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5 Things We Learned About Operational Resilience at SolarWinds Day

Operational Resilience is Strengthened with Strong Incident Response
Aligning Business and Technology Is Critical to Success
Tool Sprawl, Siloes, and Fragmentation Are Communication Issues
AI Continues to Become More Central to Effective IT Operations

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Amazon

293

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Simplifying Code Documentation with Amazon Q Developer

Amazon Q Developer's /doc agent automates README generation and updates, reducing time spent on documentation.
The /doc agent uses generative AI to analyze codebase and respect .gitignore files for documentation.
Users can create new READMEs or update existing ones with Amazon Q's /doc agent in their IDE.
For projects without documentation, selecting 'Create a README' initiates the process.
The /doc agent scans source files, summarizes, and generates documentation for the selected folder.
Documentation syncing assists in keeping documentation aligned with code changes.
Iterative improvement is enabled through feedback loops for comprehensive documentation.
Different levels of documentation creation are supported for modular projects.
Maintaining hierarchical documentation structure aids in specificity and manageability.
Amazon Q Developer's /doc agent helps automate and streamline documentation management for software projects.

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Dev

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When One Tech Stack Isn’t Enough: Orchestrating a Multi-Language Pipeline with Local FaaS

The article discusses orchestrating a multi-language pipeline using a local-first FaaS approach to handle real-time data processing across various systems.
The scenario involves using different languages and tools like Rust, Go, Python, Node.js, and Shell Script for different nodes in the pipeline.
Node 1 (Rust) focuses on high-performance ingestion, utilizing Rust's memory safety features and ownership model for handling high event throughput.
Node 2 (Go) deals with filtering and normalization, leveraging Go's concurrency features and ability to compile into a single binary for deployment flexibility.
Node 3 (Python) handles ML classification, benefiting from Python's ecosystem for data science tasks and ease of loading pretrained models.
Node 4 (Node.js) manages external service notifications, utilizing Node.js's event-driven nature for real-time hooks like Slack notifications, webhooks, etc.
Node 5 (Shell Script) focuses on archiving logs using classic CLI tools like tar and gzip, known for their reliability and efficiency in handling file archiving.
Data adapters play a crucial role in handling different data formats and ensuring seamless communication between nodes while keeping the underlying data format complexities abstracted.
By adopting a local-first FaaS mindset and unifying the pipeline into a single computational graph, the article highlights significant reductions in friction between teams working with different languages and tools.
The approach allows each team to focus on their specific node's functionality without being heavily dependent on other teams, thereby streamlining the overall data processing workflow.
Overall, the local-first FaaS approach proves beneficial for managing a multi-language environment, providing flexibility and efficiency in handling diverse tasks across the data processing pipeline.

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Dev

171

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Mastering the Backbone of Linux: The File System Structure You Must Know

The Linux file system serves as the backbone of the operating system, providing a structured way to store, manage, and access data essential for businesses and IT professionals.
Its hierarchical design, guided by the Filesystem Hierarchy Standard (FHS), ensures consistency and predictability across Linux distributions.
Key directories explored in the Linux file system include the root directory, user directories, system configuration, boot files, binary executables, device files, process information, temporary files, logs and variable data, mount points, and libraries.
Root directory (/) is crucial in organizing critical paths for enterprise systems, and IT professionals use it for maintaining file hierarchy efficiently.
User directories (/home and /root) are utilized by businesses to provide isolated workspaces for employees and by IT for privileged tasks.
System Configuration (/etc) stores critical configuration files for network settings and application configurations essential for businesses and IT teams.
Boot Files (/boot) are utilized for managing GRUB configuration files in dual-boot setups for testing and operational purposes in enterprises.
Binary Executables (/bin and /sbin) are used for essential and administrative commands by employees, businesses, and IT professionals.
Device Files (/dev) store information for managing storage devices efficiently by businesses and IT during troubleshooting or setup processes.
Process Information (/proc) provides real-time performance metrics for optimizing resource utilization in businesses and aiding system administrators in diagnosing performance issues.

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Dev

192

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🚀 10 DevOps Best Practices That Saved My Team (and Sanity)

Infrastructure as Code (IaC) using tools like Terraform, Pulumi, or AWS CloudFormation is crucial.
Automate tests, including unit tests, integration tests, and smoke tests, before deploying code.
Dockerize applications to improve portability, predictability, and production readiness.
Monitor everything but be cautious not to trigger alert fatigue, and use thresholds based on SLOs.

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Medium

243

7 Tools That Will Make You a More Productive DevOps Engineer

fzf is a command-line fuzzy finder that makes searching interactive and super fast.
tmux allows you to create multiple terminal sessions within a single window and manage remote servers.
fzf provides faster file and command searching, reducing the need for manual typing.
tmux is useful for keeping SSH sessions active, running multiple tasks in parallel, and remote server management.

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Dev

285

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🎉 2000 Followers on Dev.to – Thank You, DevOps Fam! 🙌

DevOps Challenge Hub has reached 2000 followers on Dev.to.
The journey of learning, sharing, and growing together in the DevOps space.
Emphasis on simplifying DevOps and cloud concepts for learners.
Future plans include more hands-on projects, emerging tech in DevOps, and collaborations.

