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Preemptible pods: Optimizing Kubernetes node utilization

Supercharge Your Kubernetes Workflow with Essential Tools: Starship, Kubectx, Kubecolor, and K9s

Exploring Helm template dictionary objects: Syntax evolution and best practices

Dockerizing a Golang API with MySQL and adding Docker Compose Support

Karmada: Deep dive into managing multiple AKS clusters

🔍Secret Knowledge

Zero Downtime Deployment in AWS with Tofu

Cron Jobs on Linux

How To Run Migrations Across 2,800 Microservices

Transform AWS exam generator architecture to open source

How to Run WebAssembly on Amazon EKS

⚡Techwave

Chrome Vulnerability Reward Program (VRP) has updated its rewards

How misconfigured AWS IAM roles using GitLab's OpenID Connect (OIDC) can allow unauthorized users to assume roles

Preview Release of the Migration Tool for the AWS SDK for Java 2.x

Amazon’s Exabyte-Scale Migration from Apache Spark to Ray on Amazon EC2

Unlock 1 Million RPS: Experience Triple the Speed with Valkey

🛠️Hackhub

kubeai: Private Open AI on Kubernetes

cyphernetes: A Kubernetes Query Language

chartdb: Free and open-source database diagrams editor, visualize and design your DB with a single query.

stack-auth: Open-source Auth0/Clerk alternative

mariadb-operator: Run and operate MariaDB in a cloud native way

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Preemptible pods: Optimizing Kubernetes node utilization

Preemptible Pods in Kubernetes enable efficient resource management by allowing you to assign priorities to different workloads through pod priority and preemption mechanisms. This means that critical applications are guaranteed the resources they need because higher-priority pods can preempt, or evict, lower-priority ones when resources are scarce. By implementing PriorityClasses and configuring pods accordingly, you ensure that essential services remain responsive and that your cluster optimizes node utilization.

Supercharge Your Kubernetes Workflow with Essential Tools: Starship, Kubectx, Kubecolor, and K9s

To enhance your Kubernetes workflow, using tools like Starship, Kubectx, Kubecolor, and K9s can significantly improve efficiency. Starship provides a customizable, fast shell prompt that shows key info like cluster and namespace, while Kubectx and Kubens allow quick switching between clusters and namespaces. Kubecolor adds color to kubectl output for better readability, and K9s offers a terminal-based UI to manage and visualize Kubernetes resources easily.

Exploring Helm template dictionary objects: Syntax evolution and best practices

Helm, the Kubernetes package manager, uses dictionary objects in its templating system to manage key-value pairs for application deployment. Initially, Helm syntax allowed for creating dictionaries in a single line, but this became cumbersome when handling many properties. Over time, a more efficient syntax evolved, using the `set` function to incrementally add properties to a dictionary without recreating it. Best practices for using Helm dictionaries include adding properties incrementally, avoiding reassignment to prevent data loss, maintaining consistent naming conventions, and thoroughly testing templates to ensure correct Kubernetes manifest generation.

Dockerizing a Golang API with MySQL and adding Docker Compose Support

Dockerizing a Golang API with MySQL simplifies the process of developing and testing APIs locally by containerizing both the API and database. First, you create a Dockerfile for the Go API using best practices like lightweight base images, multi-stage builds, creating a binary, and optimizing Docker layers. This ensures a smaller and more efficient container. Then, to streamline managing both the API and MySQL containers, Docker Compose is used. A `compose.yml` file sets up both services, ensuring the API only starts once the MySQL database is ready, avoiding connection issues. This setup makes local development smoother and easier to replicate.

Karmada: Deep dive into managing multiple AKS clusters

Karmada (Kubernetes Armada) is a tool that simplifies managing multiple AKS (Azure Kubernetes Service) clusters by treating them like a single entity. It helps deploy applications across clusters while handling tasks like scheduling, resource propagation, and ensuring consistency. Karmada’s components—such as the API Server, Controller Manager, Scheduler, and Agent—work together to automate the deployment process. It supports advanced strategies like multi-cluster deployments, disaster recovery, and canary releases.

Zero Downtime Deployment in AWS with Tofu

Zero Downtime Deployment in AWS is a strategy to update applications without causing service interruptions. By leveraging tools like OpenTofu, Terraform, and AWS SAM, developers can ensure seamless updates. Techniques like instance refreshes in Auto Scaling Groups (using OpenTofu), immutable infrastructure (Terraform + Ansible), and advanced deployment strategies like Blue/Green and Canary deployments enable applications to be updated while keeping them available to users. These approaches allow for gradual testing, automated rollbacks, and maintaining reliability.

Cron Jobs on Linux

Cron jobs in Linux are scheduled tasks that automate running scripts or commands at specific times or intervals, managed by the cron daemon. Common use cases include backups, updates, and system health checks. Users can create, view, or edit cron jobs using the `crontab` command. Cron jobs are defined using a simple time-based syntax, where each job can run on a specific schedule (e.g., hourly, daily, or weekly). Cron jobs can be user-specific or system-wide, and their syntax supports flexible timing options like ranges, lists, and intervals.

How To Run Migrations Across 2,800 Microservices

To handle migrations across 2,800 microservices, we use a centrally driven approach where a single team manages the entire process. This allows us to keep libraries up-to-date, maintain consistency, and automate the bulk of the changes, reducing coordination overhead and minimizing risks of failure. Our strategy relies on a monorepo structure, consistent technology (like Go), and powerful mass deployment tooling. We start by wrapping old libraries, automate common updates, handle edge cases manually, and control rollouts via config changes to ensure smooth transitions without downtime.

