The hottest Cloud Computing Substack posts right now

And their main takeaways
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Top Technology Topics

Cloud Shared Responsibility Model: Time for an (R)Evolution?

Resilient Cyber • 119 implied HN points • 27 Mar 23
🕹 Technology Cloud Computing Cybersecurity Data Privacy Information Technology
  1. The Shared Responsibility Model (SRM) explains that cloud customers and service providers each have their own security duties. Customers need to understand their roles to prevent most data breaches, which are often due to customer mistakes.
  2. Google Cloud introduced the idea of 'Shared Fate,' encouraging cloud providers to take an active role in helping customers secure their environments. This shift acknowledges that both sides must work together for better security outcomes.
  3. There are growing concerns about the risks of relying on a few major cloud providers. If one suffers a security issue, it can affect everyone, highlighting the need for a community approach to cloud security and trust.

GroupBy #12: AWS re:Invent 2023, Druid and ClickHouse at Lyft, Apache Hudi History

VuTrinh. • 39 implied HN points • 05 Dec 23
🕹 Technology Data Engineering Cloud Computing Machine Learning Software Development Data Analytics
  1. AWS re:Invent 2023 announced new features focused on improving data storage and processing. This includes faster storage options and AI capabilities for better data insights.
  2. Lyft switched from using Druid to ClickHouse for their analytics needs. This change was driven by a need for faster data query responses.
  3. Apache Hudi was created to help manage data in a more efficient way. It enables incremental data processing, making it easier to work with large amounts of information.

Big-Tech Silicon War Begins

Sector 6 | The Newsletter of AIM • 39 implied HN points • 03 Dec 23
🕹 Technology AI Machine Learning Cloud Computing
  1. Big tech companies are competing to create their own specialized chips for AI tasks. This is happening because they want to improve their services and performance.
  2. AWS has launched new AI chips, claiming to lead the market with over 50,000 customers already using their technology.
  3. Other tech giants like Google, Microsoft, and Apple are also developing their chips, but AWS believes they are significantly ahead of the competition.

Introducing Orchestra: rapidly Build and Monitor Data and AI Products

The Orchestra Data Leadership Newsletter • 19 implied HN points • 07 Mar 24
🕹 Technology Data Management Artificial Intelligence Software Engineering Data Visualization Cloud Computing
  1. Launching a free tier for Orchestra, a tool to build and monitor data and AI products, offering a lightweight approach to improving business value and AI integration.
  2. Addressing the challenges faced by data teams in balancing business value and software engineering best practices through tools like Nessie, dbt, and emerging 'as-code' BI platforms.
  3. Providing an end-to-end platform with features like declarative pipelines, data quality monitoring, granular alert control, and asset-based data lineage to empower data teams in accelerating their initiatives.

Don't wait until it's not messy

Sunday Letters • 99 implied HN points • 21 Feb 23
🕹 Technology Innovation Web Development Cloud Computing Software Engineering Emerging Tech
  1. Don't wait for things to be perfect before starting something new. It's better to jump in while things are a bit messy.
  2. As an engineer or creator, focusing on solutions is key. Look for interesting problems to solve instead of getting stuck on why things are hard.
  3. If everyone only started when it was easy, no one would ever innovate. Embrace the challenges and start building!
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Which Llama-2 Inference API should I use?

LLMs for Engineers • 39 implied HN points • 31 Oct 23
🕹 Technology AI Development Open Source APIs Machine Learning Cloud Computing
  1. TogetherAI was found to perform the best overall in terms of cost, speed, and accuracy, closely followed by MosaicML.
  2. It's important to understand your specific needs when choosing an API, like cost and speed requirements, to find the best fit.
  3. Experimenting with system prompts can lead to major improvements in performance, so don't hesitate to try different settings!

GroupBy #7: The rise of data engineer, levels of abstractions, data modeling

VuTrinh. • 39 implied HN points • 31 Oct 23
🕹 Technology Data Engineering Software Development Machine Learning Data Modeling Cloud Computing
  1. Data engineers are becoming more important in the tech world as they handle vast amounts of data. Their role is focused on building systems that allow for efficient data handling and analysis.
  2. Levels of abstraction in data engineering can be confusing, leading to challenges in understanding systems. It’s important to find a balance between using abstractions and being able to see the underlying processes.
  3. Good data modeling practices can help organizations make better use of their time-series data. Understanding how to structure data effectively is key to unlocking its value.

