Priyanshi Mishra’s Post

𝐒𝐭𝐨𝐫𝐚𝐠𝐞 𝐀𝐜𝐜𝐨𝐮𝐧𝐭𝐬 𝐢𝐧 𝐀𝐳𝐮𝐫𝐞 𝐂𝐥𝐨𝐮𝐝 Azure cloud offers a wide range of storage solutions to cater to various needs, such as high availability, durability, and scalability. Here are some key things about storage in Azure Cloud: 👇 𝐒𝐭𝐨𝐫𝐚𝐠𝐞 𝐀𝐜𝐜𝐨𝐮𝐧𝐭 𝐓𝐲𝐩𝐞𝐬: Azure provides different types of storage accounts, including General-purpose v2 (GPv2) for all types of data objects, General-purpose v1 (GPv1) for legacy support, BlobStorage accounts for storing unstructured data, and specialized accounts like FileStorage for high-performance file shares. 𝐃𝐚𝐭𝐚 𝐑𝐞𝐝𝐮𝐧𝐝𝐚𝐧𝐜𝐲 𝐎𝐩𝐭𝐢𝐨𝐧𝐬: Azure offers multiple data redundancy options to ensure data durability and availability. These include Locally Redundant Storage (LRS), Zone-Redundant Storage (ZRS), Geo-Redundant Storage (GRS), and Geo-Zone-Redundant Storage (GZRS). 𝐀𝐳𝐮𝐫𝐞 𝐁𝐥𝐨𝐛 𝐒𝐭𝐨𝐫𝐚𝐠𝐞: Designed for storing large amounts of unstructured data, such as text or binary data. It's ideal for serving images or documents directly to a browser, storing files for distributed access, and storing data for backup and restore, disaster recovery, and archiving. 𝐀𝐳𝐮𝐫𝐞 𝐅𝐢𝐥𝐞 𝐒𝐭𝐨𝐫𝐚𝐠𝐞: Provides fully managed file shares in the cloud accessible via the industry-standard Server Message Block (SMB) protocol. It’s suitable for migrating legacy applications that rely on file shares to Azure. 𝐀𝐳𝐮𝐫𝐞 𝐐𝐮𝐞𝐮𝐞 𝐒𝐭𝐨𝐫𝐚𝐠𝐞: A service for storing large numbers of messages that can be accessed from anywhere in the world via authenticated calls using HTTP or HTTPS. It's ideal for building flexible communications between different parts of cloud applications. 𝐀𝐳𝐮𝐫𝐞 𝐓𝐚𝐛𝐥𝐞 𝐒𝐭𝐨𝐫𝐚𝐠𝐞: Offers highly available, massively scalable storage, so that your application can automatically scale to meet user demand. 👉 azure offers high-performance, durable block storage for Azure Virtual Machines (VMs) with Azure Managed Disks. Managed Disks are available in several types optimized for different workloads. 👉 azurestorage provides advanced security and compliance features, including network restrictions with Virtual Network (VNet) and firewall rules, encryption in transit and at rest, and integration with Azure AD for fine-grained access control. 👉 Azure Storage is designed to scale automatically to meet the demands of your application. It can handle massive amounts of data and traffic, with the ability to scale up throughput and storage limits as needed. If you want to delve deeper into these topics, stay tuned, I will be sharing more content in my upcoming posts. 👉 Follow me Atul Kumar so that you get notified of my posts I recommend you to attend my FREE Class that will help you get insights of Azure Cloud along with various other related topics https://bit.ly/3IBIJc0 comment below 👇 what do you want to learn next 🤔 #azurecloud #k21academy #storage #learningeveryday

