menu
techminis

A naukri.com initiative

google-web-stories
Home

>

Devops News

Devops News

source image

Dev

1M

read

259

img
dot

Image Credit: Dev

Understanding and Inspecting Indexes in MySQL: A Comprehensive Guide

  • Indexes in MySQL help improve performance by reducing the data volume scanned for queries.
  • Inspecting and understanding indexes is crucial for database optimization and maintenance.
  • MySQL supports primary, unique, full-text, spatial, composite, and prefix indexes.
  • SHOW INDEX commands allow inspecting defined keys and their attributes in MySQL.
  • Understanding index structures, cardinality, and composite designs is essential for efficient querying.
  • Removing redundant indexes and optimizing composite designs can improve query performance.
  • Evaluation of existing indexes before adding new ones is important for query efficiency.
  • The information_schema.STATISTICS table provides a centralized view of all index metadata in a schema.
  • Automation tools like Releem can help track query performance and suggest index improvements.
  • Continuous monitoring and adjustment of indexes are essential for maintaining database performance.

Read Full Article

like

15 Likes

source image

Medium

1M

read

0

img
dot

Introducing DataSynclabs: A New Era for Decentralized AI Has Begun

  • DataSynclabs is launching a decentralized AI ecosystem inspired by swarm intelligence, where every contributor plays a part in building, training, and refining AI models.
  • Their mission is to break the centralized mold of AI by rethinking data processing, model governance, and scalability with transparency, equity, and resilience.
  • The ecosystem consists of Queen AI (Core Protocol), Worker Bees (Contributors), and Hive Infrastructure (Platform) working together in a three-layer structure.
  • $HVT (Hive Token) is the ecosystem's currency used for paying for compute jobs, staking for upgrades, rewarding contributors, and holders can decide on dataset approvals and more.

Read Full Article

like

Like

source image

Dev

1M

read

399

img
dot

Image Credit: Dev

How to Provide Secure Access to Your Kubernetes Clusters Using an Overlay Network

  • Overlay networks provide a solution for securing access to Kubernetes clusters without compromising protection.
  • Fine-grained access helps reduce the attack surface and simplifies access for non-developers in staging and testing environments.
  • Overlay networks like NetBird operate on top of existing network infrastructure, allowing secure peer-to-peer communication.
  • NetBird facilitates specifying access based on machines, ports, geolocations, and operating systems.
  • Deploying NetBird involves setting up the Kubernetes operator, creating configurations, and establishing secure connections to services.
  • Configuring NetBird involves installing agents on machines, creating access policies, configuring nameservers, and testing connections.
  • Using an overlay network like NetBird helps ensure secure access to internal services running in Kubernetes clusters without exposing them publicly.
  • Managing access to Kubernetes clusters and services for different teams becomes easier with NetBird's group-based access control.
  • NetBird and its Kubernetes operator are open-source, allowing users to explore and contribute to the project.
  • Implementing an overlay network like NetBird is a recommended security best practice for clusters not requiring public access.

Read Full Article

like

24 Likes

source image

Kubernetes

1M

read

354

img
dot

Image Credit: Kubernetes

Gateway API v1.3.0: Advancements in Request Mirroring, CORS, Gateway Merging, and Retry Budgets

  • Gateway API v1.3.0 introduces enhancements like percentage-based request mirroring, CORS filtering, Gateway merging, and retry budgets.
  • The release includes percentage-based request mirroring allowing users to mirror a subset of requests, enabling testing without impacting all client responses.
  • New experimental features in this release include CORS filtering for cross-origin resource sharing and XListenerSets for merging Listeners.
  • XListenerSets allow shared listeners across Gateways and enable delegation of listener configuration, such as TLS, to applications in different namespaces.
  • Retry budgets (XBackendTrafficPolicy) in v1.3.0 allow configuring limits on client-side retries for a destination Service over a specified interval.
  • To try out these features, install the Experimental channel Gateway API YAMLs and follow the Getting Started Guide.
  • Conformant implementations to Gateway API v1.3 experimental features include Airlock Microgateway, Cilium, Envoy Gateway, and Istio.
  • Users running Kubernetes 1.26 or later can leverage Gateway API v1.3 without needing to upgrade Kubernetes itself.
  • The community is encouraged to get involved, explore use-cases, try existing Gateway controllers, and participate in shaping the future of Gateway API.
  • Gateway API v1.3.0 signifies progress in Kubernetes routing APIs and offers opportunities for community engagement and feature exploration.

