Jackson Structured Programming (JSP) Timeline  by year

Jackson Structured Programming (JSP) was developed by British software consultant Michael A. Jackson to provide a rigorous, data-driven alternative to the intuitive “top-down” methods prevalent in the 1970s. Its evolution is characterized by a transition from micro-level program design to macro-level system architecture. 

The Early 1970s: Foundation and Invention

  • 1970: Michael Jackson founded his firm, Michael Jackson Systems Limited, to fully develop a new program design methodology.
  • 1974: The name Jackson Structured Programming (JSP) was coined by the company’s Swedish licensee.
  • 1975: Jackson published the seminal book Principles of Program Design, which formally documented the JSP method and is now considered a classic. 

The Late 1970s: Standardisation and Expansion

  • 1977: JSP reached global recognition, being taught in universities and used across Europe, the US, and Asia.
  • Government Adoption: The UK government adopted JSP as its standard program design method under the name SDM (System Development Methodology).
  • Industry Use: Large organisations like the World Health Organization (WHO) began using JSP as a standard for specifying programs. 

The 1980s: Evolution into System Development (JSD)

  • 1980: Jackson published JSP, A Practical Method of Program Design, further refining the technique for practical industry use.
  • 1982–1983: Jackson, along with John Cameron, introduced Jackson System Development (JSD). While JSP focused on individual programs, JSD expanded these principles to entire systems.
  • Integration: JSD was widely incorporated into the UK’s SSADM (Structured Systems Analysis and Design Method), specifically for entity and event modelling. 

The 1990s to Present: Legacy and Modern Relevance

  • 1990s: Jackson introduced his third major method, Problem Analysis (or the Problem Frames Approach), focusing on requirements and software specifications.
  • Legacy: While JSP has faded from mainstream daily practice due to the rise of Object-Oriented Programming, its core concepts—like deriving program structure from data structures—influenced modern practices like Event Storming in Domain-Driven Design (DDD). 

Jackson Structured Programming (JSP) Timeline  by year

History of Cloud Computing timeline by year

The history of cloud computing evolved from 1950s time-sharing concepts to today’s AI-integrated hyperscale ecosystems. While John McCarthy and J.C.R. Licklider envisioned computing as a global utility in the 1960s, the modern era truly began with the 1999 launch of Salesforce and the 2006 debut of Amazon Web Services (AWS). 

Foundational Era (1950s – 1980s)

  • 1955: John McCarthy introduces the theory of sharing computing time among a group of users.
  • 1961: McCarthy proposes that computing will one day be sold as a public utility, similar to water or electricity.
  • 1967: IBM develops the first operating system that allows multiple users to timeshare a single resource.
  • 1969: ARPANET (Advanced Research Projects Agency Network) is launched, serving as the precursor to the modern internet.
  • 1972: IBM releases the first version of its Virtual Machine (VM) operating system.
  • 1977: The cloud symbol is first used in original ARPANET diagrams to represent networks of computing equipment.

The Rise of the Modern Cloud (1990s – 2009)

  • 1996: The term “cloud computing” appears in an internal Compaq business plan.
  • 1997: Professor Ramnath Chellappa defines cloud computing as a “computing paradigm where the boundaries of computing will be determined by economic rationale”.
  • 1999: Salesforce.com launches, becoming the first company to offer business applications over the internet, pioneering SaaS.
  • 2002: Amazon Web Services (AWS) launches as a suite of web-accessible tools for developers.
  • 2006: AWS releases Elastic Compute Cloud (EC2) and Simple Storage Service (S3), marking the birth of modern IaaS.
  • 2007: Netflix begins its transition to a video-streaming service using cloud infrastructure.
  • 2008: Google releases Google App Engine, a platform for developing and hosting web applications in its data centres.
  • 2009: Google Apps (now G Suite) launches, bringing browser-based enterprise applications to the mainstream. 

Expansion & Specialisation (2010 – 2019)

  • 2010: Microsoft officially releases Azure.
  • 2010: NASA and Rackspace initiate OpenStack, an open-source project for cloud software.
  • 2011: Apple launches iCloud, popularising consumer cloud storage.
  • 2012: Oracle enters the market with Oracle Cloud.
  • 2013: Docker introduces open-source container software, revolutionising application portability.
  • 2014: Google launches Kubernetes for container orchestration, and AWS introduces Lambda, pioneering serverless computing.
  • 2019: Microsoft Azure introduces Azure Arc, enabling services to run across various on-premises and cloud environments. 

The AI & Edge Era (2020 – Present)

  • 2020: The COVID-19 pandemic accelerates cloud adoption for remote work and education.
  • 2022-2024: Cloud providers integrate GenAI and Machine Learning into core services, such as Microsoft’s alliance with OpenAI.
  • 2025: Quantum-as-a-Service gains traction, with IBM providing cloud access to systems with over 1,000 qubits.
  • 2026: Global spending on cloud services (SaaS, PaaS, and IaaS) is forecast to reach approximately $738 billion.