*10 Days to a Scalable Pipeline using Electronic Platform* Part 4 👇 Day 4: Data Storage Solutions – Safeguarding and Scaling Your Data After processing your data, the next big question is: where do you store it, and how do you ensure it’s scalable? In any growing pipeline, data storage is crucial for keeping everything secure, accessible, and well-organized. Why does this matter? 1. Scalability: As your pipeline generates more data, you need a storage solution that can grow with it. Whether it’s cloud storage, local servers, or a hybrid setup, the 🗝 is making sure performance doesn’t take a hit as data volumes increase. 2. Accessibility: A centralized, well-structured storage platform ensures that your team can easily access the data they need. Cloud-based solutions, for instance, enable seamless collaboration, with everyone working on the same data in real-time, no matter where they are. Speaking of seamless collaboration – I’ll be hosting an upcoming webinar on collaboration! Stay tuned for an official announcement from Labguru (BioData). Hope to see you there! 3. Security and Compliance: Protecting sensitive data—whether it’s patient records or intellectual property—is non-negotiable. Your storage solution should include encryption, secure access controls, and compliance with regulations like GDPR or HIPAA as your data footprint expands. 4. Backup and Redundancy: As your pipeline scales, so does the risk of data loss. Scalable storage systems with automated backups and redundancy help protect against accidental data loss or corruption, ensuring data remains available even if something goes wrong. 5. Efficient Retrieval and Searchability: The more data you collect, the harder it can be to find what you need. A well-organized storage system with strong indexing and search capabilities makes sure you can quickly retrieve the right data, no matter how much your storage grows. 6. Cost-Effectiveness: Many cloud storage providers offer a pay-as-you-go model, which can be a budget-friendly option for teams that don’t need a lot of storage up front but anticipate growing needs down the road. Key considerations: - Cloud vs. On-Premises: Decide if cloud storage, on-premises servers, or a hybrid model works best for your scalability, security, and budget needs. - Storage Format: Whether you’re dealing with structured data, unstructured data, or a mix, choose a storage format (like relational databases or data lakes) that best fits your requirements. - Compliance and Governance: Ensure your storage solution is aligned with the regulations relevant to your industry or region. #ELN #LIMS #Datastorage #AWS #Googlecloud #Datasecurity

🎉Major CelerData Cloud updates are here, featuring 5 powerful new features to take your customer-facing analytics to the next level. Dive into this article to see how these features, built on top of StarRocks, can supercharge your data lake workflows, reduce operational complexity, and ensure enterprise-grade disaster recovery. https://hubs.la/Q02YjlZJ0 #DataAnalytics #DataEngineering #DataLakeAnalytics#DataLake #DataLakeHouse

Security in the cloud is an ever-evolving challenge, and the insights shared in a recent article on Azure Databricks security best practices really struck a chord with me. It dives into the importance of granular access control and the need for robust monitoring to safeguard sensitive data. Imagine you’re a data engineer at a mid-sized company. You discover that a colleague has inadvertently shared sensitive datasets with external partners due to overly permissive access settings. How would you handle this? Would you tighten restrictions immediately or initiate a broader discussion on data governance best practices? I’d love to hear your thoughts on maintaining security while promoting a collaborative work environment. https://lnkd.in/gEypsTCX

Just like technology, best practices are also subject to change as we continue to improve the use of technology in a secure and optimized way. AWS Well-Architected helps cloud architects build secure, high-performing, resilient, and efficient infrastructure for a variety of applications and workloads. Built around six pillars—operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability—AWS Well-Architected provides a consistent approach for customers and partners to evaluate architectures and implement scalable designs. I recently had the opportunity to collaborate with the lovely and amazing Angela Chao and Jay Michael to update and refresh one of the best practices articulated by the AWS Well-Architected Framework's Security Pillar: SEC04-BP02 Capture logs, findings, and metrics in standardized locations (https://lnkd.in/grUB7zKH). I encourage everyone to take this opportunity to review AWS Well-Architected Framework's best practices to continue to build secure solutions and innovate at scale in the cloud! Amazon Web Services (AWS) AWS Sydney Well Architected User Group #aws #wellarchitectedframework #cloudsecurity

It is important to make sure that your critical data stored in the public cloud is backed up. As seen in a recent case where Google Cloud deleted a big customer's entire account by accident (https://lnkd.in/eJa-isA8), you need to take matters into your own hands. The best solution is likely to duplicate key data to another cloud provider or to your own on-premise network. Duplicating data to another account in the same cloud provider is probably good enough as well for most cases. This article from Hemanth M Gowda shows how you can setup cross account S3 bucket replication in AWS. https://lnkd.in/eq-aZ5fF