Read Full Article

like

21 Likes

source image

Hashicorp

1M

read

269

img
dot

Image Credit: Hashicorp

Terraform migrate 1.1 adds VCS workspace support and enhanced GitOps

  • Terraform migrate 1.1 adds VCS workspace support and enhanced GitOps for easier migration processes.
  • Infrastructure teams can now leverage automated Git-based migration flows, aligning with GitOps practices.
  • Specific updates in Terraform migrate 1.1 include VCS workspace support, Git control via provider-level git attributes, and stability/performance improvements.
  • This release enhances ease of use, adaptability to existing repositories, and overall stability for managing infrastructure with Terraform.

Read Full Article

like

16 Likes

source image

Dev

1M

read

40

img
dot

Image Credit: Dev

Load testing vs performance testing

  • Load testing, performance testing, and stress testing are often confused but have distinct purposes in testing applications under realistic conditions.
  • Performance testing encompasses load, stress, spike, and soak testing to evaluate how systems behave in various scenarios.
  • Load testing, a subset of performance testing, focuses on simulating expected user volume and traffic patterns.
  • Performance testing evaluates speed, scalability, and stability across different conditions, integrating throughout the software development lifecycle.
  • Load testing validates behavior under normal and peak usage conditions, answering critical questions about system capacity and response times.
  • Successful teams integrate performance testing throughout the development process, catching issues early and ensuring reliability under various conditions.
  • Performance testing scenarios should mirror actual user behavior and system architecture, combining business-critical user journeys with technical validation.
  • Gatling, a tool supporting multiple protocols, simplifies load testing with a no-code test builder and can be integrated into CI/CD pipelines.
  • Global scale capabilities, reliable results, cost management features, and reduced operational overhead make Gatling ideal for modern DevOps teams.
  • Gatling offers a seamless transition from the no-code approach to script-based testing in Java, JavaScript, Kotlin, or Scala for automated performance testing.

Read Full Article

like

2 Likes

source image

Dev

1M

read

152

img
dot

Image Credit: Dev

🚀 Deploying Artifacts to Multiple S3 Buckets Using AWS CodePipeline

  • Setting up an AWS CodePipeline for deploying artifacts to multiple S3 buckets is useful for scenarios like deploying static websites across different environments or regions.
  • Prerequisites include an AWS account with necessary permissions, two or more S3 buckets configured for static website hosting, and a source artifact stored in an S3 bucket.
  • The step-by-step setup involves creating a pipeline, adding a source stage with details of source bucket and object key, and adding deploy stages for each target bucket with actions like extracting files before deployment.
  • Benefits of this setup include automation that streamlines deployment, consistency in deployment artifacts across target buckets, and scalability to extend to more buckets or regions.

Read Full Article

like

9 Likes

source image

Microsoft

1M

read

318

img
dot

Image Credit: Microsoft

GitHub Secret Protection and GitHub Code Security for Azure DevOps

  • GitHub has launched standalone security products, GitHub Secret Protection and GitHub Code Security for Azure DevOps, following changes to GitHub Advanced Security.
  • GitHub Secret Protection for Azure DevOps is available for $19 per active committer per month, offering push protection, secret scanning alerts, and security overview.
  • GitHub Code Security for Azure DevOps is available for $30 per active committer per month, offering dependency alerts, CodeQL scanning, security findings for third-party tools, and security overview.
  • Customers can start using Secret Protection and Code Security plans as soon as it's available in their organization, with no disruption to the current Advanced Security experience for existing customers.

