#OpenSourceTools

[adafruit]

A mini GPS from uBlox with I2C and UART 🛰️📡🔧

The SAM-M8Q

is an entry-level 'all in one' GPS from uBlox - it comes with both UART and I2C interfaces plus a built-in antenna so it's ready to go 'out of the box.' It's also fairly small, so we decided to try and make a little breakout for it. It exposes both interfaces, but we expect most folks will like using the Stemma QT port for instant I2C interfacing. We gotta dig into uBlox's interface since we expect the I2C to be a little more complex than the PA1010 we've used.

[wesuggestsoftware1]

7 Best Open Source Marketing Automation Software for Free

For businesses seeking cost-effective marketing automation, these free open-source tools offer powerful features. Leadsius is ideal for startups, offering intuitive campaign management and lead tracking. SalesAutoPilot blends CRM and marketing automation for smoother workflows. Jumplead helps convert visitors into leads through smart forms and real-time engagement. Mautic stands out with its robust customization, email marketing, and advanced analytics. OpenEMM focuses on professional email campaign management with detailed reports. Act-On (while limited in free use) supports multi-channel automation for growing teams. Finally, Sage CRM integrates marketing with sales functions, providing clear visibility and control across customer journeys.

[hawskstack]

🔄 Backing Up and Restoring Kubernetes Block and File Volumes – No-Code Guide

Kubernetes has become a foundational platform for deploying containerized applications. But as more stateful workloads enter the cluster — like databases and shared storage systems — ensuring data protection becomes critical.

This no-code guide explores how to back up and restore Kubernetes block and file volumes, the differences between storage types, and best practices for business continuity and disaster recovery.

📌 What Is Kubernetes Volume Backup & Restore?

In Kubernetes, Persistent Volumes (PVs) store data used by pods. These volumes come in two main types:

Block Storage: Raw devices formatted by applications (e.g., for databases).

File Storage: File systems shared between pods (e.g., for media files or documents).

Backup and restore in this context means protecting this stored data from loss, corruption, or accidental deletion — and recovering it when needed.

Block vs 📂 File Storage: What's the Difference?

FeatureBlock StorageFile StorageUse CaseDatabases, apps needing low latencyMedia, documents, logsAccessSingle node accessMulti-node/shared accessExampleAmazon EBS, OpenStack CinderNFS, CephFS, GlusterFS

Understanding your storage type helps decide the right backup tool and strategy.

🔒 Why Backing Up Volumes Is Essential

🛡️ Protects critical business data

💥 Recovers from accidental deletion or failure

📦 Enables migration between clusters or cloud providers

🧪 Supports safe testing using restored copies

🔧 Common Backup Methods (No Code Involved)

1. Snapshots (for Block Volumes)

Most cloud providers and storage backends support volume snapshots, which are point-in-time backups of storage volumes. These can be triggered through the Kubernetes interface using storage plugins called CSI drivers.

Benefits:

Fast and efficient

Cloud-native and infrastructure-integrated

Easy to automate with backup tools

2. File Backups (for File Volumes)

For file-based volumes like NFS or CephFS, the best approach is to regularly copy file contents to a secure external storage location — such as object storage or an offsite file server.

Benefits:

Simple to implement

Granular control over which files to back up

Works well with shared volumes

3. Backup Tools (All-in-One Solutions)

Several tools offer full platform support to handle Kubernetes volume backup and restore — with user-friendly interfaces and no need to touch code:

Velero: Popular open-source tool that supports scheduled backups, volume snapshots, and cloud storage.

Kasten K10: Enterprise-grade solution with dashboards, policy management, and compliance features.

TrilioVault, Portworx PX-Backup, and Rancher Backup: Also offer graphical UIs and seamless Kubernetes integration.