It's TCP vs. RPC All Over Again

Systems Approach • 154 HN points • 20 Feb 23
🕹 Technology Networking Protocols Cloud Computing Datacenters Internet
  1. Debate continues on the need for a standard protocol for request/response paradigm beyond TCP and UDP.
  2. The Internet has extensively used RPC for distinct purposes like email, network management, and name resolution.
  3. Comparisons between TCP and RPC in datacenters highlight the need for a specialized transport protocol optimized for request/reply workloads.

GroupBy #23: Meta loves Python, How Uber Serves Over 40 Million Reads Per Second from Online Storage Using an Integrated Cache

VuTrinh. • 19 implied HN points • 20 Feb 24
🕹 Technology Data Engineering Software Development Data science Artificial Intelligence Cloud Computing
  1. Meta is heavily invested in Python, and they're working on improvements to enhance its performance and usability.
  2. Uber has developed a powerful database called Docstore that can handle over 40 million reads per second, demonstrating their capability in data management.
  3. Data, while useful, doesn't capture the complete reality, and it's important to recognize its limitations in understanding complex scenarios.

Microsoft Sentinel SOC 101: How to Detect and Mitigate Rare Domains Seen in Cloud Logs

Rod’s Blog • 39 implied HN points • 19 Oct 23
🕹 Technology Security Cloud Computing Threat Detection Automation Orchestration
  1. Rare domains in cloud logs can indicate malicious activities like command and control communication, phishing, or data exfiltration.
  2. Microsoft Sentinel offers a built-in hunting query to identify rare domains and mitigate potential security incidents.
  3. By using automation and orchestration in Microsoft Sentinel, organizations can efficiently respond to and manage incidents related to rare domains in cloud logs.

Creating a Security Posture Report for a Specific Azure Subscription

Rod’s Blog • 19 implied HN points • 13 Feb 24
🕹 Technology Cloud Computing Cybersecurity Data Analysis Documentation
  1. Creating a security posture report for a specific Azure subscription provides enhanced visibility into the security state of assets and workloads, aiding in identifying potential vulnerabilities.
  2. The report includes guidance for improvement with hardening recommendations to help efficiently enhance security posture.
  3. Azure Secure Score assists in prioritizing security recommendations for effective triage to enhance security posture and align with compliance standards.

Rain or Shine for Alibaba Cloud?

Tech Buzz China Insider • 59 implied HN points • 03 Mar 23
🕹 Technology Cloud Computing Market Analysis Competitors Infrastructure
  1. In the Chinese cloud computing market, Alibaba Cloud leads and is more profitable compared to Tencent and Huawei due to its robust products and market fit.
  2. Alibaba Cloud has evolved sales strategies over time, shifting from a product-driven approach to catering to traditional enterprises and government clients.
  3. The future growth of the cloud sector, including for Alibaba Cloud, is expected in areas like AI and EVs, with significant investments being made in these sectors.

Breaking Down the DoD Software Modernization Strategy

Resilient Cyber • 79 implied HN points • 13 Apr 23
🕹 Technology Software Development Cybersecurity Cloud Computing Defense technology Information Systems
  1. The Department of Defense (DoD) wants to modernize its software to keep up with technology and improve national security. They plan to deliver software that is reliable and fast to adapt to changing needs.
  2. A key part of the strategy is embracing cloud technologies and making sure software can withstand and recover from issues. This means investing in modern tech and improving processes to speed up software delivery.
  3. To achieve these goals, the DoD recognizes the importance of updating how it trains and manages its workforce. They need to make sure their team is skilled and ready to adapt to new technologies and ways of working.