History of Cloud Computing timeline by year

Evolution of CI/CD (Continuous Integration and Continuous Delivery/Deployment

The evolution of CI/CD (Continuous Integration and Continuous Delivery/Deployment) has transitioned from manual, high-risk “integration hell” to fully automated, cloud-native pipelines.

Foundational Era (Pre-2000s)

  • 1989: Earliest known work on CI with the Infuse environment.
  • 1991: Root practices of CI/CD began to emerge.
  • 1994: Grady Booch used the term “continuous integration” in his book Object-Oriented Analysis and Design with Applications.
  • 1997–1999: Kent Beck and Ron Jeffries formalise CI as a core practice of Extreme Programming (XP). 

The Rise of Automation (2001–2010) 

  • 2001: CruiseControl is released as the first widely used open-source CI server.
  • 2005: Hudson (the predecessor to Jenkins) is created by Kohsuke Kawaguchi at Sun Microsystems.
  • 2006: JetBrains releases TeamCity.
  • 2010: Jez Humble and David Farley publish the seminal book Continuous Delivery, formalising the “CD” part of the equation.
  • 2010: IMVU engineers document the first practical CD system, initially met with skepticism but quickly adopted by lean software movements. 

Modern CI/CD & Cloud Era (2011–2018)

  • 2011: Jenkins is born after a legal dispute between Oracle and the Hudson community.
  • 2011: Travis CI launches, popularising CI-as-a-Service for GitHub projects.
  • 2013: Docker is released, revolutionising CI/CD through containerisation.
  • 2014: GitLab CI is integrated directly into the GitLab platform.
  • 2018: GitHub Actions is introduced, bringing native automation directly into the world’s largest code repository. 

Cloud-Native & AI Era (2019–Present)

  • 2019: Argo CD and Flux gain prominence as Kubernetes-native GitOps tools.
  • 2020–2021: Massive growth phase for GitHub Actions, with over 12% of projects adopting or changing CI/CD technologies during this period.
  • 2024–2026: Modern pipelines transition toward adaptive systems that use AI to optimize test suites and make contextual decisions rather than just running fixed sequences. 

Evolution of CI/CD (Continuous Integration and Continuous Delivery/Deployment

Third Normal Form 3NF Development Timeline and Example

The Third Normal Form (3NF) is a standard for database design that ensures data integrity by removing transitive dependencies. Its development was part of the foundational era of the relational model. 

Comprehensive Timeline of 3NF and Normalization

  • 1970 — The Birth of Relational Theory: Dr. E.F. Codd, a researcher at IBM, published his seminal paper, “A Relational Model of Data for Large Shared Data Banks.” This introduced the concepts of First Normal Form (1NF) and the initial framework for normalization.
  • 1971 — Official Definition of 3NF: Codd formally defined Third Normal Form in his paper “Further Normalization of the Data Base Relational Model.” He also refined Second Normal Form (2NF) in this same period.
  • 1971 (August) — Technical Specification: The specific requirements for 3NF were further detailed in the IBM Research Report RJ909, solidifying the mathematical rules for removing transitive functional dependencies.
  • 1974 — Extension to Boyce-Codd Normal Form (BCNF): Together with Raymond F. Boyce, Codd introduced BCNF. Often considered a stronger version of 3NF, it addresses certain anomalies that 3NF might still permit.
  • 1977–1979 — Higher Normal Forms: Ronald Fagin introduced Fourth Normal Form (4NF) in 1977 and Fifth Normal Form (5NF) in 1979 to address multi-valued and join dependencies, respectively.
  • 1980s–Present — Industry Standard: 3NF became the most commonly used level of normalization for Relational Database Management Systems (RDBMS) because it strikes an ideal balance between reducing redundancy and maintaining query performance.
  • 2002 — 6NF Definition: C.J. Date, Hugh Darwen, and Nikos Lorentzos defined Sixth Normal Form (6NF) specifically for temporal databases. 

3NF Requirement Summary

To reach 3NF, a table must follow a cumulative progression: 

  1. 1NF: Each cell must contain atomic values, and there should be no repeating groups.
  2. 2NF: The table must be in 1NF, and every non-key attribute must depend on the entire primary key (no partial dependencies).
  3. 3NF: The table must be in 2NF, and every non-key attribute must depend only on the primary key (no transitive dependencies). 

To reach Third Normal Form (3NF), a database table must first satisfy the requirements of 1NF and 2NF. The primary goal of 3NF is to ensure that all non-key columns depend only on the primary key, effectively eliminating “transitive dependencies”. 