✅ Backup Best Practices for Kubernetes Volumes

🔁 Automate backups on a regular schedule (daily/hourly)

🔐 Encrypt data at rest and in transit

🌍 Store backups in a different location/region from the primary cluster

📌 Use labels to categorize backups by application or environment

🧪 Periodically test restore processes to validate recoverability

♻️ How Restoration Works (No Coding Required)

Restoring volumes in Kubernetes depends on the type of backup:

For snapshots, simply point new volumes to an existing snapshot when creating them again.

For file backups, use backup tools to restore contents back into the volume or re-attach to new pods.

For full-platform backup tools, use the interface to select a backup and restore it — including associated volumes, pods, and configurations.

Many solutions provide dashboards, logs, and monitoring to confirm that restoration was successful.

🚀 Summary: Protect What Matters

As Kubernetes powers more business-critical applications, backing up your block and file volumes is no longer optional — it’s essential. Whether using built-in snapshots, file-based backups, or enterprise tools, ensure you have a backup and recovery plan that’s tested, automated, and production-ready.

Your Kubernetes environment can be resilient and disaster-proof — with zero code required.

For more info, Kindly follow: Hawkstack Technologies

[forlinx]

Buildroot App Integration on Allwinner A40i: Step-by-Step

1️⃣ Create package/helloworld directory

2️⃣ Write Config.in + helloworld.mk (case-sensitive!)

3️⃣ Enable in sun8iw11p1_hf_defconfig

4️⃣ make menuconfig → compile → pack

💡 Key Insights:

.mk scripts glue Buildroot’s build system to your app’s Makefile

Error Alert: Directly overwriting .config breaks builds! Use savedefconfig instead

Final binary lands in /bin post-compilation 📦

Allwinner A40i system on module

👉 Contact us: sales@forlinx.com

[nitsan]

Apache Solr for TYPO3: Advanced Search Features for Your TYPO3 Website

Have you ever used a search bar on a website only to find results that are slow, confusing, or irrelevant? It can be really frustrating, especially when you're in a hurry to find important information. This problem happens to many TYPO3 websites because the basic built-in search often isn't powerful enough. Fortunately, Apache Solr for TYPO3 provides an excellent solution to make your search faster, smarter, and easier for all users.

What is Apache Solr?

Apache Solr is a free, open-source search engine platform designed to handle large amounts of data quickly and efficiently. It’s built on Apache Lucene, a robust search technology, and is widely used because of its speed and reliability. Solr indexes your website’s content effectively, allowing visitors to find exactly what they're looking for in seconds.

Main Features of Apache Solr

Apache Solr offers several powerful features to enhance your website's search capability:

Fast Results: Delivers instant search results, even for large websites with thousands of pages.

Faceted Search: Enables users to narrow down search results by using filters such as categories, tags, or dates.

Autocomplete and Spell-Checking: Offers suggestions as users type and corrects minor spelling errors automatically.

Synonym Support: Understands and matches similar words, ensuring accurate results even if users use different terms.

Document Indexing: Allows users to search within documents like PDFs, Word files, and Excel sheets, not just webpage text.

Why Apache Solr is Essential for TYPO3 Websites

The default TYPO3 search is limited and slow, particularly as your site grows. Apache Solr solves this by providing:

Enhanced Speed: Quickly searches large amounts of content without slowing down your site.

Better User Experience: Provides users with clear, relevant results, encouraging them to stay longer on your site.

Customization Options: Easily tailor the search functionality to your specific website needs, ensuring relevant results every time.

Scalability: Handles growth efficiently, making it perfect for websites that continue to add content.

Easy Setup and Useful Extensions

Setting up Apache Solr on your TYPO3 site is straightforward:

Install the Solr Extension: Use the TYPO3 backend or Composer to install the EXT:solr extension.

Configure Your Site: Adjust simple settings using TypoScript and ensure proper indexing by adding markers around your content.

Regularly Update Indexes: Schedule automatic content indexing via TYPO3's scheduler to keep your search updated.