Read Full Article

like

19 Likes

source image

Dev

1M

read

94

img
dot

Image Credit: Dev

Top 8 GitOps Tools You Should Know

  • GitOps is a methodology that uses Git repositories as the single source of truth for software development and infrastructure management.
  • GitOps tools automate software delivery using declarative configuration, IaC, and CI/CD, following GitOps principles.
  • Top GitOps tools include Spacelift, Argo CD, Flux CD, Codefresh, GitLab, Terraform, OpenTofu, and Werf.
  • Spacelift automates IaC workflows, supports various technologies, and includes drift detection capabilities.
  • Argo CD offers continuous delivery for Kubernetes, syncing manifests from Git repositories to clusters.
  • Flux CD provides fully automated state reconciliation with integration options for cloud providers.
  • Codefresh is an enterprise-scale SaaS GitOps solution with monitoring dashboards and debugging support.
  • Terraform, known for IaC, extends GitOps to infrastructure configuration allowing automated changes based on repository content.
  • OpenTofu, an open-source alternative to Terraform, enables syncing of infrastructure state with repository content.
  • Werf is a CI/CD system automating application delivery to Kubernetes clusters based on Git repositories.

Read Full Article

like

5 Likes

source image

Dev

1M

read

121

img
dot

Image Credit: Dev

How to Become a DevOps Engineer

  • DevOps Engineer bridges the gap between development and operations to ensure smooth and continuous software delivery.
  • Skills needed to become a DevOps Engineer include programming languages, automation tools, containerization, cloud platforms, CI/CD pipelines, configuration management, IaC, monitoring, and soft skills.
  • DevOps Engineers focus on infrastructure, automation, and deployment, while developers focus on building applications and implementing features.
  • To prepare for a DevOps career, hands-on experience with tools like Docker, Kubernetes, Terraform, Ansible, monitoring tools, and creating CI/CD pipelines are essential.

Read Full Article

like

7 Likes

source image

Dev

1M

read

237

img
dot

Image Credit: Dev

How to Deploy a Full Stack Application to Koyeb Using Docker Compose, Terraform, and GitHub Actions

  • Deploying a full-stack application to a cloud platform can be made manageable and reliable by leveraging containerization, Infrastructure as Code (IaC), and automated CI/CD pipelines.
  • This guide covers using Docker Compose, Terraform, and GitHub Actions to deploy a full-stack application on Koyeb for enhanced consistency and efficiency.
  • Prerequisites include having a Koyeb account, Koyeb API token, a GitHub repository with application code and Docker Compose files, and basic familiarity with Terraform and GitHub Actions.
  • Terraform is used to provision and manage the deployment infrastructure on Koyeb using the koyeb_app and koyeb_service resources defined to automate deployment from a GitHub repository.
  • Setting up the Koyeb API token in GitHub Secrets securely allows authentication for Terraform to interact with your Koyeb account during deployment.
  • The GitHub Actions workflow file automates the deployment process by checking out code, setting up Terraform, and deploying the application using the provided Terraform scripts.
  • After pushing the code to trigger deployment, monitoring the deployment progress in GitHub Actions helps track the workflow run and ensures successful deployment on Koyeb.
  • By following this guide, you can achieve a seamless deployment of your full-stack application on Koyeb using Docker Compose, Terraform, and GitHub Actions.
  • This approach enhances deployment consistency and efficiency while providing a reliable, repeatable way to manage the deployment environment.
  • For more practical DevOps walkthroughs, you can explore additional content by EphraimX and follow for future updates in this domain.

Read Full Article

like

14 Likes

source image

Dev

1M

read

296

img
dot

Image Credit: Dev

Load balancing multiple Rathole tunnels with Traefik HTTP and TCP routers

  • The article discusses how to load balance multiple Rathole tunnels and home servers using Traefik HTTP and TCP routers.
  • It addresses the limitation of needing one VPS per home server by introducing load balancing for traffic distribution.
  • The setup requires a working Rathole tunnel setup, multiple home servers, and Traefik HTTP and TCP routers.
  • The primary challenge arises from the inability to bind more than one port to ports 80 and 443 simultaneously.
  • To resolve this, a tool for load balancing traffic between tunnels, such as Traefik, is introduced.
  • The article explains in detail the implementation of Traefik HTTP and TCP routers for load balancing multiple tunnels.
  • Traefik is used to route HTTP traffic and handle encrypted HTTPS traffic in passthrough mode.
  • The configuration involves defining HTTP routers with HostRegexp() matcher and TCP routers with HostSNIRegexp() matcher.
  • Rathole server configurations for 2 HTTP/HTTPS tunnel pairs per home server are detailed in the article.
  • The setup aims to enable users to expose multiple home servers in a cost-effective and practical manner.

