Hi everyone, today our topic is related to the software development lifecycle. In other words, what is the life cycle followed during software development? Everything we do in our day-to-day life has a lifecycle involved in it knowingly or unknowingly, we are following a lifecycle or a pattern. For example, we make tea or coffee everyday morning to power our day. What is the procedure for making tea boiling water adding milk adding tea powder adding some sugar? These are the following steps that everybody follows during the time of tea making. The method in which the ingredients are added is the life cycle of tea making process. Let’s see. What are the possible life cycles one can follow here some people boil the water first add milk add tea then add sugar that he is ready? For some others, the order is to add milk and water together bring it to boil then add some tea and then sugar. The rest part of them is in boiling water, add tea brew it well then add some milk to the taste, and then add sugar. So, we saw here the lifecycle involves the steps, which is adding a water milk tea powder for sure. The order in which you do? It is based on your preference. If you want to honor a no sugar diet or a diet or a diabetic person adding sugar becomes an optional step in this life cycle. But no matters what life cycle we follow all of us aim for just one thing a refreshing drink to get you started for the day. Similarly, when developing software. There are numerable steps to develop an ideal quality robust software. These ways of things have been identified and proven to work by experienced teams across the globe. So, let’s go through these seven inevitable processes with a software development lifecycle. Step number one is called planning,

Planning: Planning is where the stakeholder’s business team project manager’s program manager’s technical leads everyone sits together and plans on what needs to be built in simple terms the scope of the application and the milestones by which the software should be ready.

Step number two is

Analysis: Analysis where business analysts on the project will analyze the requirements and teachers that are expected out of the software in detail.

Step number three is

Design: This is the stage where the architects and technical team get involved. They participate in the designing process and decide the architecture of the solution.

Step number four is

Implementation: Finally, it is time to start developing the development team gets on it and starts building the software

Step number five is

Testing: Testing the software gets through a testing team cycle where they start finding defects or bugs. These all defects and bugs get assigned back to the development team, they fix and give them back for retest or testing. This cycle continues until the software is ready for deployment.

Step number six is

Acceptance: Once good quality software is ready. The software is ready to stakeholders for their approval if they are happy with it that means it’ll go signal the software can be deployed for being used by the end customers.

Step number seven and the last one after the deployment scene is called the maintenance base part

Maintenance: This is the part where the deployment team and the operations team. Always make sure that the software is running without bugs and always have been running in the environment.

So, these are the seven steps that we saw involved in the software development lifecycle.

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Data platform vendor Snowflake has appointed Jon Robertson as its president of Asia-Pacific and Japan.

In the newly created role, Robertson is responsible for driving the adoption and expansion of Snowflake’s Data Cloud in the local market to help customers use their data for business insights.

“Jon brings extensive knowledge of the local market and a strong track record of success in the cloud computing industry to both the Snowflake team and our customers in the APJ region,” Snowflake chief revenue officer Chris Degnan said.

“Jon’s leadership and expertise will expand Snowflake’s footprint and empower local enterprises to mobilise their data for business value.”

Robertson joins Snowflake from VMware, where he has worked since 2007 in a number of executive roles across Japan and Southeast Asia. He also worked at EMC and SAP prior to VMware.

At VMWare, Robertson was involved in strategic planning, business development, and client engagement.

Speaking on his new role, Robertson said, “Data is at the core of the most successful businesses today, and local enterprises can realise deep benefits from the power of Snowflake Data Cloud.”

“I’m proud to join the Snowflake team and work with clients across the region to show what’s possible for their businesses with Snowflake’s platform. I will continue the Snowflake commitment of putting customers first, within our local APJ organisations.”

What Is DevSecOps?

DevSecOps—short for Development, Security, and Operations—is a methodology that integrates security practices and accountability into every phase of the application lifecycle. Rather than treating security as a separate audit performed at the end of a release cycle, DevSecOps distributes security responsibility across developers, QA engineers, security specialists, and operations teams alike.

When applied to the SDLC, DevSecOps enables continuous integration of security checks: code is continuously analyzed, tested, and validated against known vulnerabilities throughout development, not just before a production push. This approach also helps reduce the cost of compliance, since issues are caught earlier when they are cheaper and faster to fix.

Why Does DevSecOps Matter?

Vulnerabilities are discovered constantly across platforms, libraries, and operating systems. Patches are released regularly, but teams that only apply security thinking at the end of a pipeline are perpetually catching up. A single unpatched dependency or misconfigured infrastructure component can expose an entire application to exploitation.

In a fast-moving DevOps environment—where code changes multiple times per day and infrastructure is defined as code—manual, periodic security reviews are simply not sufficient. DevSecOps provides a continuous feedback loop that keeps security posture aligned with the pace of development.