TYPO3 also provides helpful extensions to make your setup easier:

EXT:solr: The core extension linking TYPO3 with Apache Solr, enabling all advanced search functionalities.

solr file_indexer: Helps index file contents so users can search inside documents.

DDEV Apache Solr for TYPO3: A development tool to easily set up and test Solr locally.

Benefits of Implementing Apache Solr

By integrating Apache Solr into your TYPO3 website, you gain:

Improved Site Engagement: Visitors stay longer as they easily find what they need.

Increased Efficiency: Reduces the effort needed to find important information, benefiting both users and administrators.

Professional Search Experience: Gives your website a polished, professional feel, enhancing user trust and satisfaction.

Conclusion

Apache Solr significantly upgrades your TYPO3 site's search capability, providing fast, accurate, and user-friendly results. It's easy to set up, customize, and maintain, making it a valuable tool for improving your website’s performance. Start using Apache Solr today to enhance the search experience for your users and watch your website engagement grow!

[bluelupinblogs]

7 Trending Open Source Tools for Backend Developers in 2025

Looking to supercharge your backend development game? Check out these powerful open-source tools that are making waves in 2025! From seamless API management to efficient database solutions, these tools are must-haves for any developer aiming to stay ahead.

Which one’s your favorite? Let us know in the comments! 👇

[nexttechtitans123]

Looking for the best open-source tools for user interface design? 🌟 Discover how these tools can empower your creativity while staying budget-friendly. Check out the latest insights here 💻✨

[techvibehub]

Open Source Tools for Data Science: A Beginner’s Toolkit

Data science is a powerful tool used by companies and organizations to make smart decisions, improve operations, and discover new opportunities. As more people realize the potential of data science, the need for easy-to-use and affordable tools has grown. Thankfully, the open-source community provides many resources that are both powerful and free. In this blog post, we will explore a beginner-friendly toolkit of open-source tools that are perfect for getting started in data science.

Why Use Open Source Tools for Data Science?

Before we dive into the tools, it’s helpful to understand why using open-source software for data science is a good idea:

1. Cost-Effective: Open-source tools are free, making them ideal for students, startups, and anyone on a tight budget.

2. Community Support: These tools often have strong communities where people share knowledge, help solve problems, and contribute to improving the tools.

3. Flexible and Customizable: You can change and adapt open-source tools to fit your needs, which is very useful in data science, where every project is different.

4. Transparent: Since the code is open for anyone to see, you can understand exactly how the tools work, which builds trust.

Essential Open Source Tools for Data Science Beginners

Let’s explore some of the most popular and easy-to-use open-source tools that cover every step in the data science process.

 1. Python

The most often used programming language for data science is Python. It's highly adaptable and simple to learn.

Why Python?

  - Simple to Read: Python’s syntax is straightforward, making it a great choice for beginners.

  - Many Libraries: Python has a lot of libraries specifically designed for data science tasks, from working with data to building machine learning models.

  - Large Community: Python’s community is huge, meaning there are lots of tutorials, forums, and resources to help you learn.

Key Libraries for Data Science:

  - NumPy: Handles numerical calculations and array data.

  - Pandas: Helps you organize and analyze data, especially in tables.

  - Matplotlib and Seaborn: Used to create graphs and charts to visualize data.

  - Scikit-learn: A powerful tool for machine learning, offering easy-to-use tools for data analysis.

 2. Jupyter Notebook

Jupyter Notebook is a web application where you can write and run code, see the results, and add notes—all in one place.

Why Jupyter Notebook?

  - Interactive Coding: You can write and test code in small chunks, making it easier to learn and troubleshoot.

  - Great for Documentation: You can write explanations alongside your code, which helps keep your work organized.

  - Built-In Visualization: Jupyter works well with visualization libraries like Matplotlib, so you can see your data in graphs right in your notebook.

 3. R Programming Language

R is another popular language in data science, especially known for its strength in statistical analysis and data visualization.

