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Platform architecture: from standards to a usable product · Guide · A practical guide to turning architecture standards into paved roads, reusable contracts, and measurable platform outcomes.
Observability systems: design the telemetry path before the dashboard · Guide · A systems guide to telemetry contracts, collection, routing, storage boundaries, and operational feedback at scale.
AI governance for software systems: controls that fit delivery · Guide · A delivery-focused guide to AI inventories, risk boundaries, evaluation, human oversight, and operational evidence.
Cloud migration: sequence decisions, not just workloads · Guide · A practical guide to cloud migration boundaries, dependency mapping, landing zones, observability, cutovers, and exit criteria.
Staff engineering practice: create leverage through clear systems · Guide · A practical guide to technical direction, decision records, cross-team delivery, mentoring, and operational credibility.
Architecture Solution Blueprint platform · Project · Designed and led the zero-to-one delivery of an enterprise platform that turns 1,000+ architecture patterns into real-time service recommendations, solution blueprints, and automated architecture workflows.
Vendor-neutral observability platform · Project · Architected a vendor-neutral OpenTelemetry and telemetry-routing platform designed for approximately 150 TB/day across 10,000+ systems, enabling governed collection and routing without coupling teams to a single observability vendor.
ASB Assist · Project · Building an LLM and RAG architecture assistant that turns natural-language requirements into architecture recommendations and diagrams using retrieval, tool integration, evaluation, grounding controls, guardrails, and auditable workflows.
Healthcare verification platform · Project · Joined as the first engineer and built the platform across React and TypeScript, Node.js APIs, verification workflows, document-classification integration, and AWS EKS in a regulated healthcare environment.
DCS-BBN · Project · A peer-to-peer archival storage network using Solidity smart contracts, Hyperledger Fabric, and privacy-preserving verification. Published by Springer.
Automatic trading system · Project · A low-latency trading system that combines live brokerage APIs, market-data streams, quantitative signals, position sizing, and automated risk controls.
Staff Software Developer & Enterprise Architect — Royal Bank of Canada · Experience · Building enterprise platforms and standards across architecture automation, observability, cloud infrastructure, and responsible AI.
Blockchain Architect & First Full Stack Engineer — HealthCard · Experience · Built the acquired startup’s initial product and cloud architecture across frontend, APIs, verification, and deployment.
IT Developer / Software Developer Co-op — Canada Revenue Agency · Experience · Modernised federal tax-platform interfaces and contributed to accessible digital services used by Canadians.
Teaching Assistant & Research Assistant — Dalhousie University · Experience · Supported software development, algorithms, and graduate cloud-computing courses while researching call-stack decision algorithms.
Blockchain Developer — CryptoVantage · Experience · Built on-chain event processing and wallet-risk analysis for anti-money-laundering workflows.
Decentralized Cloud Storage Based on Blockchain Networking · Research · Published research on attribute-based access control, blockchain security events, and untrusted cloud storage.
Investment philosophy · Page · Dhruv Doshi’s personal investment philosophy: compound capital, avoid permanent ruin, demand quality and valuation discipline, and continuously re-underwrite every holding.
