Collaboration Platforms for Remote Teams

As organizations increasingly adopt hybrid-cloud architectures, understanding the right path and tools is crucial for professionals aiming to deliver resilient, scalable, and efficient applications. Here’s a Cloud Native roadmap breaking down the skills and tools to master across critical domains. Dive in and explore the ecosystem that powers modern applications! 🔴 𝟭. 𝗟𝗶𝗻𝘂𝘅 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀   Linux remains at the heart of cloud-native systems. Get comfortable with terminal commands, bash scripting, and distributions like Ubuntu and Red Hat for a solid start. 🟢 𝟮. 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹𝘀   Protocols like HTTP, SSL, and SSH form the backbone of connectivity. Tools like Wireshark are invaluable for monitoring and securing network traffic. 🔵 𝟯. 𝗖𝗹𝗼𝘂𝗱 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀   The cloud is non-negotiable! Whether AWS, Azure, or Google Cloud, understanding SaaS, PaaS, and IaaS is key to harnessing the cloud's potential. 🟣 𝟰. 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆   Security is foundational in cloud-native environments. Tools like Open Policy Agent and Prisma provide the framework for enforcing policies and securing applications. 🟡 𝟱. 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝘀 & 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻   Containers revolutionized app deployment! Master Docker, Kubernetes, and service meshes like Istio to orchestrate, scale, and manage applications seamlessly. 🟠 𝟲. 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝘀 𝗖𝗼𝗱𝗲 (𝗜𝗮𝗖)   IaC tools like Terraform, Chef, and Puppet automate infrastructure, ensuring consistency and efficiency across deployments. IaC is a must for scalable cloud-native applications. 🟢 𝟳. 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆   With tools like Prometheus, Grafana, and Elastic Stack, observability gives you the visibility needed to monitor, troubleshoot, and optimize performance in real time. 🔵 𝟴. 𝗖𝗜/𝗖𝗗   Continuous Integration and Delivery streamline deployments. GitLab, Jenkins, and GitOps practices (Argo) enable rapid, reliable application delivery. This roadmap covers essential areas for cloud-native development, from Linux fundamentals to CI/CD and observability. But, the cloud-native landscape is vast and rapidly evolving! Did I miss any critical tools or concepts? Whether it's a tool you swear by or an emerging trend you're excited about, drop it in the comments! 👇

Atlassian has been fully distributed for almost five years. We don’t have all the answers, but we’ve learned a lot about how to keep teams thriving across time zones—and we’re applying those insights every day.  ➡️ Asynchronous work: Async tools are at the core of how we operate. Confluence is our virtual hub where we share stories, celebrate new hires, and collaborate effortlessly. We also use Loom to share videos and give feedback on our own time—avoiding those dreaded “this could have been an email” moments. In fact, we’ve saved nearly half a million meetings using Loom! ➡️ Designing workdays: We’ve learned to structure workdays for focus, collaboration, and meetings (only when absolutely necessary). Teams work across no more than two time zones, ensuring at least four hours of overlap to get things done together. ➡️ Intentional connection: Data shows that real connection happens when teams meet regularly—not sporadically in an office. We provide Intentional Togetherness Gatherings (ITGs), curated experiences, and focused in-person time to collaborate. ➡️ Adapting for different needs: It’s not one-size-fits-all. For example, new hires and grads often benefit from more frequent in-person meetups, so we make sure to offer opportunities for them to connect early on. https://lnkd.in/g2sSbe3v