Why R?

  - Strong in Statistics: R is built specifically for statistical analysis, making it very powerful in this area.

  - Excellent Visualization: R has great tools for making beautiful, detailed graphs.

  - Lots of Packages: CRAN, R’s package repository, has thousands of packages that extend R’s capabilities.

Key Packages for Data Science:

  - ggplot2: Creates high-quality graphs and charts.

  - dplyr: Helps manipulate and clean data.

  - caret: Simplifies the process of building predictive models.

 4. TensorFlow and Keras

TensorFlow is a library developed by Google for numerical calculations and machine learning. Keras is a simpler interface that runs on top of TensorFlow, making it easier to build neural networks.

Why TensorFlow and Keras?

  - Deep Learning: TensorFlow is excellent for deep learning, a type of machine learning that mimics the human brain.

  - Flexible: TensorFlow is highly flexible, allowing for complex tasks.

  - User-Friendly with Keras: Keras makes it easier for beginners to get started with TensorFlow by simplifying the process of building models.

 5. Apache Spark

Apache Spark is an engine used for processing large amounts of data quickly. It’s great for big data projects.

Why Apache Spark?

  - Speed: Spark processes data in memory, making it much faster than traditional tools.

  - Handles Big Data: Spark can work with large datasets, making it a good choice for big data projects.

  - Supports Multiple Languages: You can use Spark with Python, R, Scala, and more.

 6. Git and GitHub

Git is a version control system that tracks changes to your code, while GitHub is a platform for hosting and sharing Git repositories.

Why Git and GitHub?

  - Teamwork: GitHub makes it easy to work with others on the same project.

  - Track Changes: Git keeps track of every change you make to your code, so you can always go back to an earlier version if needed.

  - Organize Projects: GitHub offers tools for managing and documenting your work.

 7. KNIME

KNIME (Konstanz Information Miner) is a data analytics platform that lets you create visual workflows for data science without writing code.

Why KNIME?

  - Easy to Use: KNIME’s drag-and-drop interface is great for beginners who want to perform complex tasks without coding.

  - Flexible: KNIME works with many other tools and languages, including Python, R, and Java.

  - Good for Visualization: KNIME offers many options for visualizing your data.

 8. OpenRefine

OpenRefine (formerly Google Refine) is a tool for cleaning and organizing messy data.

Why OpenRefine?

  - Data Cleaning: OpenRefine is great for fixing and organizing large datasets, which is a crucial step in data science.

  - Simple Interface: You can clean data using an easy-to-understand interface without writing complex code.

  - Track Changes: You can see all the changes you’ve made to your data, making it easy to reproduce your results.

 9. Orange

Orange is a tool for data visualization and analysis that’s easy to use, even for beginners.

Why Orange?

  - Visual Programming: Orange lets you perform data analysis tasks through a visual interface, no coding required.

  - Data Mining: It offers powerful tools for digging deeper into your data, including machine learning algorithms.

  - Interactive Exploration: Orange’s tools make it easier to explore and present your data interactively.

 10. D3.js

D3.js (Data-Driven Documents) is a JavaScript library used to create dynamic, interactive data visualizations on websites.

Why D3.js?

  - Highly Customizable: D3.js allows for custom-made visualizations that can be tailored to your needs.

  - Interactive: You can create charts and graphs that users can interact with, making data more engaging.

  - Web Integration: D3.js works well with web technologies, making it ideal for creating data visualizations for websites.

How to Get Started with These Tools

Starting out in data science can feel overwhelming with so many tools to choose from. Here’s a simple guide to help you begin:

1. Begin with Python and Jupyter Notebook: These are essential tools in data science. Start by learning Python basics and practice writing and running code in Jupyter Notebook.

2. Learn Data Visualization: Once you're comfortable with Python, try creating charts and graphs using Matplotlib, Seaborn, or R’s ggplot2. Visualizing data is key to understanding it.