"Active-active multi-region design: the honest trade-offs" · Note · Every few years a team decides it needs active active multi region, usually after an outage, with the requirement phrased as "we can never go down." Active active is legitimate for a…
"Agent orchestration patterns: planner-executor, routing, and supervision" · Note · Most teams building AI agents start with a single agent loop: a model, a prompt, and a pile of tools. It works for the demo. It falls apart when the task is too long, too varied, or too…
"AI red teaming: a practical playbook for enterprise teams" · Note · AI red teaming is the practice of adversarially testing AI systems before attackers do. It borrows the name from cybersecurity red teams, and the analogy is useful but incomplete: you…
"Third-party AI vendor risk management" · Note · Enterprise AI systems are built on third party components: foundation model APIs, embedding services, vector database vendors, agent frameworks, evaluation platforms, annotation…
Design APIs for agent consumers · Note · APIs were designed for human developers reading documentation. AI agents are becoming a significant consumer of the same interfaces, and they read APIs differently: they parse schemas…
API versioning strategy that survives contact with reality · Note · The real goal of API versioning is not elegance. It is this: never break a consumer you don't know about. Internal services you can grep for callers. External APIs — public, partner, or…
"Audit logging for AI systems: what to record and why" · Note · AI systems make decisions and take actions that need to be explainable after the fact: why did the agent do that, what data did it use, who approved it, what exactly happened? Audit…
"Caching strategy for distributed systems" · Note · Caching is the highest leverage performance tool in distributed systems and the most reliable source of subtle correctness bugs. Every cache is a bet: that serving slightly stale data…
The Canadian public-sector technology landscape · Note · Canada's public sector technology landscape is large, fragmented, and full of opportunity for firms that understand how it actually buys and builds. Federal departments, provinces,…
"Change data capture in production: log-based vs the alternatives" · Note · Almost every data platform eventually needs to get rows out of a production database without breaking it. The analytical store needs fresh data, the search index needs updates, the…
"Chaos engineering that survives the pilot" · Note · Chaos engineering has a pilot problem. A team runs a game day, kills some pods, finds a missing readiness probe, writes a triumphant blog style internal post — and eighteen months later…
"Choosing a vector database: what actually differentiates them" · Note · The vector database market has a marketing problem: every product claims to be the fastest, most scalable, most accurate option, and the benchmarks they publish are engineered to prove…
Cloud cost attribution that survives contact with reality · Note · Every organization wants to know what its cloud spend buys. Most cost attribution efforts produce dashboards that engineers ignore and finance distrusts. The gap is usually not tooling;…
Data retention and deletion in AI systems · Note · AI systems are data copies all the way down: training sets, vector indexes, caches, logs, evaluation sets, and backups. Each copy has its own lifecycle, and deletion requests — from…
"Defending against prompt injection in production LLM systems" · Note · Prompt injection is the defining security problem of LLM applications. It is not a bug that gets patched; it is a structural property of systems that mix instructions and data in the…
"Design systems are a platform: treat them like one" · Note · Most design systems die the same way: a burst of initial energy produces a component library, teams adopt it unevenly, the library drifts from the product, contributions stall, and…
"Engineering metrics that matter: DORA, SPACE, and the ones in between" · Note · Every engineering organization measures something. Most measure the wrong things, confidently, on beautiful dashboards nobody acts on. Velocity is up; the engineers say everything is on…
Sequence enterprise AI adoption by risk, not by hype · Note · Most enterprise AI programs fail in one of two ways: they start with the highest risk use case and stall in governance review, or they scatter dozens of disconnected pilots that never…
"Envelope encryption and KMS design for application teams" · Note · Every application team eventually faces the same requirement: encrypt sensitive data, manage the keys properly, rotate them, and prove it to an auditor. The naive approaches — a key in…
"Evaluating AI agents: beyond task success rate" · Note · Task success rate is the metric everyone reports and almost no one should rely on alone. It tells you whether the agent completed the task — not whether it completed it well, safely,…