Read Full Article

like

17 Likes

source image

Dev

1M

read

300

img
dot

Image Credit: Dev

From Prototype to Production - Local Kubernetes: Our AI Resume Matcher's Journey

  • The article discusses the transition of an AI Resume Matcher from a prototype to production using Local Kubernetes.
  • Key learnings include containerizing the Java Spring Boot application with Docker, setting up a local Kubernetes environment, crafting Kubernetes deployment manifests, configuring Google Cloud authentication for Vertex AI, and exposing the application through a Kubernetes Service.
  • Local Kubernetes offers advantages such as mimicking production environments, handling growth, building cloud-ready skills, and ensuring standardized deployments.
  • Prerequisites include having the AI Resume Matcher project code, Docker Desktop for local Kubernetes, and a Google Cloud account with Vertex AI enabled.
  • The process involves containerizing the application, launching Kubernetes with Docker Desktop, orchestrating with Kubernetes using manifest files, setting up Google Cloud authentication securely, and deploying the application.
  • For Google Cloud authentication, a Service Account and JSON key file are utilized to create a Kubernetes Secret for secure authentication within the Kubernetes pod.
  • Testing the deployed application involves checking pod status, verifying deployment, inspecting application logs, and sending a test request to ensure proper functioning.
  • By following the steps outlined, developers can deploy the AI Resume Matcher on a local Kubernetes cluster, gaining practical experience with DevOps practices and cloud-native technologies.
  • The journey from a Docker Compose setup to a Kubernetes cluster deployment enhances the application's robustness and scalability, paving the way for production readiness.
  • Overall, the article provides a comprehensive guide to transitioning an AI application from a basic prototype to a fully orchestrated production environment while showcasing key DevOps principles.

Read Full Article

like

18 Likes

source image

Dev

1M

read

372

img
dot

Image Credit: Dev

Code, Charts, and Checklists: Dev Workflows That Ship Faster

  • Shipping code fast involves building a workflow that removes bottlenecks, increases visibility, and keeps developers focused.
  • Key elements for faster development include clean code practices, visual progress tracking through charts, and dependable checklists.
  • Issues in dev workflows include overloaded sprint boards, missed deadlines, rushed code reviews, and team burnout.
  • Adopting a Minimum Viable Product (MVP) approach reduces wasted effort, shortens feedback loops, and keeps development cycles focused.
  • Charts like burndown charts provide real-time visibility to track progress, spot scope creep, and promote team accountability.
  • Checklists automate repetitive tasks, minimize errors, speed up onboarding, and free up mental energy for problem-solving.
  • Integrating code practices, charts, and checklists into a cohesive workflow using smart project management platforms enhances planning, execution, tracking, and alignment with product goals.
  • By combining lean coding, visual charts, and practical checklists, developers can create effective workflows that scale with the team.
  • Strategies for efficient developer workflows include starting with an MVP mindset, utilizing burndown charts, and implementing templates and checklists.
  • These proven strategies help developer teams ship on time and manage the development lifecycle effectively.

Read Full Article

like

22 Likes

source image

Dev

1M

read

336

img
dot

Image Credit: Dev

Why Developers and Operations People Fight (And How to Stop Being Caught in the Middle)

  • DevOps is a collaboration between developers and operations to ensure successful outcomes in tech projects.
  • Developers focus on building features like login buttons, algorithms, and chat features, while operations ensure functionality and reliability.
  • Tension arises due to differing priorities: developers aim for speed and innovation, while operations prioritize stability and security.
  • High dev-ops collaboration leads to faster deployments, quicker incident recovery, and lower change failure rates.
  • Effective solutions involve promoting communication, setting shared goals, building common understandings, and learning both development and operations.
  • Tools like Docker, CI/CD, and monitoring tools help bridge the gap between developers and operations.
  • Successful engineers understand both development and operations, stay curious, and ask critical questions about system impacts.
  • Companies thrive when all team members work together towards common goals and understanding.
  • Beginners are advised to learn Docker basics, understand monitoring, practice deployments, and grasp incident response.
  • Continuous growth and progress are vital in tech, showcasing improvement through actions rather than just announcements.
  • Aiming for consistency and teamwork, understanding different perspectives, and aiming towards growth are essential in navigating dev-ops dynamics.

Read Full Article

like

20 Likes

For uninterrupted reading, download the app