Transform AWS exam generator architecture to open source

In this series, we aim to transform a serverless AWS architecture for an exam generator app into an open-source version. The original solution helps educators create curriculum-aligned assessments quickly, while students can take personalized quizzes with instant feedback. We'll replace key AWS services like Cognito, Lambda, DynamoDB, and Fargate with open-source alternatives and host everything on a Kubernetes cluster.

How to Run WebAssembly on Amazon EKS

The article outlines the process of setting up a Wasm environment on Amazon EKS using tools like HashiCorp Packer and Terraform to create custom Amazon Machine Images (AMIs) and manage the infrastructure. It details how to build an EKS cluster, deploy example workloads using different Wasm runtimes (Spin and WasmEdge), and check if everything is working correctly. Finally, it offers instructions for cleaning up the resources after running the applications.

Chrome Vulnerability Reward Program (VRP) has updated its rewards

Google's Chrome Vulnerability Reward Program (VRP) has updated its reward structure to encourage deeper research into Chrome's security vulnerabilities. As Chrome becomes more secure, finding impactful bugs has become harder. The new structure separates memory corruption bugs from other vulnerability types and offers higher rewards for more complex, well-documented reports, such as those demonstrating remote code execution (RCE) or memory corruption. The top reward for an RCE in a non-sandboxed process is now $250,000. These changes aim to incentivize thorough and high-quality bug reporting, ensuring Chrome remains secure.

How misconfigured AWS IAM roles using GitLab's OpenID Connect (OIDC) can allow unauthorized users to assume roles

The article by Nick Frichette explains how misconfigured AWS IAM roles using GitLab's OpenID Connect (OIDC) can allow unauthorized users to assume roles. This occurs when the trust policy lacks restrictions on which specific GitLab groups or projects can access the role. By default, the AWS Console creates a vulnerable trust policy, making it possible for any GitLab user to exploit the misconfiguration. The article walks through how to generate a GitLab OIDC token and use it to assume a misconfigured role, highlighting the risks of default settings in AWS.

Preview Release of the Migration Tool for the AWS SDK for Java 2.x

AWS has released a preview of a migration tool to help developers transition from AWS SDK for Java 1.x to 2.x, as 1.x is now in maintenance mode. This tool uses OpenRewrite, an open-source code refactoring tool, to automate much of the migration process. It currently supports most service SDK clients, except for AmazonS3Client, TransferManager, and DynamoDBMapper, and helps reduce the time and effort needed for the upgrade. Developers can use this tool with Maven or Gradle projects, choosing between preview (dryRun) or actual (run) modes to apply the changes.

Amazon’s Exabyte-Scale Migration from Apache Spark to Ray on Amazon EC2

Amazon’s Business Data Technologies (BDT) team is migrating from Apache Spark to Ray on Amazon EC2 to handle exabyte-scale data more efficiently. The switch is driven by the need to reduce data processing costs and time for their large business intelligence datasets. Apache Spark, though powerful, had started to show limitations with scalability and performance as their data grew. Ray, initially known for machine learning tasks, offered a more flexible and cost-effective solution with its distributed compute capabilities, reducing processing costs by 82% and improving data processing speeds significantly.

Unlock 1 Million RPS: Experience Triple the Speed with Valkey

Valkey 8.0, set for release in September 2024, introduces a new multi-threaded architecture that significantly boosts performance, increasing throughput by 230% to over 1 million requests per second and reducing latency by nearly 70%. This is achieved through an innovative I/O threading system, where dedicated worker threads handle tasks like reading commands and writing responses, freeing up the main thread to focus on executing commands. Valkey 8.0 also supports larger shards, improving performance for workloads that don't scale well horizontally, but comes with trade-offs like increased complexity in managing larger nodes.

kubeai: Private Open AI on Kubernetes

KubeAI is an open-source tool that allows users to run AI models like LLMs (Large Language Models), embeddings, and speech-to-text on Kubernetes. It provides an API compatible with OpenAI, letting users serve and scale models like Whisper and vLLM across CPU, GPU, and soon TPU infrastructure.

cyphernetes: A Kubernetes Query Language

Cyphernetes is a query language for Kubernetes inspired by Cypher (from Neo4j) that simplifies managing Kubernetes resources. Instead of complex `kubectl` commands, Cyphernetes lets users perform operations like finding and modifying deployments, services, and ingresses with clear, SQL-like syntax.

chartdb: Free and open-source database diagrams editor, visualize and design your DB with a single query.

ChartDB is an open-source, web-based tool for creating and editing database diagrams. With a single "Smart Query," users can instantly visualize their database schema, making it easy to understand and document database structures. It supports multiple databases like PostgreSQL, MySQL, and SQLite.

stack-auth: Open-source Auth0/Clerk alternative

ChartDB is a free, open-source tool for creating and editing database diagrams. It allows users to instantly visualize their database schema with a single query and supports databases like PostgreSQL, MySQL, and SQLite. Users can interactively edit schemas, export SQL scripts, and even use AI to generate migration scripts for switching between databases.

mariadb-operator: Run and operate MariaDB in a cloud native way

The MariaDB Operator allows users to manage MariaDB databases in a cloud-native environment using Kubernetes. It simplifies tasks like deploying and operating MariaDB instances through Custom Resource Definitions (CRDs), enabling features like high availability, automated backups, and flexible storage options.

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