"Event-driven architecture pitfalls and how to avoid them" · Note · Event driven architecture has a seductive pitch: services decoupled in time and space, reacting to facts instead of calling each other. The pitch is not wrong. But the failure modes of…
"Feature flag governance: flags as inventory, not litter" · Note · Every sufficiently mature codebase contains a graveyard of feature flags: new checkout flow v2 final , enable thing temp , johns experiment do not delete . Each was created for a good…
"Feature stores: when your ML platform needs one" · Note · Every ML team eventually hits the same wall: the model that worked in the notebook fails in production, and the root cause is features. Training used one definition of "user's 30 day…
"Fine-tuning vs RAG vs prompting: how to actually decide" · Note · Teams building on LLMs face a recurring decision: should we fine tune a model, build retrieval augmented generation, or just engineer better prompts? The discourse around this is noisy…
"FinOps for AI workloads: controlling GPU and inference spend" · Note · AI workloads have a cost profile unlike anything else in the enterprise cloud bill: GPU compute that is expensive per hour and often poorly utilized, inference costs that scale with…
GitOps at scale: what works past the demo · Note · The GitOps demo is compelling: commit to git, watch the agent sync it to the cluster. It takes a day to set up and about a year to discover what it doesn't do. This note is about that…
"Guardrail architecture for LLM applications" · Note · Guardrails are the controls that keep LLM applications within acceptable bounds: blocking disallowed content, enforcing policies, validating outputs, and constraining agent actions.…
"Hiring bars for senior engineers: what the bar is really made of" · Note · Every company claims a high hiring bar. Few can say what it's made of. Ask a hiring manager what distinguishes their senior bar from their mid level bar and you'll usually get vibes:…
Incident review culture for AI systems · Note · Incident review for traditional software asks what the system did wrong. Incident review for AI systems must also ask what the system did confidently, plausibly, and incorrectly — and…
The internal developer platform adoption playbook · Note · Building an internal developer platform is an engineering problem. Getting engineers to use it is an organizational one. Most platform programs underinvest in adoption by an order of…
"Lakehouse architecture: the decisions that actually matter" · Note · The lakehouse pitch is seductive: one storage layer — cheap object storage — with warehouse grade reliability and query performance on top. ACID transactions, schema enforcement, time…
"Legacy modernization in the public sector: constraints are the design" · Note · Private sector modernization advice assumes things that aren't true in government: that you can reorganize teams freely, that funding follows value, that downtime is a business…
"Managing technical debt like a portfolio" · Note · "Technical debt" is the most overused and least managed concept in software engineering. Every team says they have it. Almost none can say how much, where it is, what it costs, or what…
"Phishing-resistant authentication: MFA that actually holds up" · Note · "We have MFA" is the most common false confidence in authentication. SMS codes, TOTP apps, and push approvals all count as multi factor, and all of them fail against a phishing page…
"Micro-frontends: the narrow conditions where they pay off" · Note · Micro frontends promise microservices' organizational benefits for the UI: independent teams deploying independently. In practice, most adoptions buy the complexity of distributed…
"Mobile release trains: CI/CD when the app store is your deploy target" · Note · Web teams deploy when they feel like it. Mobile teams deploy when Apple and Google let them. That asymmetry rewrites every assumption CI/CD makes: there is no rollback, no instant…
Model risk management for LLM systems in regulated industries · Note · Regulated industries — banking, insurance, healthcare — have managed model risk for decades. Credit models, fraud models, and capital models all pass through validation functions that…
"Network segmentation in cloud: VPC design that holds up" · Note · Cloud networking gives you a green field and a dangerous amount of rope. There is no physical firewall to misconfigure — instead there are security groups, NACLs, route tables, and IAM…
"OAuth 2.0 and OIDC in production: flows, tokens, and the mistakes that repeat" · Note · OAuth 2.0 is an authorization framework that the industry uses for authentication anyway, usually by bolting OpenID Connect on top. The specs are readable, the libraries are mature, and…
Observability for LLM applications · Note · Traditional observability answers what the system did. LLM application observability must also answer what the system said, why it said it, what it cost, and whether it should have said…
"Offline-first mobile architecture: sync, conflicts, and honesty" · Note · Mobile networks lie. They report full signal in elevators, drop mid request in parking garages, and throttle aggressively on congested cells. An app designed for reliable connectivity…