Microsoft Sentinel SOC 101: How to Detect and Mitigate Fileless Malware Attacks with Microsoft Sentinel

Rod’s Blog • 39 implied HN points • 09 Oct 23
🕹 Technology Cybersecurity Cloud Computing AI Threat Detection Malware
  1. Fileless malware attacks are increasing and can be a serious threat to organizations as they evade traditional antivirus solutions by not relying on executable files.
  2. Microsoft Sentinel, a cloud-native security information and event management solution, can help detect and mitigate fileless malware attacks by collecting data at scale, utilizing analytics rules, and automating incident response.
  3. To prevent fileless malware attacks, consider using web filtering to block phishing emails, managed threat hunting for early detection, and indicators of attack (IOAs) analysis to identify malicious activities.

BYOK

Aipreneur • 39 implied HN points • 08 Mar 23
🕹 Technology AI Data science Machine Learning Cloud Computing Mobile technology
  1. BYOD (Bring Your Own Device) became popular in corporates due to iPhone's rise and employee preferences.
  2. BYOD is beneficial for companies in cost-saving, convenience, increased mobility, and changing workforce demographics.
  3. The emerging trend of BYOK (Bring Your Own Keys) is starting in AI platforms, where users need to pay for keys to access and use data responsibly.

Showing the Receipts of Smart Manufacturing

Exponential Industry • 39 implied HN points • 30 Mar 23
🕹 Technology Technology Adoption Cloud Computing
  1. Manufacturers are adopting smart manufacturing technologies for greater agility and resilience in a changing global landscape.
  2. Smart manufacturing technology adoption is driven by advancements, lower costs, and interoperability across industries.
  3. Industry verticals with higher gross margins like aerospace, electronics, and automotive invest more in smart manufacturing technologies.

NVIDIA Builds Safety Net

Sector 6 | The Newsletter of AIM • 39 implied HN points • 28 Aug 23
🕹 Technology AI Cloud Computing Software Generative AI Partnerships
  1. NVIDIA launched the AI Foundation, a cloud-based service that helps businesses use generative AI for different projects like medical research and artwork.
  2. They partnered with VMware to help companies create and use smart AI applications, like chatbots and virtual assistants.
  3. This move shows NVIDIA is trying to diversify its business and stay strong in the GPU market.

Microsoft Sentinel SOC 101: How to Detect and Mitigate Cryptojacking Attacks with Microsoft Sentinel

Rod’s Blog • 39 implied HN points • 03 Oct 23
🕹 Technology Cybersecurity Cloud Computing Data Analytics Threat Detection
  1. Cryptojacking involves using cloud resources to mine cryptocurrencies, leading to increased costs and performance issues for affected cloud customers.
  2. Common indicators of cryptojacking include high CPU/memory usage by unknown processes, unusual network traffic patterns, changes in cloud resource usage, and presence of malicious mining code.
  3. Microsoft Sentinel can help detect and respond to cryptojacking by analyzing data from various sources, applying advanced analytics, providing visualization dashboards, and enabling fast investigation and response using built-in playbooks.

Using Azure Open AI with Microsoft Sentinel Part 1 - Getting Keys and Endpoints

Rod’s Blog • 39 implied HN points • 30 Mar 23
🕹 Technology Cloud Computing AI Data Management Cybersecurity Programming
  1. Consider transitioning from Logic App connector for Open AI ChatGPT to Azure Open AI's ChatGPT for more control over data.
  2. When working with Azure Open AI models, deployments should be done in the Azure console, not Azure OpenAI Studio, and need patience for the API to become accessible.
  3. In Microsoft Sentinel, use best practices like storing API keys and endpoints in Parameters for calls to Azure Open AI deployments.

Azure Cracks the Code

Sector 6 | The Newsletter of AIM • 39 implied HN points • 08 Aug 23
🕹 Technology Cloud Computing Tech Companies Market Trends
  1. Microsoft Azure is growing fast, making over $55 billion in revenue, which is more than half of Microsoft's cloud earnings.
  2. The cloud market is getting more competitive since the rise of Generative AI, with companies like Google Cloud also seeing big revenue increases.
  3. Azure's revenue grew by 23% recently, showing that it's gaining traction in the cloud space against established leaders.

Cross-workspace Query Best Practice for Microsoft Sentinel

Rod’s Blog • 39 implied HN points • 17 Apr 23
🕹 Technology Cybersecurity Cloud Computing Data Analysis Social media
  1. Cross-workspace queries in Microsoft Sentinel are crucial for managing multiple workspaces or customers.
  2. When using cross-workspace queries, it is more efficient to use the workspace ID rather than names or fully qualified names.
  3. Workspace IDs can be found in the Overview pane of the Log Analytics workspace or using a KQL query in Azure Resource Graph Explorer.