2025 is the Year of ACP, not just MCP. IBM has introduced a new protocol for AI collaboration called Agent Communication Protocol, building upon the foundation laid by Anthropic's Model Context Protocol. ACP takes a leap forward in how AI systems work together, allowing complex multi-agent workflows that were impossible with MCP alone. Here's how ACP works: 1️⃣ Agent Orchestration ACP enables multiple AI agents to communicate seamlessly, allowing specialized agents to combine their capabilities. 2️⃣ Standardized Messaging The protocol uses structured message formats that help agents understand each other across different frameworks and languages. 3️⃣ Task Delegation Complex problems are broken down and assigned to the most capable specialized agents, then results are assembled into cohesive solutions. 4️⃣ Framework Independence ACP works with agents built in any programming language or AI framework, removing technical barriers to collaboration. 5️⃣ Dynamic Discovery Agents can discover and utilize each other's capabilities, creating flexible AI ecosystems that evolve to meet changing needs. Whether you're building complex AI workflows or connecting specialized agents, ACP elevates what's possible, enabling deeper collaboration and more powerful solutions. Here's how ACP is architecturally different from MCP: MCP: - Focuses on connecting a single AI to external data sources and tools - Creates one-to-many relationships between an AI and various resources - Uses JSON-RPC primarily for accessing information and executing actions - Designed to expand what one AI model can access and accomplish ACP: - Centers on connecting multiple AIs to each other in collaborative relationships - Creates many-to-many networks of specialized agent capabilities - Extends JSON-RPC with agent-specific communication patterns - Designed for dividing complex tasks among specialized AI team members Understanding these distinctions matters for building the right AI infrastructure. Some problems need better tools for one AI. Others need multiple AIs working together. ACP isn't just different from MCP; it's complementary: ✅ Solves problems too complex for any single AI agent ✅ Creates AI teams with specialized members handling different aspects of a task ✅ Enables more natural workflows that mirror human team collaboration The combination of MCP and ACP is essential. MCP gives individual AIs access to tools and data. ACP helps those AIs work together as teams. Together, they create AI systems that are more capable, flexible, and effective. Over to you: What complex problems could you solve with a team of specialized AI agents working together?

Introducing Insights in Chrome DevTools Performance panel! Many web developers know the power of the Chrome DevTools Performance panel, but navigating its wealth of data to pinpoint issues can be daunting. While tools like Lighthouse provide great summaries, they often lack the context of when and where issues occur within a full performance trace. On the Chrome team we're bridging this gap with the new "Insights sidebar" directly within the Performance panel. Read all about it: https://lnkd.in/gGd3bkPw This exciting feature integrates Lighthouse-style analysis right into your workflow. After recording a performance trace, the Insights sidebar appears, offering actionable recommendations. Crucially, it doesn't just list potential problems but highlights relevant events and overlays explanations directly on the performance timeline. Hover over an insight like "LCP by phase," "Render blocking requests" or "Layout shift culprits" to visually connect the suggestion to the specific moments in your trace. The sidebar covers key areas like Largest Contentful Paint (LCP) optimization (including phase breakdowns and request discovery), Interaction to Next Paint (INP) analysis (like DOM size impact and forced reflows), Cumulative Layout Shift (CLS) culprits, and general page load issues such as third-party impact and image optimization. It's designed to make performance debugging more intuitive by linking high-level insights to the granular data, helping you improve Core Web Vitals and overall user experience more effectively. Check out the Insights sidebar in the latest Chrome versions (it's been evolving since Chrome 131!). It’s a fantastic step towards making complex performance analysis more accessible. Give it a try on your next performance audit! #softwareengineering #programming #ai

I’ve been thinking a lot about the 90 minute virtual meeting paradox. We spend the first 30 minutes on welcoming everyone and introductions, the next 15 on framing, and then a few people share thoughts. Then, just when the conversation gets meaningful, the host abruptly announces "We're out of time!” and throws a few rushed closing thoughts and announcements together. Sound familiar? We crave deep, meaningful, trust-based exchanges in virtual meeting environments that feel both tiring and rushed. It seems like as soon as momentum builds and insights emerge, it’s time to wrap up. Share-outs become a regurgitation of top-level ideas—usually focused on the most soundbite-ready insights and omitting those seeds of ideas that didn’t have time to be explored further. And sometimes, we even cite these meetings as examples of participation in a process, even when that participation is only surface level to check the participation box.  After facilitating and attending hundreds (thousands?) of virtual meetings, I've found four practices that create space for more engagement and depth: 1. Send a thoughtful and focused pre-work prompt at least a few days ahead of time that invites reflection before gathering. When participants arrive having already engaged with the core question(s), it’s much easier to jump right into conversation. Consider who designs these prompts and whose perspectives they center. 2. Replace round-robin introductions with a focused check-in question that directly connects to the meeting's purpose. "What's one tension you're navigating in this work?" for example yields more insight than sharing organizational affiliations. Be mindful of who speaks first and how difference cultural communication styles may influence participation.  3. Structure the agenda with intentionally expanding time blocks—start tight (and facilitate accordingly), and then create more spaciousness as the meeting progresses. This honors the natural rhythm of how trust and dialogue develop, and allows for varying approaches to processing and sharing.  4. Prioritize accessibility and inclusion in every aspect of the meeting. Anticipating and designing for participants needs means you’re thinking about language justice, technology and materials accessibility, neurodivergence, power dynamics, and content framing. Asking “What do you need to fully participate in this meeting?” ahead of time invites participants to share their needs. These meeting suggestions aren’t just about efficiency—they’re about creating spaces where authentic relationships and useful conversations can actually develop. Especially at times when people are exhausted and working hard to manage their own energy, a well-designed meeting can be a welcome space to engage. I’m curious to hear from others: What's your most effective strategy for holding substantive meetings in time-constrained virtual spaces? What meeting structures have you seen that actually work?