"PII detection and redaction in AI data pipelines" · Note · AI systems are PII magnets. They ingest documents full of personal data, process user inputs containing identifiers, generate outputs that recombine sensitive information, and log…
Platform engineering for AI workloads · Note · AI workloads are becoming ordinary production workloads, but platforms built for stateless microservices handle them poorly. GPU scheduling, model serving, evaluation infrastructure,…
"Platform team topologies: organizing for leverage, not tickets" · Note · Every platform team starts with the same noble intent: build the paved road so product teams can move fast. And nearly every platform team ends up in the same place: a ticket queue.…
"Policy as code with OPA: guardrails without gatekeepers" · Note · Most organizations enforce policy through people: a security review board that meets on Tuesdays, a Slack message asking "can we deploy this?", a spreadsheet of approved images that is…
"Procurement-friendly architecture: build systems that survive the RFP" · Note · In the private sector, architecture serves the product. In the public sector, architecture also serves the procurement — because every significant system will be bought, built, or…
Progressive delivery for platform changes · Note · Platform changes are high blast radius by definition: a bad rollout of a shared build pipeline, service mesh configuration, or base image affects every team at once. Yet platform teams…
"Push notification architecture at real scale" · Note · Push notifications look simple — your server calls a provider API, the phone buzzes — until the second million devices, the first incident where a notification storm wakes a continent,…
RAG failure modes in production and how to contain them · Note · Retrieval augmented generation fails in production in ways that never appear in a demo. The demo uses a clean corpus, a cooperative user, and a forgiving evaluator. Production…
Rate limiting and quota design for shared platforms · Note · Rate limiting is one of those topics where everyone uses the same words to mean different things, and then the design review goes sideways. Before algorithms and headers, get the…
"RFC culture that actually decides" · Note · Most engineering organizations have an RFC process. Few have an RFC culture. The difference: a process produces documents; a culture produces decisions. I've seen RFC repos with…
"Sagas for distributed transactions: choreography vs orchestration" · Note · The moment a business transaction crosses a service boundary, ACID stops applying. An order touches inventory, payment, fraud screening, and fulfillment — four services, four databases,…
"Shadow AI: discovering and governing unsanctioned AI use" · Note · Shadow AI is the use of AI tools and services without IT or security approval: employees pasting customer data into public chatbots, teams building workflows on unvetted AI APIs,…
"SSO and SCIM: the enterprise identity lifecycle nobody designs for" · Note · Enterprise buyers ask for SSO on the first sales call, and most engineering teams treat it as the whole identity problem. SSO is sign in — a single arrow pointing into your application.…
"SSR, ISR, and edge rendering: choosing without the hype" · Note · Every few years the frontend world rediscovers server rendering and declares client side rendering dead, then rediscovers its costs and declares SSR dead. The reality is boring and…
The staff engineer operating cadence · Note · Staff engineering is often described through its outcomes — leverage, influence, technical direction — and rarely through its weekly reality. But the difference between a staff engineer…
"Staff-plus archetypes: the four paths that actually exist" · Note · Ask ten staff engineers what their job is and you'll get ten different answers — not because they're confused, but because staff plus isn't one job. It's a scope band containing several…
"Stream processing design: state, time, and exactly-once" · Note · Batch processing asks "what happened?" Stream processing asks "what is happening, right now, and what should we do about it?" The difference is not speed — it is that the input never…
"Web performance budgets: make speed a release gate" · Note · Every web team agrees performance matters and almost none treat it as a requirement. Features ship, bundles grow, images accumulate, third party scripts multiply, and performance…
When to bring in enterprise AI consulting · Note · Most organizations do not need an AI consultant. They need a clear problem, an empowered owner, and the patience to run the sequencing that works: low risk internal wins first, the…
Zero-downtime database migrations at scale · Note · Most migration guides describe a single ALTER TABLE on a dev database and call it a strategy. In production, migrations are a concurrency problem: old code and new code run against the…