Step-by-Step Process

  1. Verify Second Normal Form (2NF)
    • Ensure the table has a primary key.
    • Confirm all non-key attributes depend on the entire primary key (no partial dependencies).
  2. Identify Transitive Dependencies
    • Look for “hidden” relationships where a non-prime attribute depends on another non-prime attribute.
    • Logic: If Attribute A (Primary Key) → Attribute B, and Attribute B → Attribute C, then Attribute C has a transitive dependency on the Primary Key through B.
  3. Remove the Dependent Attributes
    • Select the attributes that do not directly depend on the primary key.
    • Move these attributes into a new, separate table.
  4. Establish Relationships
    • In the original table, keep the attribute that served as the “determinant” (the non-key attribute that others depended on) to act as a foreign key.
    • In the new table, set that same attribute as the primary key. 

Practical Example

Consider a Student table with: StudentID (PK), StudentName, ZipCode, and City. 

  • Problem: City depends on ZipCode, and ZipCode depends on StudentID. This is a transitive dependency (StudentID → ZipCode → City).
  • 3NF Solution:
    • Table 1 (Students): StudentID (PK), StudentName, ZipCode (FK).
    • Table 2 (Locations): ZipCode (PK), City. 

By following these steps, you eliminate data redundancy and prevent update anomalies where changing a city name would otherwise require updating every student record in that zip code. 

Third Normal Form 3NF Development Timeline and Example

DevOps Development Timeline History Overview

The history of DevOps is a transition from siloed development and operations teams toward a unified culture of automation and collaboration. 

Timeline History of DevOps

Pre-DevOps & Foundations (2001–2008)

  • 2001: The Agile Manifesto is published, laying the groundwork for iterative software development and cross-functional teamwork.
  • 2006: Amazon Web Services (AWS) launches, providing the cloud infrastructure necessary for rapid, automated deployments.
  • 2007: Belgian consultant Patrick Debois begins investigating ways to bridge the gap between development and operations while working on a data centre migration project.
  • 2008: At the Agile conference in Toronto, Andrew Shafer and Patrick Debois meet and discuss “Agile Infrastructure,” marking the conceptual start of the movement. 

The Emergence of DevOps (2009–2014) 

  • 2009: John Allspaw and Paul Hammond give the legendary talk “10+ Deploys Per Day: Dev and Ops Cooperation at Flickr” at the Velocity Conference.
  • 2009: Patrick Debois organises the first DevOpsDays in Ghent, Belgium, and coins the term “DevOps“.
  • 2011: Analyst firm Gartner officially predicts DevOps will evolve from a niche concept to a mainstream strategy.
  • 2013: The book The Phoenix Project is published, popularising DevOps principles through a fictional narrative of a company’s digital transformation.
  • 2013: Docker is released, revolutionising the industry by making containerization accessible and consistent across environments.
  • 2014: The first State of DevOps Report is published by Puppet, providing data-driven evidence of DevOps’ impact on performance. 

Mainstream Adoption & Cloud-Native (2015–2019)

  • 2015: Google releases Kubernetes as an open-source project, establishing the standard for container orchestration.
  • 2015: Major cloud providers launch managed container services, such as Google Kubernetes Engine (GKE).
  • 2017: Security begins “shifting left,” leading to the formalisation of DevSecOps within development pipelines.
  • 2018: The book Accelerate is published, detailing the science behind high-performing DevOps organisations.
  • 2019: DevOpsDays celebrates its 10th anniversary with events in over 20 countries, signalling global maturity. 

The AI & Platform Era (2020–2026)

  • 2020: The COVID-19 pandemic accelerates remote work and digital transformation, making DevOps practices essential for enterprise survival.
  • 2023: Generative AI begins to be integrated into CI/CD pipelines for automated code generation, testing, and anomaly detection.
  • 2024: The focus shifts to Platform Engineering, aiming to reduce developer cognitive load through Internal Developer Platforms (IDPs).
  • 2025: AIOps (Artificial Intelligence for IT Operations) becomes standard for predictive analytics and self-healing infrastructure.
  • 2026: DevOps continues to evolve with a focus on zero-CVE container images and high-demand roles for engineers who can manage AI-driven workflows.
DevOps over time

DevOps Development Timeline History Overview

Centiun MS Business Applications and AI Specialists

Centiun Company Overview

Centiun is a British IT services consulting company and Microsoft Partner, helping enterprise public and private sector organisations achieve digital transformation excellence through the Microsoft cloud.

We specialise in Microsft Dynamics 365, Power Platform, and Micrisoft 365, delivering expert consultancy, solution architecture, implementation, and managed services that enable organisations to modernise operations, improve service delivery, and unlock greater value from their technology investment.

Centiun MS Business Applications and AI Specialists

From CRM transformation and business process automation to secure collaboration, data-driven decision making, and AI enabled innovation, Centiun supports customers to build smarter, faster and more resilient ways of working.