3. Master Version Control with Git: As your projects become more complex, using version control will help you keep track of changes. Learn Git basics and use GitHub to save your work.

4. Explore Machine Learning: Tools like Scikit-learn, TensorFlow, and Keras are great for beginners interested in machine learning. Start with simple models and build up to more complex ones.

5. Clean and Organize Data: Use Pandas and OpenRefine to tidy up your data. Data preparation is a vital step that can greatly affect your results.

6. Try Big Data with Apache Spark: If you’re working with large datasets, learn how to use Apache Spark. It’s a powerful tool for processing big data.

7. Create Interactive Visualizations: If you’re interested in web development or interactive data displays, explore D3.js. It’s a fantastic tool for making custom data visualizations for websites.

Conclusion

Data science offers a wide range of open-source tools that can help you at every step of your data journey. Whether you're just starting out or looking to deepen your skills, these tools provide everything you need to succeed in data science. By starting with the basics and gradually exploring more advanced tools, you can build a strong foundation in data science and unlock the power of your data.

[osintelligence]

https://bit.ly/3RnKL4Q - 🛠️ Mosint: A New Open-Source Email OSINT Tool: Developed by Alp Keskin, Mosint is designed for efficient email investigations. It stands out for its speed, pulling data asynchronously from multiple services. This tool is ideal for security tests involving leaked email addresses. #Mosint #EmailOSINT #CyberSecurityTool 📧 Features of Mosint: The tool offers fast email scanning, is lightweight on resources, and features email verification, social media checks, data breach analysis, and more. It outputs results to a JSON file, simplifying data management for security researchers. #EmailSecurity #DataBreachAnalysis 🌐 Future Enhancements: Keskin plans to integrate more services into Mosint and may develop a Mosint API service. This indicates ongoing improvements to the tool's capabilities in email security and data analysis. Mosint is currently available for free on GitHub. #CyberSecurityInnovation #OpenSourceTools 🔍 Other Noteworthy Open-Source Tools: In addition to Mosint, there are several open-source tools worth considering for various cybersecurity needs: ➡️ Vigil: LLM security scanner ➡️ AWS Kill Switch: Incident response tool ➡️ PolarDNS: DNS server for security evaluations ➡️ k0smotron: Kubernetes cluster management ➡️ Kubescape 3.0: Kubernetes security enhancement ➡️ Logging Made Easy: Log management solution from CISA ➡️ GOAD: Practice environment for Active Directory attacks ➡️ Wazuh: XDR and SIEM system ➡️ Yeti: Threat intelligence repository ➡️ BinDiff: Binary file comparison tool ➡️ LLM Guard: Toolkit for securing Large Language Models ➡️ Velociraptor: Digital forensics and incident response tool These tools demonstrate the diverse range of open-source solutions available for enhancing cybersecurity and digital forensics.

[gmtasoftware]

𝗦𝘁𝗼𝗽 𝗣𝗮𝘆𝗶𝗻𝗴 𝗳𝗼𝗿 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲: 𝟭𝟬 𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 𝗦𝗮𝗮𝗦 𝗧𝗼𝗼𝗹𝘀 𝘁𝗼 𝗦𝗹𝗮𝘀𝗵 𝗬𝗼𝘂𝗿 𝗖𝗼𝘀𝘁𝘀💸💻

In today’s digital age, businesses, software development companies, and individuals alike rely on software tools to run their operations efficiently From customer relationship management CRM … https://medium.com/@gmtasoftware/stop-paying-for-software-10-open-source-saas-tools-to-slash-your-costs-2c8fe3f1b213 Stay Informed: Check Out Our @gmtasoftware Latest #mediumarticle 👉 https://medium.com/@gmtasoftware