Elastic support for OpenTelemetry and managed OTLP ingestion · Note · Elastic supports OpenTelemetry through managed OTLP ingestion, the Elastic Distribution of OpenTelemetry, and standard SDK or collector pipelines. Organisations can send traces,…
Dynatrace support for OpenTelemetry and native OTLP · Note · Dynatrace supports OpenTelemetry through native OTLP API endpoints, the upstream OpenTelemetry Collector, and a Dynatrace collector distribution. It also supports mixed environments…
Measure whether an internal platform creates leverage · Note · An internal platform can look successful while moving work from one team to another. Repository count, portal visits, and cluster utilisation show activity, but they do not prove that…
Datadog support for OpenTelemetry and OTLP ingestion · Note · Datadog accepts OpenTelemetry data through several integration paths, but the resulting product capabilities are not identical. A design should choose explicitly between the Datadog…
Splunk support for OpenTelemetry collection and OTLP · Note · Splunk supports OpenTelemetry through the Splunk Distribution of the OpenTelemetry Collector, standard OTLP ingestion paths, and integrations with Splunk Observability Cloud and Splunk…
AWS support for OpenTelemetry with ADOT and CloudWatch · Note · AWS supports OpenTelemetry through several paths: the AWS Distro for OpenTelemetry, the CloudWatch agent, upstream or custom collectors, and CloudWatch OTLP endpoints. The right choice…
Microsoft 365 audit data in an OpenTelemetry pipeline · Note · Microsoft 365 audit data is valuable operational and security telemetry, but Microsoft 365 is not itself a general native OTLP source. The reliable architecture is to retrieve tenant…
OpenTelemetry pipeline architecture for vendor-neutral observability · Note · OpenTelemetry standardises how applications produce and transmit traces, metrics, and logs. It does not make every backend identical, and it does not operate the telemetry path…
Pattern matching algorithms for architecture recommendations · Note · An architecture recommendation platform must translate incomplete requirements into a small set of compatible patterns and services while explaining why each result fits. This is not…
Production RAG requires retrieval evidence and control · Note · Retrieval augmented generation is often described as “search, then prompt.” A production RAG system is more accurately a governed information retrieval system connected to a…
FINOS CALM and architecture as code · Note · Architecture diagrams are useful for communication, but a diagram alone is difficult to validate, compare, or connect to delivery controls. The Common Architecture Language…
Staff engineering is measured through leverage · Note · Staff level engineering is not defined by taking the hardest ticket or writing the most code. Its impact appears through the decisions, systems, and people that enable many teams to…
Architecture governance should operate through evidence · Note · Architecture governance is useful when it improves decisions and makes system risk visible. It becomes harmful when every change waits for a central meeting that lacks the context to…
Technical roadmaps should preserve options · Note · A technical roadmap should explain how engineering investments change business capability and system risk. A list of technologies with quarterly dates is a delivery calendar, not a strategy.
Capacity planning begins with constraints · Note · Capacity planning is not forecasting one traffic number and adding a fixed percentage. It is identifying which resource limits the user outcome, how demand approaches that limit, and…
Incident command is a coordination system · Note · During a serious incident, technical skill is necessary but insufficient. Many responders changing the system without shared priorities can increase risk. Incident command creates a…
Plan schema evolution as a production migration · Note · Database schema changes are distributed system changes. Application instances, background jobs, replicas, analytical consumers, and rollback versions rarely update at the same instant.…
Use data contracts to make ownership executable · Note · A data contract makes the expectations between a data producer and its consumers explicit. It covers more than column names: meaning, ownership, quality, timeliness, compatibility,…
Design safe tool use for AI agents · Note · An AI agent becomes materially different from a chatbot when it can read private data or change external systems. The central safety question is not whether the model produces good…
Build AI governance into the delivery control plane · Note · AI governance fails when it exists only as a policy document reviewed before launch. Controls must be attached to the same delivery path that versions models, prompts, data, tools,…
Evaluate LLM systems as systems · Note · A language model feature cannot be evaluated by trying a few prompts and deciding the answers look good. Its quality depends on the model, instructions, tools, retrieval, application…