Our approach combines deep Microsoft expertise with a practical focus on outcomes – designing and delivering solutions that are scalable, compliant, and tailored to the needs of complex organisations.

Whether you’re starting your digital journey or optimising an existing platform, Centiun is your trusted Microsoft for long-term transformation and support.

Website: https://centiun.com

On LinkedIn: https://www.linkedin.com/company/centiun/

Email: info@centiun.com

Centiun MS Business Applications and AI Specialists

Centiun Limited is a UK-based technology consultancy that specialises in digital transformation and Microsoft Business Applications. Incorporated on 30 October 2025, the company operates as a Microsoft AI Cloud Partner, helping organisations modernise infrastructure and adopt AI-driven workflows. 

Core Services

Centiun provides a range of strategic and technical services focused on the Microsoft ecosystem: 

  • Business Applications: Implementing and automating processes using Microsoft Dynamics 365 and Power Platform.
  • Cloud Migration: Transitioning legacy systems to secure cloud environments to enhance scalability.
  • AI Readiness: Preparing businesses to integrate tools like Microsoft Copilot and agentic AI for sales and customer service.
  • Managed Services: Providing ongoing support, maintenance, and technical governance. 

Target Industries

The firm tailors its solutions for several sectors, including:

  • Public Sector: Central government and non-departmental public bodies.
  • Healthcare: Public and private healthcare project delivery.
  • Nonprofit: Cost-effective digital solutions for charitable organisations.
  • Financial Services: Fintech, insurance, and banking services requiring high regulatory precision. 

Key Company Facts

  • Location: Headquartered at Cheadle Royal Business Park, Cheshire, England.
  • Leadership: Directed by Kieran Gerard Holmes.
  • Compliance: Registered with the Information Commissioner’s Office (ICO) for data protection and holds Cyber Essentials certification.

Centiun is a specialized Microsoft AI Cloud Partner that focuses on modernizing business operations through the Microsoft Business Applications stack, primarily Microsoft Dynamics 365 and the Power Platform. Based in Cheshire, UK, they provide a range of services from AI readiness and digital transformation to managed support for small and medium-sized enterprises (SMEs). 

……….

Centiun Microsoft Dynamics Overview

Centiun offers tailored implementation and support for the full suite of Microsoft Dynamics 365 applications, which unify CRM (Customer Relationship Management) and ERP (Enterprise Resource Planning) capabilities. 

  • Core Applications Supported:
    • Sales & Marketing: Tools like Dynamics 365 Sales and Customer Insights to manage leads, automate marketing journeys, and provide a 360-degree view of customer data.
    • Service: Customer Service and Field Service modules to improve resolution efficiency and enhance overall customer experience.
    • ERP & Operations: Streamlining finance, supply chain, and HR processes using scalable cloud environments.
  • Key Service Pillars:
    • Digital Transformation: Modernising legacy systems and digitising paper forms into secure digital records.
    • AI Integration: Implementing Microsoft Copilot and predictive analytics to automate routine tasks and enhance decision-making.
    • Data Governance: Ensuring all customer interactions are GDPR compliant and stored in secure, audit-ready systems.
    • Managed Services: Providing SLA-compliant support and maintenance to ensure systems remain evergreen and secure. 

Centiun Partner Timeline (2025–2026) 

While Centiun’s experts have over 20 years of combined experience with Microsoft applications, the company itself reached several major official milestones recently: 

  • 2025
    • August: Published guidance on Digitising Paper Forms to help organisations move away from manual processes.
    • September: Centiun officially registered with the Information Commissioner’s Office (ICO) to ensure data protection compliance.
    • October: Achieved the nationally recognised Cyber Essentials Certification, demonstrating commitment to cybersecurity.
    • October: Centiun Limited was officially incorporated as a private limited company.
    • November: Appointed as an official Crown Commercial Service Supplier, allowing them to provide services to the UK public sector.
    • December: Announced a strategic partnership with Pax8 to further enhance their cloud-based solution delivery.
  • 2026
    • January: Launched specialized App Modernisation services to help businesses revitalize legacy infrastructure.
    • February: Reaffirmed their mission as a digital partner for sustainability and efficiency for SMEs. 

Stakeholders are key to Project Success

Stakeholders are key to Project Success

War Machine 2026, with Alan Ritchson, on Netflix

War Machine with Alan Ritchson

New… War Machine on Netflix… with Alan Ritchson of Reacher fame… a little like the first Predator movie (but with a giant transformer type robot) with a touch of Aliens in the last segment… not bad… hectic but ‘not bad’… conclusion… don’t make Predator sequels… re-imagine the original but differently… good fun at least… 😀

War Machine 2026, with Alan Ritchson, on Netflix