𝗖𝗼𝗻𝗻𝗲𝗰𝘁 𝘄𝗶𝘁𝗵 𝘂𝘀 -: 📝𝗘𝗺𝗮𝗶𝗹 - 𝗶𝗻𝗳𝗼@𝗴𝗺𝘁𝗮𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲.𝗰𝗼𝗺 🌐𝗩𝗶𝘀𝗶𝘁 𝘂𝘀- https://www.gmtasoftware.com/ 📞𝗖𝗼𝗻𝘁𝗮𝗰𝘁 - 0141-4022847

#OpenSourceTools #SaaSAlternatives #FreeSoftware #OpenSourceSaaS #CostCuttingTech #TechForBusiness #DigitalTools #StartupTools #TechSavings #GMTAsoftware #MediumArticle #BusinessEfficiency #SoftwareDevelopment #OpenSourceCommunity

[hawskstack]

🚀 Istio Service Mesh Essentials: What You Need to Know

In today’s cloud-native world, managing microservices at scale requires more than just containers and Kubernetes. That’s where Istio, a powerful open-source service mesh, steps in — offering observability, security, and traffic control for your applications without changing your code.

🔍 What Is Istio?

Istio is a service mesh that provides a uniform way to secure, connect, and observe microservices. It works by injecting lightweight proxies (Envoy) alongside services (a pattern known as the sidecar pattern), allowing developers to offload network-level concerns like:

Service discovery

Load balancing

Traffic routing

Metrics collection

Security policies

⚙️ Key Components of Istio

Envoy Proxy A high-performance proxy that intercepts all incoming and outgoing traffic for the service it’s attached to.

Pilot Manages service discovery and traffic management.

Citadel Handles strong identity and certificate management for mutual TLS.

Mixer (Deprecated in recent versions) Was used for policy enforcement and telemetry collection. Now replaced by extensions and telemetry APIs.

Istiod A simplified control plane that consolidates the roles of Pilot, Citadel, and others in recent Istio releases.

🔐 Why Use Istio?

✅ Security: Enforce mutual TLS, fine-grained access policies, and encrypt service-to-service communication.

✅ Traffic Management: Split traffic between service versions for canary deployments, A/B testing, or blue-green releases.

✅ Observability: Automatically generate metrics, logs, and distributed traces for all services using tools like Prometheus, Grafana, and Jaeger.

✅ Resilience: Implement retries, timeouts, and circuit breakers without touching application code.

🌐 Istio in the Real World

Imagine a microservices app running on Kubernetes. Instead of each service implementing its own security and logging, Istio takes care of these concerns at the infrastructure layer, freeing developers to focus on core functionality.

Getting Started

You can install Istio on Kubernetes using the istioctl CLI or Helm charts. Once installed:

Label your namespace for Istio injection

Deploy services

Use VirtualServices and DestinationRules to control traffic

Monitor traffic using Prometheus and Kiali dashboards

🔚 Conclusion

Istio is an essential tool for organizations operating microservices in production. It reduces complexity, enhances security, and brings deep insights into service behavior — all without requiring code changes.

Whether you’re just getting started or scaling a mature environment, Istio Service Mesh brings enterprise-grade networking and observability to your cloud-native stack.

[weflowtips]

🌟 Webflow Tip of the Day

“Supercharge Webflow with Supabase: Add Realtime + Auth + SQL Power”

Want to go beyond static CMS in Webflow? Integrate Supabase — an open-source Firebase alternative — to add real database features like realtime data, auth, row-level security, and more.

🔧 Top Benefits of Using Supabase with Webflow:

✅ Database as a service – Store and manage structured data just like SQL ✅ User Authentication – Email/password, magic links, or OAuth (perfect for gated dashboards) ✅ Realtime Data Sync – Update Webflow UI with Supabase events via JavaScript ✅ Secure Access – Set row-level access rules (great for multi-user projects) ✅ API Ready – Fetch and push data using REST or Supabase client library

🧠 Pro Trick: Use Supabase + Wized or custom JS to fetch user-specific data and show personalized content inside Webflow. Combine with hidden Webflow attributes like data-user-id for seamless logic-driven UI.

