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Siliconangle

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How platform engineering solutions are simplifying cloud-native operations

  • Platform engineering solutions are simplifying cloud-native operations and expanding innovation with private AI.
  • Companies embrace cloud-native applications, increasing demand for efficient platform engineering solutions.
  • Nethopper LLC addresses the complexity of multicloud and Kubernetes environments with its Kubernetes AI Operations solution.
  • KAOPS from Nethopper provides a centralized platform for managing DevOps pipelines, enhancing automation, security, and scalability.

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Dev

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Don't Let Incidents Drown Your Support Team: How to Minimize Support Requests

  • Dealing with an incident can be stressful enough, but the flood of support requests that often comes with it can make things even worse.
  • Here are five strategies to avoid a flood of support requests during an incident:
  • Monitor social media to quickly identify common issues and provide updates and guidance to customers.
  • Provide proactive guidance to customers to reduce the volume of support requests.
  • Leverage chatbots to automate support for common issues and ensure quick and efficient assistance.
  • Create an incident response plan to effectively manage incidents and minimize support requests.
  • Encourage self-service options to empower customers and reduce the number of support requests.

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🧟‍♂️ The Zombie Server That Wouldn’t Die 💀

  • An old server at SpookyCloud Inc called the Zombie Server keeps returning after being terminated.
  • The server returns stronger with each termination, consuming more CPU resources.
  • Investigation reveals that the server belongs to a forgotten Auto Scaling Group from an ex-employee.
  • Lessons learned from the experience include tagging resources, cleaning up old environments, reviewing Auto Scaling Groups, and automating cleanup tasks.

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Itrevolution

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How I Broke My 20-Year SPSS Habit To Vibe Code Something in a Python Colab Notebook

  • The author shares their experience breaking a 20-year habit of using SPSS for statistical analysis and transitioning to using Python in a Google Colab Notebook for data analysis.
  • The transition involved embracing 'vibe coding' or 'chat coding,' where the author fully immersed themselves in the coding process, relying on AI-generated code and Python tools while maintaining cognitive engagement.
  • The author highlights the efficiency and productivity of SPSS due to its years of optimization but acknowledges the limitations when compared to modern tools like Python and R, especially in terms of data cleaning and analysis capabilities.
  • The challenge of learning Python and using new technologies like Pandas and Matplotlib was initially daunting, but the discovery of Google Colab with its coding assistant simplified the process for the author.
  • The author's experience in leveraging Python through chat-oriented programming led to successful data analysis tasks that would have been difficult to achieve using SPSS, showcasing the transformative potential of adopting new coding practices.
  • The use of AI-generated code, collaboration with the coding assistant, and exploration of Python libraries enabled the author to conduct sophisticated data analysis in a new ecosystem, marking a significant shift in their programming approach.
  • The author emphasizes the importance of being able to attempt advanced tasks in a different programming environment, highlighting the benefits of leveraging modern tools like Python for data analysis and programming challenges.
  • The article concludes by pointing out the transformative nature of embracing new coding methodologies and tools, emphasizing the opportunities for growth and innovation that come with breaking away from long-standing programming habits.
  • The shift from SPSS reliance to Python experimentation showcases the author's journey towards adapting to modern programming paradigms and exploring innovative ways to approach data analysis tasks.

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Deploy Nextcloud on Kubernetes

  • Nextcloud is an open-source data storage solution that can be self-hosted on Kubernetes.
  • The deployment of Nextcloud on a home Kubernetes cluster involves various steps:
  • Setting up environment variables for Nextcloud's user credentials, SMTP mail server, and MinIO credentials.
  • Using Nginx Ingress to expose Nextcloud within the home network and configuring Cloudflare Tunnel for remote access.

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AI-powered cloud security: How CrowdStrike and Google Cloud are enhancing protection at scale

  • CrowdStrike and Google Cloud are collaborating to enhance cloud security at scale, utilizing AI-powered technologies for proactive threat defense.
  • CrowdStrike's cloud-native security platform, backed by real-time AI-driven threat intelligence, enables enterprises to detect and prevent attacks effectively.
  • Google Cloud Marketplace simplifies access to trusted cloud security solutions, ensuring robust protection for workloads moving to the cloud.
  • The partnership provides embedded security protections for Google Cloud services like Kubernetes Engine, Cloud Run, and BigQuery.
  • Industries with high stakes, such as retail and finance, benefit from the CrowdStrike and Google Cloud partnership for securing cloud workloads.
  • Organizations can streamline procurement and consolidate security solutions through Google Cloud Marketplace, enhancing agility in responding to threats.
  • By integrating seamlessly into the DevOps cycle, CrowdStrike and Google Cloud focus on operational efficiency and reducing deployment times for cloud security.
  • The collaboration allows for scalability of protection amidst high-speed operations, as demonstrated by an international retailer enhancing cloud security during peak shopping periods.
  • Real-world examples showcase successful deployments of Falcon Cloud Security in protecting Google Cloud instances, emphasizing the importance of a secure cloud foundation.
  • The joint effort emphasizes removing operational friction and providing security-focused capabilities to enterprises looking to adopt cloud technologies efficiently and securely.

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Kubernetes Myth #06: Kubernetes Pods Always Need a Service Account

  • A service account is only needed when a pod needs to communicate with the Kubernetes API server or requires an identity for authentication.
  • Kubernetes assigns a default service account to every pod by default.
  • You can disable token mount at two levels, Pod level and SA level.
  • Removing the token from the service account is a simple yet effective way to reduce unnecessary attack surfaces in the cluster.