🔷 Azure Cloud Services🔷 Unlock the potential of Azure Cloud with this comprehensive guide to its key services across various domains! Compute Virtual Machines: Scalable, on-demand computing power. App Service: Build, deploy, and scale web apps and APIs. Containers: Use Container Instances for quick deployment, Container Registry for management, and AKS (Azure Kubernetes Service) for orchestration. Virtual Desktop: Remote desktop and app virtualization. Batch: High-performance parallel and batch computing. Networking Virtual Network: Private network for your Azure services. Load Balancer: Distribute network traffic. Application Gateway: Application delivery controller (ADC). Traffic Manager: DNS-based traffic load balancer. Network Watcher: Network performance monitoring. Firewall: Protect your network with advanced security. Express Route: Dedicated, high-throughput connections. Private Link: Secure connectivity to Azure services. Front Door: Global load balancing and site acceleration. Virtual Network Gateway: Connects on-premises networks. Storage Blob Storage: Object storage for any type of unstructured data. Azure Files: Managed file shares. Disk Storage: Persistent disk storage for VMs. Queue Storage: Message queuing for large workloads. Data Lake: Scalable storage for big data analytics. NetApp Files: High-performance file storage. Database SQL Database: Managed relational database service. Cosmos DB: Globally distributed, multi-model database. Azure Database for MySQL/PostgreSQL/MariaDB: Managed relational databases. Cache for Redis: In-memory data structure store. Database Migration Service: Simplify database migration. AI & Machine Learning Machine Learning: Build, train, and deploy models. Cognitive Services: Add AI capabilities to apps. Video Indexer: Extract insights from video content. OpenAI: Integrate advanced AI models. Media & Content Delivery Media Services: Video encoding, streaming, and content protection. CDN (Content Delivery Network): Distribute content globally with low latency. IoT IoT Hub: Connect, monitor, and manage IoT assets. IoT Central: Build and deploy IoT applications. IoT Edge: Run IoT solutions at the edge. Digital Twins: Create digital models of physical environments. Security Sentinel: Cloud-native SIEM (Security Information and Event Management). Security Center: Unified security management and advanced threat protection. Key Vault: Safeguard cryptographic keys and secrets. Defender: Comprehensive threat protection. Analytics & Blockchain Synapse Analytics: Analytics service for big data and data warehousing. Stream Analytics: Real-time data stream processing. Databricks: Collaborative data and AI service. Analysis Services: Enterprise-grade analytics engine. Data Explorer: Fast and highly scalable data exploration service. #Azure #CloudComputing #DevOps #AI #MachineLearning #IoT #Security #Networking #Database #BigData #Analytics #Blockchain

Are you an Independent Software Vendor (ISV) struggling to manage multiple Microsoft cloud tenants/instances? The amount of data and data security, as well as data isolation, can become a nightmare to handle. Fortunately, Microsoft OneLake was designed to assist ISVs with managing customer tenants/instances at scale. Learn more about this solution here: https://lnkd.in/e9b8mTyb #fasttrack Microsoft Security Microsoft Cloud Microsoft in Government Microsoft Azure

Distributed cloud may solve data management challenges

Few Points - Google Cloud Memorystore.. Certainly! Google Cloud Memorystore offers a range of features designed to provide a reliable, scalable, and high-performance managed in-memory data store solution. Here are some of the key features in detail: Fully Managed Service: Google Cloud Memorystore is a fully managed service, which means Google handles infrastructure provisioning, scaling, monitoring, and maintenance tasks. This allows developers to focus on building applications without worrying about managing underlying infrastructure. Redis and Memcached Support: Memorystore supports both Redis and Memcached, two popular in-memory data stores, providing flexibility for different use cases and application requirements. Developers can choose the appropriate data store based on their application's needs, whether it's Redis for advanced data structures and features or Memcached for simple key-value caching. High Availability: Memorystore ensures high availability through features like automatic failover and data replication. In Redis mode, Memorystore uses a master/replica architecture with automatic failover to ensure uninterrupted service even in the event of a node failure. Memcached mode offers multi-zone replication for improved fault tolerance. Performance: With Memorystore, applications can achieve low-latency read and write operations by storing frequently accessed data in memory. Scalability: Memorystore allows you to scale your in-memory data store horizontally by adding or removing nodes dynamically based on workload demands. This ensures that your application can handle increasing traffic and data volumes without performance degradation. Security: Google Cloud Memorystore provides robust security features to protect your data, including VPC peering for private network access, IAM roles for fine-grained access control, and data encryption at rest and in transit using industry-standard encryption algorithms. Monitoring and Logging: Memorystore integrates with Google Cloud's monitoring and logging services, allowing you to monitor key performance metrics, set up alerts, and analyze logs to troubleshoot issues and optimize resource utilization. Backup and Restore: Memorystore offers automated backup and restore functionality to protect against data loss. You can schedule regular backups and restore data to a previous state in the event of accidental data deletion or corruption. Global Reach: Google Cloud Memorystore is available in multiple regions globally, allowing you to deploy your in-memory data store closer to your users for lower latency and improved performance. Overall, Google Cloud Memorystore combines the performance benefits of in-memory data stores with the convenience of a fully managed service, making it an ideal choice for caching, session storage, and real-time data processing applications in the cloud.