Key Benefits of DevSecOps

• Reduces vulnerabilities present in application source code.
• Reduces vulnerabilities in Infrastructure as Code (IaC) definitions.
• Decreases the attack surface by limiting exploitable paths into the application.
• Improves application stability, availability, and overall security posture.
• Reduces downtime caused by security incidents or emergency patching.
• Lowers compliance costs by surfacing issues earlier in the development cycle.

How to Enable DevSecOps in Your Current Pipeline: Five Phases

Integrating DevSecOps into an existing DevOps pipeline does not require rebuilding your workflow from scratch. The following five phases provide a structured path for incrementally embedding security into your SDLC.

Phase 1: Secure Local Development

Security starts on the developer’s workstation. Most modern applications rely on open-source libraries and containerized services. If developers are using Docker images to replicate services locally, those images should come from trusted registries and be scanned for known vulnerabilities before use. Even official images from major providers can contain unpatched CVEs. Tools such as Trivy or Snyk Container can scan images during local development. Establishing a baseline of secure, up-to-date base images ensures that vulnerabilities are not baked into the development environment from day one.

Phase 2: Version Control and Static Security Analysis

When developers push code to a version control system (VCS) such as Git, automated security checks should trigger immediately. Static Application Security Testing (SAST) tools analyze source code without executing it, identifying common vulnerabilities like injection flaws, hardcoded secrets, and insecure dependencies.

Dependency scanning is equally important. Tools such as Snyk or Sonatype Nexus can automatically audit third-party libraries against databases of known vulnerabilities every time a pull request is opened. Blocking merges when critical vulnerabilities are detected prevents insecure code from advancing through the pipeline.

Phase 3: Continuous Integration and Secure Build

The CI/CD build environment itself must be hardened. Build servers should communicate exclusively over HTTPS, be isolated from the public internet where possible, and have access controls enforced. Build artifacts—container images, packages, or binaries—should be scanned for vulnerabilities before being promoted to any environment.

Common CI platforms used in DevSecOps pipelines include Jenkins, CircleCI, AWS CodeBuild, GitHub Actions, and Azure DevOps. Each can be extended with security scanning plugins or pipeline steps that fail the build when unacceptable risks are detected.

Phase 4: Secrets Management and Secure Deployment

Environment-specific configuration—database credentials, API keys, certificates—must never be stored in source code or passed as plain-text environment variables. A dedicated secrets manager such as HashiCorp Vault, AWS Secrets Manager, or Azure Key Vault should be used to inject secrets at runtime. The CI/CD tool retrieves and injects these values securely without exposing them in logs or pipeline definitions.

During deployment, enforce least-privilege access: the deployment process should only have permission to perform the specific actions it requires—nothing more.

Phase 5: Infrastructure Security and Runtime Monitoring

Once the application is in production, continuous monitoring is essential. An Intrusion Detection System (IDS) monitors host and network activity for suspicious behavior. Open-source tools such as OSSEC or its successor Wazuh provide host-based intrusion detection, log analysis, and compliance reporting across your server fleet.

In addition to IDS, Application Performance Monitoring (APM) tools and cloud-native monitoring services provide visibility into runtime behavior, helping teams detect anomalies that may indicate an active exploit or a misconfiguration causing unintended exposure.

No application is 100% secure after deployment. New vulnerabilities are disclosed daily. The goal of this continuous cycle is to detect, assess, and remediate issues as quickly as possible—closing the window of exposure before it can be exploited.

Essential Tools for a DevSecOps Pipeline

Tooling

• CI/CD Platform — Jenkins, GitHub Actions, CircleCI, AWS CodeBuild, Azure DevOps
• Version Control System — Git (GitHub, GitLab, Bitbucket)
• SAST / Dependency Scanning — Snyk, Sonatype Nexus, SonarQube, Semgrep
• Container Scanning — Trivy, Snyk Container, Clair
• Secrets Management — HashiCorp Vault, AWS Secrets Manager, Azure Key Vault
• IaC Security Scanning — Checkov, tfsec, KICS
• Intrusion Detection — OSSEC, Wazuh
• Runtime Monitoring / APM — Datadog, New Relic, AWS CloudWatch, Prometheus + Grafana

Core Processes

• Automated static and dependency vulnerability scanning on every commit or pull request
• Dynamic Application Security Testing (DAST) against running environments
• Automated regression and integration testing
• Automated artifact promotion gated on security scan results
• Continuous deployment with secrets injected at runtime
• Ongoing runtime monitoring and alerting

An Ideal DevSecOps Workflow

The following represents a typical end-to-end DevSecOps workflow:

