Gatikrushna Sahu’s Post

Policy-based replication has some major benefits over Global Mirror - no 1920 events, huge performance gains and significantly simpler management. As version 8.6.0 is now a recommended release, you should be thinking about upgrading your replication experience - read how here: https://lnkd.in/dDpYzh3m

The Role of Consistency & Latency in the context of Replication 👾 Consistency: Refers to the requirement that all replicas of a distributed system reflect the same state. A system is consistent when all nodes return the same response for a given request at the same time. Latency: The time it takes for a system to respond to a request. Lower latency means faster response times. When it comes to replication, remember to keep in mind the tradeoff between consistency and latency. We may choose to write to a single node, respond immediately and replicate later, at the cost of data loss in case of replication failure; or we may choose to wait for partial or full replication before responding, at the cost of increased latency.

☁️📶 GaussDB is a high-performance, AI-Native distributed database that is well-suited to enhance Carrier business operations and management: ⚡ High Availability: A dual-cluster strong consistency solution; city-level remote disaster recovery from over 1,000 km away with zero RPO ⚡ Security: A fully software-encrypted database, CC EAL4+ certified, the highest level of security certification in the industry ⚡ Easy Deployment and Migration: Uses UGO's pre-migration evaluation and schema migration techniques to automatically convert syntax of mainstream databases to GaussDB syntax, with greater than 90% Syntax compatibility Find Out More here: https://lnkd.in/dkEyEzsT #HuaweiCloud #CarrierCloud #DigitalTransformation

Optimise your data protection strategies and check out this guide to best practices featuring a combined solution based on Quantum ActiveScale and Veeam Backup and Recovery. https://lnkd.in/eVgeGzVP

Optimise your data protection strategies and check out this guide to best practices featuring a combined solution based on Quantum ActiveScale and Veeam Backup and Recovery. https://lnkd.in/ed35gnQT

Hydrolix has built a powerhouse platform for modern log storage and observability! The below snippet is why adoption is off the charts for storage and management of critical security data: “It’s about recognizing a critical problem in the tech industry that has a ripple effect across everything from headcount to profitability to budgets. It’s about the cost and volume of incoming data. Many enterprises are dealing with terabyte scale volumes of log data every day, and they have to choose between prohibitively high costs to keep that data or throwing it away. Even worse, sometimes they have to do both—pay too much and discard data!” Check it out here:

In my last post ,discussed about challaneges and issues faced because of replication lags. This post is about how to mitigate the issues caused by replication lag Below are some of the common techniques used:- Optimized Replication Protocols: Use efficient replication protocols that minimize latency and maximize throughput between nodes. Quorum-based Consistency Models: Implement quorum-based read and write operations to ensure that reads and writes are consistent across replicas. Asynchronous and Synchronous Replication: Depending on the use case, choose between asynchronous (eventual consistency) and synchronous (strong consistency) replication models. Monitoring and Alerts: Implement robust monitoring and alerting systems to detect and mitigate replication lag issues proactively. Load Balancing and Routing: Use intelligent load balancing and routing strategies to direct read and write operations to nodes with minimal replication lag. Conflict Resolution Mechanisms: Implement conflict resolution mechanisms to handle inconsistencies that arise due to replication lag and concurrent updates. #distributedSystems #backendEngineering

Such a nice introductory article about Change Block Tracking. Worth reading and am happy to say as I am currently working on Storage domain, where we are actively using this concept.

Most observability platforms are too expensive to fully monitor large distributed systems at scale, leading to issues like short data retention windows and discarded data. And these distributed systems are growing larger and more complex while emitting more log data than ever before. With many traditional observability solutions struggling to keep up with increases in log volume and system complexity, is observability still worth the effort and expense? Read what Hydrolix co-founder Marty Kagan has to say on the topic. https://lnkd.in/eP7zqQaB

High availability clusters are vital in ensuring the data is always accessible but they come with challenges like split-brain and amnesia. We have tackled these issues head on. Split-brain, where nodes lose connection and make conflicting decisions, is managed through quorum and fencing, while amnesia where a failed node "forgets" data is prevented with robust data synchronization and redundancy mechanisms. Your storage stays online, secure, and fully operational. No single point of failure. Have a look at the detailed blogpost: https://lnkd.in/eiQuQzuh #HighAvailability #xiRAID #DataIntegrity #softwareraid #hpc