🎯 Perfect For:

No-code SaaS dashboards

Gated communities

Job boards, CRMs, or listing platforms

Multi-role web apps

📌 Need quality Webflow development or a custom solution? Check out my work here: 🌐 Portfolio: www.webflowwork.com 🎯 Upwork: https://bit.ly/4iu6AKd 🎯 Fiverr: https://bit.ly/3EzQxNd

#WebflowTips #Supabase #WebflowCMS #Wized #WebflowExperts #RealtimeApps #NoCodeSaaS #WebflowIndia #OpenSourceTools #FirebaseAlternative #WizedIntegration #WebflowDevelopment #MadeInWebflow #FrontendDev

[reneleijen]

EFF lanceert tool om IMSI-catchers opsporingsdiensten te detecteren

In de VS heeft burgerrechtenorganisatie EFF een gratis opensourcetool gelanceerd om IMSI-catchers van opsporingsdiensten te detecteren. Deze ‘Rayhunter‘ onderschept, bewaart en analyseert – realtime – het controleverkeer tussen de mobile hotspot waarop de software draait en de zendmast waarmee die verbonden is. Bij een verdachte activiteit wordt de gebruiker gewaarschuwd; opgeslagen logs worden…

[windmillcode]

🚀 **Exciting Updates for LibTracker - The Ultimate SBOM Tool!** 🚀

🚀 **Exciting Updates for LibTracker - The Ultimate SBOM Tool!** 🚀

📣 **Greetings to all LibTracker users!**

LibTracker is your go-to Visual Studio Code extension to take control of your apps. Quickly identify and resolve outdated versions, security vulnerabilities, and problematic licensing with ease.

🎉 **Milestone Achieved**:

We’re thrilled to announce that LibTracker has surpassed **100 users** since our launch on **November 5th**! Thank you for your support and trust in our tool.

🔗 **Try LibTracker Now**:

Available on the VSCode Marketplace:

[Download LibTracker](https://marketplace.visualstudio.com/items?itemName=windmillcode-publisher-0.lib-tracker)

---

✨ **Major Update: App Detail Page** ✨

LibTracker now provides detailed insights into each app in your project:

- **Dependency Info**: View detailed dependency relationships.

- **Version Info**: Identify outdated versions at a glance.

- **License Info**: Ensure compliance with licensing requirements.

- **Progress Tracking**: This info takes a long time to retrieve dont be tricked into thinking it has hanged

---

💡 **What’s Next?**

We’re working on exciting new features to take LibTracker to the next level:

1. **npm App Focus**: Using npm as a model for enhanced functionality across all apps.

2. **Security Information**: Integrate vulnerability insights to keep your projects secure.

3. **Advanced Package Management**:

   - Add or update packages.

   - Choose specific versions or the latest version.

   - Create snapshots to rollback changes if updates fail.

   - Bulk operations: Import, append, export dependencies.

4. **Performance Enhancements**:

   - Cache detailed dependency HTTP API calls.

   - Refresh logic for improved efficiency.

5. **Coming Soon Notifications**: Alerts for upcoming features on inactive buttons.

---

🔍 **Community Call**:

We’d love to hear your thoughts and suggestions for tools and security sources to improve vulnerability detection in packages! Should we partner with **Snyk** or other leaders in SBOM tools? Let us know what you think or if you'd like to sponsor us!

Thank you for supporting LibTracker. Together, let’s make dependency management effortless! 💻✨

LibTracker, SBOM, DependencyManagement, OpenSource, VisualStudioCode, VSCodeExtension, AppSecurity, SoftwareDevelopment, SoftwareLicensing, VersionControl, Npm, Snyk, CyberSecurity, DevTools, SoftwareEngineering, AppUpdates, Milestones, TechCommunity, VulnerabilityManagement, OpenSourceTools