex)

Permit.io’s Substack • 19 implied HN points • 04 Jul 24
🕹 Technology Cloud Computing
  1. Developer experience (DevEx) is really important because it helps developers focus on building great apps while also handling security tasks more smoothly.
  2. It's crucial to make security features easy to use so that everyone involved, from developers to non-technical users, can manage permissions and access without problems.
  3. A successful approach to DevEx considers the whole development process, ensuring security practices are integrated naturally into workflows from start to finish.

Data Science Weekly - Issue 484

Data Science Weekly Newsletter • 439 implied HN points • 02 Mar 23
🕹 Technology Cloud Computing
  1. Data scientists need the right tools and environment to do their jobs effectively. Organizations can help by improving their data science infrastructure.
  2. Understanding how to choose and advocate for important metrics is vital for product teams. This can lead to significant growth in user engagement.
  3. A/B testing is crucial in fraud detection to compare models and determine their effectiveness. It can provide valuable insights that improve model performance.

So... what is Stateless Architecture in Software Engineering[System Design Sundays]

Technology Made Simple • 199 implied HN points • 04 Jun 23
🕹 Technology Cloud Computing
  1. To understand stateless architecture, it's important to know the background of traditional client-server patterns and why moving towards stateless is beneficial.
  2. The concept of state in an application is crucial, and stateless architecture outsources state handling to more efficient systems like using cookies and shared instances for storing state.
  3. Stateless architecture simplifies state management, enhances client-side performance, and makes server scaling easier, aligning well with modern computing capabilities.

I spent 5 hours learning how ClickHouse built their internal data warehouse.

VuTrinh. • 1 HN point • 21 Sep 24
🕹 Technology Cloud Computing
  1. ClickHouse built its internal data warehouse to better understand customer usage and improve its services. They collected data from multiple sources to gain valuable insights.
  2. They use tools like Airflow for scheduling and Superset for data visualization, making their data processing efficient. This setup allows them to handle large volumes of data daily.
  3. Over time, ClickHouse evolved its system by adding dbt for data transformation and improving user experiences with better SQL query tools. They also incorporated real-time data to enhance their reporting.

Defending CI/CD Environments - The NSA/CISA Way

Resilient Cyber • 299 implied HN points • 29 Jun 23
🕹 Technology Cloud Computing
  1. CI/CD environments are crucial for the development and delivery of software, but they can also be targeted by hackers. It's important to secure these systems to prevent attacks.
  2. The NSA and CISA have released guidelines that offer best practices for protecting CI/CD pipelines. Using existing frameworks and tools can help improve security effectively.
  3. Transitioning to a Zero Trust model is recommended to enhance security in software development. This approach minimizes risks by ensuring that all access is restricted and monitored.

BigQuery processing engine: Shuffle

VuTrinh. • 119 implied HN points • 06 Jan 24
🕹 Technology Cloud Computing
  1. BigQuery uses a processing engine called Dremel, which takes inspiration from how MapReduce handles data. It improves how data is shuffled between workers for faster processing.
  2. Traditional approaches have issues like resource fragmentation and unpredictable scaling when dealing with huge data. Dremel solves this by managing shuffle storage separately from the worker, which helps in scaling and resource management.
  3. By separating the shuffle layer, Dremel reduces latency, improves fault tolerance, and allows for more flexible worker allocation during execution. This makes it easier to handle larger data sets efficiently.

LangGraph Cloud

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 02 Jul 24
🕹 Technology Cloud Computing
  1. LangGraph Cloud is a new service that helps developers easily deploy and manage their LangGraph applications online.
  2. Agent applications can handle complex tasks automatically and use large language models to work efficiently, but they face challenges like high costs and the need for better control.
  3. LangGraph Studio provides a visual way to see how code flows in applications, helping users understand and debug their work without changing any code.

I spent 7 hours reading another paper to understand more about Snowflake's internal. Here's what I found.

VuTrinh. • 79 implied HN points • 02 Mar 24
🕹 Technology Cloud Computing
  1. Snowflake has a unique design with three main layers: storage, virtual warehouse, and cloud service. This structure helps manage data efficiently and ensures high availability.
  2. The system uses a special ephemeral storage for temporary data during queries, which allows for quick access and less strain on the overall system. This helps with performance and reduces network load.
  3. Snowflake is designed for flexibility, allowing it to adapt resources based on customer needs and workloads. This elasticity helps provide better performance and efficiency.

GroupBy #29: Scaling AI/ML Infrastructure at Uber, The Sisyphean struggle and the new era of data infrastructure

VuTrinh. • 59 implied HN points • 02 Apr 24
🕹 Technology Cloud Computing
  1. Uber is focusing on building strong AI and machine learning infrastructure to keep up with the growing complexity of their models. This involves using both CPUs and GPUs for better efficiency.
  2. Data management is becoming crucial for companies like Netflix as they deal with massive amounts of production data. They are developing tools to effectively manage and optimize this data.
  3. The data streaming landscape is evolving, with new technologies emerging that make handling data easier and more efficient. This is changing how companies approach data infrastructure.

This well-known data company could be reversing the ETL to ELT shift

The Orchestra Data Leadership Newsletter • 79 implied HN points • 25 Feb 24
🕹 Technology Cloud Computing
  1. ETL (Extract-Transform-Load) and ELT (Extract-Load-Transform) have been key data engineering paradigms, but with the rise of the cloud, the need for in-transit data transformation has decreased.
  2. Fivetran, a widely known data company, is potentially shifting back to ETL methods by offering pre-built transformation features, effectively simplifying the data modeling process for users.
  3. There seems to be a trend towards a possible resurgence of ETL practices in the data industry, with companies like Fivetran potentially leading the way in providing ETL-like services within their platforms.

I spent 4 hours figuring out how BigQuery executes the SQL query internally. Here's what I found.

VuTrinh. • 79 implied HN points • 24 Feb 24
🕹 Technology Cloud Computing
  1. BigQuery processes SQL queries by planning, optimizing, and executing them. It starts by validating the query and creating an efficient execution plan.
  2. The query execution uses a dynamic tree structure that adjusts based on data characteristics. This helps to manage different types of queries more effectively.
  3. Key components of BigQuery include the Query Master for planning, the Scheduler for assigning resources, and Worker Shards that carry out the actual computations.