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Querying transaction details from a Hyperledger Fabric ledger is critical for auditing, compliance verification, and debugging chaincode behavior. The QSCC (Query System Chaincode) provides the GetTransactionByID function to retrieve complete transaction metadata including endorsements, read/write sets, and validation status. This guide uses Hyperledger Fabric 2.5+ on Ubuntu 24.04 LTS with the test-network from fabric-samples. Environment…
Hyperledger Fabric is a modular, enterprise-grade consortium blockchain platform. While its official documentation is comprehensive, deploying a test network from scratch requires configuring multiple dependencies and tools—a process that’s time-consuming for new users. This guide covers both automated and manual setup approaches to get a working Fabric network running quickly. Prerequisites You’ll need: Ubuntu 24.04…
When you see output like this from hdfs dfsadmin -report, you need to understand what each metric means and how to respond: Under replicated blocks: 139016 Blocks with corrupt replicas: 9 Missing blocks: 0 Understanding block states in HDFS is essential for cluster health. The distinction between these categories determines how urgent your response needs…
Securing your website with HTTPS is no longer optional—it’s essential for SEO, user trust, and browser compatibility. The good news: Let’s Encrypt provides free certificates, and the tooling has matured significantly. Using Certbot with Nginx or Apache The standard approach is Certbot, which automates certificate issuance and renewal: sudo certbot –nginx This automatically configures HTTPS…
Chrome on iOS has a fundamental limitation: it cannot accept self-signed SSL certificates or custom Certificate Authorities (CAs) because iOS restricts all browsers to use the system’s certificate validation. Unlike desktop Chrome, you cannot bypass this through browser settings. Why This Limitation Exists iOS enforces strict security policies where all apps—including Chrome, Safari, and Firefox—must…
A database schema is the blueprint that defines how data is organized and stored in a database. Think of it as the architectural plan for your database—it specifies tables, columns, data types, relationships, constraints, and rules that govern how data can be stored and accessed. Core Components of a Schema A schema encompasses several key…
Consistency models define the guarantees that a distributed system makes about the order and visibility of data modifications across nodes. Understanding these models is essential when designing systems, choosing databases, or debugging data anomalies in production. Strong Consistency Models Strict Consistency is the ideal but rarely achievable model. It guarantees that reads always reflect the…
If you’re creating posters—whether for conferences, events, or general communication—you’ll want the right tools and guidance. Here’s a practical breakdown of what works. Design Software Inkscape is your go-to for vector-based design. It’s free, open-source, and handles logos, text, and scalable graphics without quality loss. Use it when you need clean lines, precise shapes, or…
The Secondary NameNode periodically merges the fsimage and edits log files to keep the edits log manageable and consolidate metadata. When this checkpointing fails, you’ll see errors like: ERROR org.apache.hadoop.hdfs.server.namenode.SecondaryNameNode: Exception in doCheckpoint java.io.IOException: Inconsistent checkpoint fields. This typically indicates a mismatch between the NameNode and Secondary NameNode metadata states, often from unclean shutdowns or…
QEMU/KVM networking operates across multiple layers — TAP devices, QEMU’s packet queuing, virtio descriptors, and kernel bypass mechanisms. Understanding this stack is essential for debugging connectivity issues and tuning performance in production environments. TAP Device Fundamentals TAP (TUN/TAP) devices create a bridge between the guest and host network stack. A typical QEMU/KVM configuration looks like:…
Most popular task monitoring tools (top, iotop, procfs) sample disk I/O information at granularity limited by kernel timer frequency—typically once per second. This sampling rate misses short-lived I/O bursts and makes it difficult to accurately measure which tasks are truly I/O bound. eBPF and kernel tracepoints let you capture microsecond-level accuracy without heavy overhead. Why…
Choosing the right cloud storage service requires understanding how each platform handles data consistency. This post covers the current consistency guarantees from the three major providers and how they affect your application design. Amazon S3 S3 is a key-based object store built for Internet-scale workloads. The consistency model is now straightforward across all operations. S3…
Andrew Fikes, Principal Engineer at Google, presented on storage architecture and the fundamental challenges that emerge when operating at scale. The presentation from the 2010 Faculty Summit remains relevant for understanding how distributed storage systems must be designed and the trade-offs inherent in large-scale deployments. Core Storage Challenges at Scale Google’s storage systems had to…
Jeff Dean’s “Designs, Lessons and Advice from Building Large Distributed Systems” is essential reading for anyone building or operating distributed infrastructure. This talk, presented at multiple conferences including LADIS and various tech events, distills decades of experience at Google and now at Google Research. If you’re designing systems that scale beyond a single machine, you…
Colossus is Google’s successor to the Google File System (GFS), designed to handle the massive scale of data storage across Google’s infrastructure. While GFS was documented in detail in the 2003 SOSP paper, Colossus information remains sparse in academic literature—much of what we know comes from talks and interviews with Google engineers. Colossus serves as…
Understanding distributed systems and cloud computing starts with the literature. These papers form the foundation for anyone working in the space — they’re not just historical artifacts, they’re still actively referenced and their design principles remain relevant. Internet-Scale Systems and Datacenters The Google cluster architecture paper remains essential reading. It laid out the practical realities…