Preparing the SOC for Generative AI

Rod’s Blog • 39 implied HN points • 05 Sep 23
🕹 Technology AI Cybersecurity Automation Podcasts Cloud Computing
  1. Before implementing Generative AI in a SOC, it's important to configure incident tags to provide more information for AI.
  2. Assigning specific incidents to analysts based on skillsets through automation rules can enhance SOC efficiency.
  3. Practicing gathering information to create better Generative AI prompts is crucial for successful AI utilization in a SOC.

Tech Talks Weekly #4

Tech Talks Weekly • 19 implied HN points • 19 Feb 24
🕹 Technology Software Development Web Development Data science Cloud Computing Programming Languages
  1. The newsletter summarizes recent tech talks from various conferences, making it easier for readers to find valuable content. It's a great resource for anyone interested in technology.
  2. Each issue features a selection of must-watch talks, along with a list of new uploads categorized by conference. This helps viewers easily discover trending topics in tech.
  3. Readers are encouraged to provide feedback on the newsletter format and share it with friends or colleagues to grow the community. It's all about connecting more people to interesting tech discussions.

Dissecting the FedRAMP Authorization Act

Resilient Cyber • 99 implied HN points • 04 Dec 22
🇺🇸 U.S. Politics Legislation Cybersecurity Cloud Computing Federal Government
  1. The FedRAMP Authorization Act aims to improve how federal agencies adopt cloud services. It highlights the importance of cloud for modernizing old IT systems and creating jobs in the tech sector.
  2. A key change in the legislation is the creation of a Federal Secure Cloud Advisory Committee. This group will include experts from both the government and private sector to streamline cloud service authorizations and improve communication.
  3. Another important aspect is the 'Presumption of Adequacy', which allows agencies to trust existing FedRAMP authorizations without needing extra checks. This should reduce the repetitive security assessments that cloud service providers currently face.

GroupBy #18: Uber - GC Tuning for Improved Presto Reliability, How Meta is advancing GenAI

VuTrinh. • 19 implied HN points • 16 Jan 24
🕹 Technology Data Engineering Artificial Intelligence Cloud Computing Software Development System reliability
  1. Uber improved its Presto reliability by tuning garbage collection. This helps the system run better and more dependably.
  2. Meta is making strides in generative AI, focusing on how it can bring new advancements. The future looks promising for AI technologies.
  3. Python 3.13 introduced a Just-In-Time (JIT) compiler, which could speed up programming processes. This is a beneficial development for Python users.

GroupBy #17: Pinterest’s new wide column database using RocksDB, Fault tolerance Kafka on Kubernetes at Grab

VuTrinh. • 19 implied HN points • 09 Jan 24
🕹 Technology Data Engineering Software Development Database Systems Cloud Computing Big Data
  1. Pinterest has developed a new wide column database using RocksDB for better data handling. This helps them manage large amounts of data more efficiently.
  2. Grab improved Kafka's fault tolerance on Kubernetes, ensuring their real-time data streaming service runs smoothly even when problems occur.
  3. The newsletter will evolve, offering more content types like curated resources on data engineering and personal insights every week.

How Netflix survived the AWS outage in 2011 [System Design Sundays]

Technology Made Simple • 39 implied HN points • 13 Feb 23
🕹 Technology Systems Design Resilience Cloud Computing Chaos Engineering Data architecture
  1. Netflix utilized Open Connect Appliances to provide better streaming by localizing content on devices of certain ISPs.
  2. The use of Stateless-service architecture allows any server to step in if one fails, ensuring uninterrupted service.
  3. Netflix's redundancy strategy includes storing data in multiple zones, using 'n+1' redundancy, and employing graceful degradation techniques to maintain limited functionality in case of failure.