Letter H: Hybrid Work: Protecting an Organization with a Hybrid Workforce Our "A to Z of Cybersecurity" tackles Hybrid Work - the new normal with employees working both remotely and on-site. However, a dispersed workforce introduces new security challenges. Let's bridge the security gap and keep your hybrid castle safe: Fortifying Your Defenses: · Secure Remote Access: Implement strong authentication and access controls for remote connections. · Endpoint Security: Deploy robust security software on all devices, regardless of location. · Data Loss Prevention (DLP): Prevent sensitive data from being accidentally or maliciously shared outside the organization. United We Stand: · Collaboration Tools: Use secure collaboration platforms to share information and foster teamwork. · Cloud Security: Choose cloud service providers with robust security measures and educate employees on secure cloud usage. · Zero Trust Architecture: Implement a security model that verifies access for all users, regardless of location or device. Hybrid work offers flexibility, but security remains paramount. By building strong defenses, fostering awareness, and implementing secure collaboration tools, you can create a safe and productive hybrid environment for your organization. #Cybersecurity #HybridWork #A2ZofCybersecurity

Safeguarding information while enabling collaboration requires methods that respect privacy, ensure accuracy, and sustain trust. Privacy-Enhancing Technologies create conditions where data becomes useful without being exposed, aligning innovation with responsibility. When companies exchange sensitive information, the tension between insight and confidentiality becomes evident. Cryptographic PETs apply advanced encryption that allows data to be analyzed securely, while distributed approaches such as federated learning ensure that knowledge can be shared without revealing raw information. The practical benefits are visible in sectors such as banking, healthcare, supply chains, and retail, where secure sharing strengthens operational efficiency and trust. At the same time, adoption requires balancing privacy, accuracy, performance, and costs, which makes strategic choices essential. A thoughtful approach begins with mapping sensitive data, selecting the appropriate PETs, and aligning them with governance and compliance frameworks. This is where technological innovation meets organizational responsibility, creating the foundation for trusted collaboration. #PrivacyEnhancingTechnologies #DataSharing #DigitalTrust #Cybersecurity

🌐 "How can we lead inclusive team meetings when our team is so widely distributed across timezones?" That's a question our #Inclusion Strategy team at Netflix has been reflecting on quite a bit lately – and that's surely not an issue we face alone. Here are some ideas that popped up as we put our geographically distance heads together to ensure that everyone has an equal opportunity to participate in discussions that are relevant to all: 1️⃣ Establish a Meeting Time Rotation: to ensure fair participation, create a rotating schedule for your meetings. This means alternating meeting times to accommodate different time zones, so that each team member has an opportunity to attend during their regular working hours on a rotating basis. 2️⃣ Consider Core Overlapping Hours: identify the core overlapping hours when the majority of team members are available. Aim to schedule important meetings during these hours to maximize attendance. This may require some flexibility from all team members, but it fosters a sense of shared responsibility for ensuring everyone's voice can be heard. 3️⃣ Prioritise Meeting Relevance: ensure that meetings are called only when it's essential for all team members to be present. Avoid scheduling meetings for routine updates that can be shared asynchronously, giving team members more flexibility to manage their schedules. 4️⃣ Create Pre-Meeting Materials: provide agendas, and key discussion points well in advance, so team members who cannot attend live sessions can still contribute their input asynchronously. This way, everyone can stay informed and engaged in the decision-making process. 5️⃣ Encourage Rotating Facilitation: consider rotating meeting facilitators to accommodate different time zones. This not only distributes the responsibility but also allows team members from various geographies to lead discussions and bring diverse perspectives to the forefront. 6️⃣ Use Inclusive Meeting Technologies: leverage virtual meeting tools with features like real-time chat and polling to foster engagement from all participants, regardless of their location. Consider having all meetings recorded by default (unless there's a compelling reason not to), streamlining access to the team immediately after each recording is ready. 7️⃣ Promote Open Feedback Channels: establish channels for team members to asynchronously provide feedback on meeting times and themes, and communication methods. 8️⃣ Acknowledge and Respect Personal & Cultural Differences: be mindful of cultural practices and observances that may impact team members' availability or participation. Strive to do the same about individuals' needs, too (like dropping kids at school). These strategies can help create an inclusive and equitable approach to meetings, enhancing the chances of all team members feeling valued and empowered to contribute. How else can you foster that? 🤔