Define the boundaries of a production RAG system · Note · Retrieval augmented generation connects a language model to external information, but it does not automatically make an answer correct, current, or authorised. A production design must…
Build portable boundaries, not lowest-common-denominator clouds · Note · Multi cloud strategies often begin with a desire to avoid lock in and end with a platform that hides every useful provider capability. Portability is more effective when it is applied…
Use the strangler pattern for controlled cloud migration · Note · Large migrations fail when “move the system” is treated as one indivisible project. The strangler pattern reduces risk by placing a controlled boundary around the existing system and…
Treat Terraform modules as versioned interfaces · Note · A reusable Terraform module is an internal product interface. Its inputs, outputs, defaults, provider constraints, state behavior, and upgrade path affect every stack that consumes it.…
Choose Kubernetes tenancy boundaries deliberately · Note · Kubernetes can host many teams and workloads, but a namespace is not automatically a complete security, reliability, or cost boundary. Tenancy design should begin with the risks that…
Manage secrets without creating secret sprawl · Note · Secret management is not solved by moving passwords from source code into a central vault. The larger goal is to reduce the number, lifetime, reach, and human handling of credentials…
Zero Trust begins with service identity · Note · Network location is a weak security identity. A request originating inside a cluster, virtual network, or corporate boundary is not automatically trustworthy. A Zero Trust design…
Evolve event contracts without breaking consumers · Note · An event is a public record of something that happened. Once multiple consumers depend on it, its schema, meaning, ordering, and delivery behavior form a contract—even if the producer…
Design APIs for safe retries · Note · Networks fail in ambiguous ways. A client can time out after the server commits a change but before the response arrives. Retrying may be necessary, yet repeating the operation may…
Service-level objectives are decision tools · Note · A service level objective is not a decorative percentage on a dashboard. It is an agreement about the reliability users need and a mechanism for deciding how engineering capacity should…
Treat telemetry as a production contract · Note · Telemetry is often added after a service is built: a few logs, default metrics, and traces sampled when something fails. At scale, that creates inconsistent names, missing context,…
Architecture decision records that remain useful · Note · An architecture decision record is valuable only if a future engineer can understand what changed, why it changed, and when the decision should be reconsidered. Length is not the goal.…
Design the platform as a product · Note · An internal platform is successful when product teams choose it because it removes work, not because governance forces them to use it. That changes the architecture question from “what…
Deep Learning Explained - From Basics to Advanced · Note · Deep Learning, a subset of machine learning, has revolutionized artificial intelligence by enabling computers to learn from vast amounts of data. Its applications range from image and…
The Fundamentals of Machine Learning · Note · Machine Learning (ML) is a subset of artificial intelligence (AI) that enables systems to learn from data and improve their performance over time without being explicitly programmed.…
Introduction to Artificial Intelligence - History and Evolution · Note · Artificial Intelligence (AI) has evolved from a niche field of study to a transformative technology influencing many facets of modern life. This blog delves into the history and…
What is cloud computing? · Note · Cloud computing is the on demand availability of computer system resources, especially data storage (cloud storage) and computing power, without direct active management by the user.…
Downtime with Cloud Computing · Note · Downtine in Cloud Computing Cloud Outage simply refers to the duration when the cloud infrastructure service is unavailable for use. The unavailability may also refer to performance…
High-performance computing in the cloud · Note · HPC stands for High Performance Computing, the name dictattes itslef. This is the vertical in which cloud computing offers extremenly high resources in the computation side. AWS is run…
Poly-cloud architecture · Note · A poly cloud is a cloud approach that uses different types of cloud services that are hosted onto various clouds. A poly cloud approach runs different kinds of cloud services on one…
Multi-cloud architecture · Note · Multi cloud is the use of two or more cloud computing services from any number of different cloud vendors. A multi cloud environment could be all private, all public or a combination of…
Distributed cloud · Note · DISTRIBUTED CLOUD Distributed cloud enables a geographically distributed, centrally managed distribution of public cloud services optimized for performance, compliance, and edge computing.