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10 Top CI/CD Pipeline Challenges And Solutions [2025]

  • CI/CD pipelines have become popular in software development, but challenges persist in their implementation.
  • Key challenges include limited environment resources, ownership complexities, multiple pipeline implementations, and security tool integration.
  • Other challenges are coordination issues, cost management, integration into existing projects, and resistance to cultural change.
  • Inefficient implementation, lack of training, and continuous testing optimization are also common hurdles.
  • Continuous testing is crucial, spanning from functional to non-functional tests for reliability and performance.
  • LambdaTest offers solutions through cloud-based testing integration to address CI/CD challenges effectively.
  • Automated testing, proper tool selection, and training are emphasized for successful CI/CD implementation.
  • Using cloud automation platforms like LambdaTest can streamline testing processes and improve efficiency.
  • Effective CI/CD implementation allows organizations to focus on innovation and feature delivery rather than manual operations.

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Announcing support for upgrades to Java 21 in Amazon Q Developer

  • Amazon Q Developer announced support for upgrades to Java 21, making it easier for Java developers to keep their applications up-to-date.
  • The latest version of Amazon Q Developer includes improved summarization and recommendations for simplifying the upgrade process.
  • Java 21 brings benefits such as virtual threads, improved performance, and better memory management, helping to enhance application concurrency, speed, and memory usage.
  • Amazon Q Developer simplifies the upgrade process by automatically analyzing codebases, providing detailed diffs, and generating summaries and tailored recommendations for further improvements.

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Database Sharding: Breaking It Down Without Breaking Your DB

  • Sharding is a technique where a database is split into smaller, manageable pieces to improve performance and scalability.
  • Sharding is necessary when the database outgrows the capacity of a single machine, query performance degrades, high availability is required, scaling up is not feasible, or for faster local access.
  • The main types of sharding include Key-Based (Hash) Sharding, Geo Sharding, Directory-Based (Lookup) Sharding, Range-Based Sharding, and Vertical Sharding.
  • Challenges of sharding include managing complexity, difficulty in rebalancing, expensive joins across shards, ensuring data consistency, and separate backup and recovery strategies for each shard.

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The Role of AI in DevOps

  • AI plays a crucial role in improving software delivery through predictive analytics, automation, and monitoring in DevOps, addressing modern software complexities and faster deployment demands.
  • Organizations are integrating AI technologies like machine learning and natural language processing into traditional DevOps to enhance processes and collaboration within teams.
  • The role of AI in DevOps optimizes tasks, automates repetitive processes, and provides insights for data-driven decision-making, leading to improved application performance and efficiency.
  • AI technologies such as machine learning, natural language processing, deep learning, and robotic process automation are utilized in DevOps to streamline processes and enhance efficiency.
  • Applications of AI in DevOps include personalized customer experiences, accelerated software development, and enhanced observability and performance monitoring.
  • Implementing AI in DevOps involves selecting AI-native tools, data collection and analysis, continuous learning, collaboration, training, and monitoring performance.
  • Top DevOps AI tools like LambdaTest, Jenkins X, and Dynatrace enhance automation, monitoring, incident management, and optimization of DevOps workflows.
  • Challenges in integrating AI in DevOps include communication barriers, resistance to change, skill gaps, integration complexities, data quality issues, and regulatory compliance.
  • Best practices for using AI in DevOps include starting small, aligning with business goals, monitoring algorithm behavior, training teams, ensuring data quality, and utilizing AI for testing and infrastructure management.
  • Future trends of AI in DevOps include advancements in AI technologies, predictive analytics, machine learning applications, and addressing ethical considerations and regulatory compliance challenges.

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GoFr: Power Up Your Microservices with This Go Framework

  • GoFr is an opinionated Go framework designed for developing microservices faster and with less hassle.
  • It provides built-in observability tools like health-check and heartbeat URLs, automatic Kubernetes probe support, tracing, metrics, and structured logging.
  • GoFr simplifies microservice development by supporting various data sources and handling tasks like database migrations and CRUD operations automatically.
  • It also offers features such as logging, flexible responses, health checks, metrics exposure, tracing capabilities, level-based logging, and circuit breaker pattern implementation.

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China Creates High-Tech Fund To Support AI, Tech Innovation

  • China has announced the creation of a state-backed fund to support AI, tech innovation, and emerging industries.
  • The fund, called the 'state venture capital guidance fund,' will focus on cutting-edge areas like AI, quantum technology, and hydrogen energy storage.
  • With a potential funding of nearly 1 trillion yuan ($138 billion) over 20 years, the fund aims to attract capital from local governments and the private sector.
  • China's move comes in response to mounting pressure from American tech restrictions and is seen as a step towards achieving semiconductor self-sufficiency.

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Flow Engineering Immersion Course: Transform How Teams Work Together

  • The Flow Engineering Immersion Course, part of the IT Revolution Immersion Course series, is now available for preorder.
  • The course is designed to improve collaboration and performance in large-scale organizations by teaching Flow Engineering techniques.
  • These techniques help teams align around outcomes, visualize and improve workflows, address bottlenecks, design effective processes, and create roadmaps for change.
  • Preordering customers can enjoy a 30% discount on the regular price, with the course launching on April 15th, 2025.

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Medium

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Introduction to Go.

  • Go is an open-source, statically-typed, compiled programming language created at Google.
  • Go combines the performance and security benefits of low-level languages like C with the ease of use of higher-level languages like Python.
  • Go excels in performance and built-in concurrency, making it well-suited for scalable, cloud-based servers optimized for performance.
  • Go offers simpler syntax and faster startup times compared to Java, and provides a balance between performance, simplicity, and ease of deployment.

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