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Devopsonline

365

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The Future of Banking: Embracing AI and Coreless Innovation

Traditional financial institutions are under pressure to modernise and adopt AI.
Legacy systems are hindering transformation efforts in financial institutions.
The future of banking involves adopting adaptable strategies and harnessing the benefits of new technologies.
The coreless banking model, embracing AI and open standards, offers a way forward for banks.

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Medium

193

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Grind LeetCode or Build Projects?

Build projects, then LeetCode.
Projects and open-source contributions are important for gaining experience and filling your resume with relevant content.
Having at least three unit-tested projects is recommended, which can be web or mobile applications accessible to others.
Grinding LeetCode is important for testing algorithms and data structures, which is often a requirement for top companies.

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Dev

378

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This Is Likely the Computing Technology that Supports the Most Data Sources

Enterprise data sources have evolved to include databases, files, APIs, streaming data, and more, requiring technologies to support multi-source computation.
The 'logical data warehouse' is a common approach for multi-source computation but faces limitations in supporting diverse data sources.
esProc is a technology that excels in multi-data source support without the need for heavy modeling, offering a lightweight approach and extensive connectivity capabilities.
esProc supports various data sources like relational databases, non-relational databases, file formats, message queues, big data platforms, APIs, and more.
Compared to other technologies, esProc not only supports a wider range of sources but also offers easier usability for cross-source computation.
esProc offers a simple and powerful scripting language, SPL, for cross-source computation, providing seamless connectivity and computation capabilities.
Users can easily extend new data sources in esProc without the need for complex development, enhancing flexibility and usability.
esProc prioritizes flexibility and extensibility over transparency, allowing for easier handling of complex and irregular data structures.
With seamless integration into mainstream application systems and flexible deployment options, esProc ensures a satisfying user experience and ease of integration.
esProc stands out for supporting a wide variety of data sources, offering extensibility, unified syntax, structured data format compatibility, and smooth integration with mainstream systems.
Overall, esProc emerges as a computing technology that supports a wide range of data sources while providing user-friendly experiences, quick extensibility, and powerful support.

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Dev

180

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My Learnings About Etcd

Etcd is a distributed key-value store, fully open-source and implemented in Golang.
It is a critical component of the control plane in Kubernetes, storing all cluster data in a key-value format.
Etcd is designed as a fault-tolerant and highly available system, utilizing the RAFT consensus algorithm for ensuring strong consistency.
Etcd uses the BoltDB storage engine and follows the B+ Tree design to provide consistent and predictable reads.

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Dev

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How to Build a Self-Service DevOps Platform (Platform Engineering Explained)

As organizations scale their DevOps practices, the demand for efficiency, autonomy, and standardization grows.
A Self-Service DevOps Platform is an internal platform that provides standardized workflows, automation, and tooling to enable developers to deploy, manage, and scale applications efficiently without requiring deep knowledge of infrastructure.
Key components of a Self-Service DevOps Platform include Infrastructure as Code, CI/CD Pipelines, Observability & Monitoring, Self-Service Portals, and Security & Compliance.
Benefits of implementing a Self-Service DevOps Platform include faster development cycles, developer autonomy, cost efficiency, scalability, and improved security.

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Dev

193

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Tired of Manual Deployments? Let AI Automate the Process.

Manual deployments are outdated and inefficient.
AI-powered deployment automation platforms like Kuberns are revolutionizing the process.
Kuberns eliminates repetitive tasks, enables faster shipping, reduces infrastructure costs, and provides smarter rollbacks and monitoring.
Automation is the future of deployment in 2025.

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Hackernoon

365

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A Kubernetes Special: Even More OpenTelemetry to Chew On

The article discusses the author's experience with presenting OpenTelemetry demos to varied audiences and the constant updates made to keep presentations engaging.
After a job loss due to an IT crisis, the author joined LoftLabs, working on vCluster, a cluster virtualization solution.
The demo underwent changes focusing on Kubernetes-related features, transitioning from Docker Compose to Helm for more intricate workload deployments.
Helm subcharts like Valkey, Traefik, Jaeger, PostgreSQL, and the OpenTelemetry components were utilized to optimize infrastructure setup.
The article highlights design choices, including using Traefik as an Ingress Controller and segmenting Docker Compose services into infrastructure and app groups.
Configuring access between host and virtual clusters, leveraging Traefik, and integrating OpenTelemetry Collector to monitor clusters are discussed.
The author details deploying and initializing PostgreSQL with scripts, utilizing Helm charts efficiently, and exploring Kubernetes instrumentation with OpenTelemetry.
A Quarkus component addition for showcasing OpenTelemetry integration and a summary of new features like Quarkus, vCluster, Helm usage, etc., are included.
The article concludes with a call for feedback and mentions missing components like .Net, showcasing a commitment to continuous improvement and expansion.
For more details, the article suggests exploring topics like Helm, OpenTelemetry Collector, Kubernetes auto-instrumentation, vCluster, Traefik, and Quarkus usage.
The author invites suggestions and contributions, embracing a collaborative approach for further enhancements in the tech landscape.

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Dev

176

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How to Create a Resource Group in Azure

Azure Resource Group is a logical unit where related Azure resources are grouped together.
It helps with organizing, managing permissions, applying policies, and facilitating resource deployment and deletion.
The process for creating an Azure Resource Group involves logging into the Azure account, accessing the Resource Group section, creating a new Resource Group, naming it, selecting the region, reviewing the details, and finally creating the Resource Group.
Once the Resource Group is created, resources can be added to it to manage them collectively.

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