Community cloud · Note · Community cloud computing refers to a shared cloud computing service environment that is targeted to a limited set of organizations or employees (such as banks or heads of trading…
Hybrid cloud · Note · Hybrid cloud refers to a mixed computing, storage, and services environment made up of on premises infrastructure, private cloud services, and a public cloud—such as Amazon Web Services…
Private cloud · Note · Private cloud is a cloud computing environment dedicated to a single customer. It combines many of the benefits of cloud computing with the security and control of on premises IT…
Public cloud · Note · A public cloud is a type of cloud computing in which a third party service provider makes computing resources—which can include anything from ready to use software applications, to…
Serverless computing and Function as a Service · Note · Function as a Service (FaaS) is a serverless way to execute modular pieces of code on the edge. FaaS lets developers write and update a piece of code on the fly, which can then be…
Mobile Backend as a Service (MBaaS) · Note · Mobile backend as a service (MBaaS), also known as "backend as a service", is a model for providing web app and mobile app developers with a way to link their applications to backend…
Platform as a Service (PaaS) · Note · Platform as a service (PaaS) or application platform as a service (aPaaS) or platform based service is a category of cloud computing services that allows customers to provision,…
Software as a Service (SaaS) · Note · SaaS stands for software as a service, which means software is hosted by a third party provider and delivered to customers over the internet as a service. While most SaaS products are…
Infrastructure as a Service (IaaS) · Note · Infrastructure as a service (IaaS) are online services that provide high level APIs used to dereference various low level details of underlying network infrastructure like physical…
What is cryptocurrency? · Note · A cryptocurrency, crypto currency, or crypto is a collection of binary data which is designed to work as a medium of exchange wherein individual coin ownership records are stored in a…
How banks could respond to blockchain · Note · As the financial service industry is moving from the exploration phase to the application phase for blockchain, banks need to understand the future role of blockchain and its impact on…
How blockchain could disrupt banking · Note · In today's day and age, banks are the most important key point in the whole finance ecosystem where they serve as the critical storehouses and transfer hubs of value. Now with the…
Where blockchain falls short · Note · 1. There is no customer protection on the blockchain Blockchain technology operates as a push based settlement system. This means the individual holds power over the resource they want…
What if we combine Blockchain and Cloud Computing? · Note · Blockchain technology is distributed ledger with records of data containing all details of the transaction carried out and distributed among the nodes present in the network. All the…
Where could blockchain be used? · Note · Blockchain is freaking exciting and does have the potential to transform all of the business and how it operates, but that doesn’t mean it’s the right solution for every scenario.…
What is an initial coin offering? · Note · An initial coin offering (ICO) or initial currency offering is a type of funding using cryptocurrencies. It is often a form of crowdfunding, although a private ICO which does not seek…
What is Cryptocurrency ATM? · Note · Bitcoin ATMs (Automated Teller Machine) are kiosks that allows a person to purchase Bitcoin and other cryptocurrencies by using cash or debit card. Some Bitcoin ATMs offer bi…
What are atomic swaps? · Note · An atomic swap is a smart contract technology that enables the exchange of one cryptocurrency for another without using centralized intermediaries, such as exchanges.
What are cryptocurrency exchanges? · Note · A crypto exchange is a platform on which you can buy and sell cryptocurrency. You can use exchanges to trade one crypto for another — converting Bitcoin to Litecoin, for example — or to…
What are transaction fees in blockchain? · Note · The blockchain fee is a cryptocurrency transaction fee that is charged to users when performing crypto transactions. The fee is collected in order to process the transaction on the network.
What is anonymity in blockchain? · Note · Blockchain is public for all but the information saved in the Blockchain is not public for all the users as it comes up with SHA encryption, and the information is only accessed during…
What is a blockchain wallet? · Note · Crypto wallets keep your private keys – the passwords that give you access to your cryptocurrencies – safe and accessible, allowing you to send and receive cryptocurrencies like Bitcoin…
How mining works in blockchain · Note · What exactly is Blockchain mining? A peer to peer computer process, Blockchain mining is used to secure and verify Cryptocurrency transactions. Mining involves Blockchain miners who add…
Timestamping in blockchain and cryptocurrencies · Note · Trusted timestamping is the process of securely keeping track of the creation and modification time of a document. Security here means that no one—not even the owner of the…
What are nodes in blockchain? · Note · A Node is a part of cryptocurrency needed to make most of the popular tokens like Bitcoin or Dogecoin function. It's a fundamental part of the blockchain network, which is the…
What is Blockchain? · Note · Blockchain is the technology that allows the user to create a decentralized system of transaction and data transfers. For the naïve person, it is a method to create a people's bank…