Here’s How I Made Website Performance Tracking Effortless with Microsoft Fabric A Company's Website Performance Can Directly Impact Its Business There is a famous quote, "𝗪𝗵𝗮𝘁 𝗴𝗲𝘁𝘀 𝗺𝗲𝗮𝘀𝘂𝗿𝗲𝗱, 𝗴𝗲𝘁𝘀 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗱." This holds true for websites as well. Google provides a service called “PageSpeed Insights,” which uses data from Chrome users to measure your website's performance and provide a score. It’s convenient to visit this website and check the score whenever we want. However, we have to go to that website and run the report each time to see the score. Additionally, we can't view historical data; we can only see the current status. Without having the previous data, it’s nearly impossible to know whether we have improved or not. That’s when we got the idea to implement an internal solution for this. When I checked for the available options, PageSpeed Insights offered an API to get the reports. In simple terms, whatever we are doing manually using the browser and clicking the analyze button, we can now send the request programmatically using Python and get the score. This is where Microsoft Fabric helped me; Without Fabric, I would have depended on either a Data Engineer or a Backend Developer to help me create this architecture to run the code daily and store the data in a DB. With Fabric, I can write the code in a Notebook, schedule the run on a daily basis, and store the data in a Lakehouse. Post which, I connected the data into Power BI and made a report, which shows the historical data in one place. And that’s why we say, Microsoft Fabric is here to connect all the tech roles! Have you started exploring Fabric? #fabric #microsoft #website #performance #data

🚀 Delta Sharing: The Open Protocol for Secure Data Exchange Traditionally, data sharing involved providing static CSV/Parquet file dumps based on ad-hoc requests, requiring data engineers to create extracts or build complex ETL pipelines. By the time data reached recipients, it was often outdated. Additionally, moving data across organizational boundaries increased security risks and required manual auditing as well. Delta Sharing, an open protocol, solves these challenges by enabling direct, real-time data exchange while ensuring security and governance. 🔍 What is Delta Sharing? Delta Sharing is an open-source protocol that allows data providers to securely share live data from their data lake or lakehouse with any recipient, regardless of the computing platform they use. It is designed to work with Delta Lake, but it also supports other formats like Apache Parquet. 🔧 What Problems Does Delta Sharing Solve? ✅ Eliminates Data Copies – Consumers can query shared data without duplicating or exporting it into another system. ✅ Interoperability – Enables cross-platform sharing across different cloud and analytics services, including Databricks, Apache Spark, Pandas, and others. ✅ Real-time & Secure Access – Uses fine-grained access control to ensure only authorized users can access the latest version of shared data. ✅ Simplified Data Collaboration – Reduces the need for custom APIs, FTP transfers, or complex ETL workflows when sharing data with external partners. 🛠 Key Components in a Delta Sharing Scenario - Provider (Data Owner) – The entity sharing the data. - Delta Sharing Server – Handles authentication and access control. - Recipient (Data Consumer) – The entity accessing the shared data, which can be a data warehouse, a machine learning model, or a BI tool. - Storage Backend – Typically an object store (AWS S3, Azure Blob, Google Cloud Storage, MinIO) where the data resides. 📌 Common Use Cases for Delta Sharing 💡 Inter-company Data Exchange – Share supply chain, financial, or operational data with partners securely. 📊 Federated Analytics – Analysts can query live shared datasets without moving them into their own data warehouse. 🤖 Machine Learning & AI – Data scientists can directly access fresh, live data for model training without worrying about outdated extracts. ⚡ Data Monetization – Organizations can offer secure access to valuable datasets as a service without needing data pipelines. Delta Sharing + Unity Catalog Delta Sharing and Unity Catalog work together to enable secure, scalable, and governed data sharing across organizations. While Delta Sharing provides the protocol for sharing live data with external consumers, Unity Catalog acts as the central governance layer, ensuring fine-grained access control, auditing, and security compliance. I will write about this integration in the future. #deltasharing #datagovernance #datasharing