Technical Articles

Distributed systems pose some challenges regarding design, operations, and maintenance.

The Global Data Network or GDN offers dynamic content as a combination of a streaming data processing and NoSQL databases with minimal latency across the globe.

Edge Artificial Intelligence processes ML and AI algorithms on edge devices with the lowest possible latency.

Telecommunication, internet, and edge network service providers often use geo-distributed PoPs for instant access to other networks with low latency.

The BASE is typically a multi-model database that focuses on high availability, horizontal scale, as well as fault tolerance instead of consistency.

AWS Lambda decouples a developer from responsibilities related to servers such as provisioning, logging, set up, scaling, operating, and monitoring.

Big data sets have high volume, velocity, and variety characteristics that require specific technology and analytical methods beyond traditional data processing

Personalization and adaption of the content rely upon the user’s request data, and the content to be delivered adjusts according to retrieved data from the user

Cloudflare workers are serverless functions written in JavaScript, deployed & distributed across an edge network, leveraging developers with minimal latency.

Serverless computing allows easier deployments and maintenance, cost effectiveness, automated scalability, and function as a service.

Deep learning is comprised of artificial neural networks entirely based on learning and making improvements by adopting a set of data to train itself.

OWASP provides open-source tools, resources, and training which can be used to improve the security of online applications.

Representational State Transfer or RESTful API is a stateless architectural web transport protocol to share data between web applications or services

Data is essential & provides valuable business insights. There are different kinds of data generated by a range of data sources-structured and unstructured data

GraphQL is a query language for retrieving desired information from APIs. It was created as a solution to problems in standard architectural styles such as REST

Distributed systems contain computers, servers, computational resources, phones, PCs, IoT devices e.g. smart tv and cameras that communicate with each other.

A messaging queue acts as an asynchronous temporary storage for messages.

AI consists of a problem, theory, algorithm, & practical demonstration. ML is a type of AI used for machines that make decisions based on experience.

Authentication is classified into three categories like Knowledge-based, Possession, and Inherence factor.

A digital twin comprises of virtual model to precisely predict or reflect a physical object, typically focused on maintenance, operation, or product design.

An API endpoint lies at one end which receives, processes requests from an application and then sends the information requested.

There are two types of latency: A one-way transmission or round trip, depending on the use case.

A data lake stores, manages, and secures raw or unprocessed data in one place. Data is generally in multiple different formats & obtained from various sources.

To be useful, machine learning should provide accurate, low cost, and low latency results. A distributed edge network might be the optimal technique.

Distributed databases synchronize over many network nodes in different regions, but are shown as a single database, sharing data across multiple sites.

With DBaaS, the cloud provider is responsible for managing essential tasks, including infrastructure setup, OS & software updates, backups, & disaster recovery

Static content includes documents, style sheets, images, videos, html and scripts, etc. which are resistant to changes and are shared with every user as-is.

Unlike SQL databases where data is organized in rows & tables, a graph database has nodes or entities connected to each other based on their relationships.

ETL, extract, transform, and load, is a workflow designed to shift data from a source to a destination while undergoing changes through the process.

Simple Object Access Protocol (SOAP) is a protocol used to establish communications between distributed elements of different applications via an XML schema.

Batch processing allows high-volume data to be processed efficiently, performing large-scale sorting, parsing, counting & gathering information, in parallel.

Publisher/subscriber architecture (pub/sub) allows asynchronous streaming based on message queues. Modular, robust, and low latency with a backlog of messages.

Machine learning reduces the workload of security analysts by flagging behavioral anomalies like malicious programs and spam across different platforms.

Real-time data is available as it is created whereas streaming data specifies uninterrupted ingestion of data without any response time requirement.

Security tokens authenticate users & authorize access to privileged digital resources or assets, commonly used for multi factor authentication (MFA)

Video streaming is dependent on the data that is being processed at the delivery network and the server, impacting directly the playback quality.

A document database is a type of NoSQL database widely used to store & manage semi-structured data with diverse attributes.

Polyglot persistence and multi-model databases allow an application to take advantage of multiple data models, allowing it to scale when the user base grows.

Functions are snippets of code that accomplish a task in response to events. FaaS is a platform that allows developers to build and deploy these functions.

Systems are susceptible to attacks. The complexities of securing fintech systems have increased with digitization of currency, stocks, trading, etc.

Security Assertion Markup Language (SAML) provides a way to secure such credentials i.e., passwords using SSO or Single Sign-On technology.

Data fabric is a unified management architecture automating data access, governance, & data integration, providing real-time data for analytic and AI engines.

Information about events, such as the time, nature, and initiator, can be very useful for yielding business intelligence.

A key value store’s simple and flexible architecture allows it to scale more easily and have better response times than a traditional RDBMS or SQL database.

Real-time machine learning is implemented through an event-driven architecture instead of request-driven, injecting streaming data into the training model.

Real-time analytical technologies yield actionable intelligence to overcome potential security threats and improve real-time performance.

CDC or Change Data Capture allows database systems to communicate and synchronize data records across all storage points including data warehouses and lakes.

ACID (Atomicity, Consistency, Isolation, and Durability) is a set of principles that add security, reliability, persistence, consistency and data integrity.