GroupBy #16: Uber's Anomaly Detection & Alerting System, many layers of data lineage

VuTrinh. • 19 implied HN points • 02 Jan 24
🕹 Technology Data Engineering Machine Learning Software Development Data Analytics Cloud Computing
  1. Uber has developed an anomaly detection system called uVitals, which helps identify issues before they become major problems. It analyzes data patterns to catch anomalies early.
  2. Data modeling is essential for creating structured databases that allow for better analysis and comparisons. It's important for data projects to have clear designs.
  3. As the field of data engineering evolves, new roadmaps and resources are emerging to guide professionals in developing necessary skills. Staying updated can help engineers advance their careers.

Building a Compliance and AppSec Program for a Federal Platform-as-a-Service (PaaS)

Resilient Cyber • 59 implied HN points • 11 Apr 23
🕹 Technology Cybersecurity Cloud Computing DevOps Compliance Software Development
  1. Building a compliance and AppSec program for a federal Platform-as-a-Service is challenging. It's important to understand which security controls can be inherited by development teams.
  2. Scaling the compliance program across multiple teams can lead to unique challenges. It's crucial to onboard each team effectively while minimizing their workload.
  3. Developers need support in balancing security and compliance with their work. Educating auditors about cloud practices is also important for smoother collaboration.

GroupBy #14: What it takes to be a Senior IC at Meta, Netflix Data Engineering Summit

VuTrinh. • 19 implied HN points • 19 Dec 23
🕹 Technology Data Engineering Software Development Cloud Computing Artificial Intelligence Big Data
  1. To be a Senior Individual Contributor at Meta, focus on quickly adding value and aligning with the organization's goals. It's about making an impact and building good relationships within the team.
  2. Data modeling involves creating a shared understanding between business and data teams. It's essential for delivering valuable insights and ensuring everyone is on the same page.
  3. Job hopping in data engineering can be successful with the right approach. Make sure to deliver value early on and always be ready for new opportunities while enjoying your work-life balance.

GroupBy #13: Explaining Kubernetes To My Uber Driver, Data Modelling For Data Engineers

VuTrinh. • 19 implied HN points • 12 Dec 23
🕹 Technology Data Engineering Software Development Learning Resources Cloud Computing
  1. Kubernetes can be tricky to explain, but using simple analogies can help anyone understand its purpose. It's like managing many containers, just like an Uber driver manages different passengers.
  2. Data modeling is essential for data engineers to organize and structure data effectively. This helps make data more accessible and useful for analysis.
  3. Learning resources, such as free online courses, are available to help you start or improve your skills in data engineering. They cover various important topics for new and experienced data engineers.

Clouded Judgement 2.7.25 - "Group + Triage" AI Systems

Clouded Judgement • 4 implied HN points • 07 Feb 25
🕹 Technology AI Systems Software Cloud Computing Data Management Automation
  1. AI can really help with organizing and prioritizing tasks in many areas like customer support and fraud detection. This means faster and more efficient decision-making for businesses.
  2. Cloud software companies like Amazon, Microsoft, and Google are seeing some slower growth lately. It's important to keep an eye on how they perform in future reports.
  3. The value of a software company is often based on its revenue, especially when it's not profitable yet. Understanding these valuation methods can help investors make smarter choices.

Stay the hell away from anything that's not cloud portable

DevOps, K8s, and the Cloud • 6 HN points • 24 Apr 24
🕹 Technology Cloud Computing Serverless Computing
  1. Stick to using standard, open, and protocol-compliant resources whenever possible for cloud portability.
  2. If leveraging proprietary capabilities, wrap them in clean abstractions to swap out implementations across clouds easily.
  3. Prioritize cloud portability early to avoid the risks of vendor lock-in and technical debt in the future.

Troublesome Tenants

Resilient Cyber • 59 implied HN points • 16 Jan 23
🕹 Technology Cloud Computing Cybersecurity Data Privacy Software Development Information Technology
  1. The PEACH Framework helps with cloud security by focusing on tenant isolation. It gives guidance on how to keep different customer data safe from each other.
  2. Multi-tenancy in cloud computing can bring risks, especially if security isn't handled correctly. It's important for both cloud service providers and users to understand these risks and take steps to protect themselves.
  3. Effective tenant isolation involves using several methods, like reducing complexity and improving separation. These strategies help ensure that one tenant's data doesn’t accidentally mix with another's.