1. A developer writes new code and opens a pull request in the VCS. Automated SAST and dependency scans run immediately.
2. QA or a security engineer reviews the static analysis results alongside the functional code review. Critical findings must be resolved before merge.
3. On merge to the main branch, the CI pipeline builds the artifact and scans the resulting container image or package for vulnerabilities.
4. Infrastructure for the test environment is provisioned automatically using IaC tools (e.g., Terraform, AWS CloudFormation, Pulumi), with security baselines applied via configuration management.
5. The automated test suite runs against the deployed test environment, covering functional, integration, API, and security tests (e.g., DAST scans using OWASP ZAP or a comparable tool).
6. On a successful test run, the artifact is promoted and deployed to production via the CD pipeline, with secrets injected securely at runtime.
7. The production deployment is monitored continuously using APM and IDS tooling. Alerts are routed to the on-call team for rapid response.

Common Challenges When Adopting DevSecOps

Tool Sprawl

Introducing too many security tools at once creates cognitive overload and alert fatigue, particularly for teams not yet familiar with security workflows. The recommended approach is to start with the highest-value tools—typically dependency scanning and secrets management—and add more capabilities as the team builds confidence and process maturity.

Cultural Adoption

DevSecOps is as much a cultural shift as a technical one. Developers need to understand why security gates exist and how to act on scan results. Ongoing training, clear documentation, and treating security findings with the same priority as functional bugs all help embed security into the team’s day-to-day habits.

Chasing Perfection

A DevSecOps pipeline will not be perfect from day one, and that is acceptable. Teams that try to enforce zero-tolerance policies before the process is mature often create friction that slows delivery without meaningfully improving security. Establish risk thresholds, start with critical and high-severity findings as hard blockers, and refine policies incrementally as the pipeline matures.

Conclusion

DevSecOps is not an optional add-on for mature organizations—it is the foundation of responsible software delivery in any environment where speed and security must coexist. By embedding security checks at each phase of the SDLC and distributing security accountability across the entire team, organizations reduce their exposure, improve compliance, and build higher-quality software. Start with the phases most relevant to your current risk profile, invest in team education, and iterate toward a fully automated security pipeline over time.

No matter how much digital transformation you have already achieved, the work is not finished. Digital transformation is an ongoing process that demands continuous dedication and a sustained focus on improvement. It truly is a journey, not a destination.

In an effort to capture industry best practices, The Open Group has been working to embed several core value streams into its IT4IT Reference Architecture — a framework designed to help IT organizations manage end-to-end digital services. These value streams are essential for managing digital transformation at enterprise scale. If you want to achieve true organizational agility and increase release velocity, there is no reason to wait to get started.

The Six Value Streams: An Overview

The core concept behind all six value streams is continuous improvement. The era of creating a fixed annual plan at the beginning of the year — only to watch it slowly fall apart as market conditions shift and user expectations evolve — is over. Today, businesses must be genuinely agile, constantly adjusting to market needs and reacting to unexpected complexity.

The concept of continuous improvement is not new. But efficiently managing agile improvement across the planning, development, and delivery of transformative digital services remains difficult at enterprise scale. It requires a significant change of mindset and meaningful upfront effort. The six value streams described below provide a practical framework for getting there.

1. Continuous Build and Test

Continuous build and test is grounded in the principles of continuous integration. Most organizations have already adopted core agile strategies: prioritizing features, writing source code, and running iterative test cycles. The challenge is applying this consistently across an enterprise with dozens or even hundreds of development teams.

At that scale, organizations must find ways to standardize the build-and-test process. This means efficiently reusing resources and code across teams, centrally managing user requirements, and continuously validating security across the entire portfolio. Maintaining consistent product quality when many teams are working in parallel is one of the most complex operational challenges in enterprise software delivery.

• Standardize CI pipelines across teams to reduce drift and enforce quality gates.
• Centralize dependency and code reuse to avoid duplication and reduce maintenance overhead.
• Embed security testing throughout the build cycle rather than treating it as a final gate.

2. Continuous Deployment

Continuous deployment is already a recognized component of the IT4IT architecture, but many organizations struggle with it over the long run. Putting a product into production is straightforward — the difficulty lies in maintaining full visibility into what has been released, where it was deployed, and when.

Maintaining a product three years after its initial release becomes especially complex when you are supporting multiple versions across global environments. Key questions organizations frequently fail to answer consistently include:

• How do you patch individual versions of an application running in different environments?
• What are the inter-product dependencies for each deployed version?
• How do you monitor the entire application estate as it grows in size and age?

A mature continuous deployment practice requires robust release tracking, dependency mapping, and automated rollback capabilities — not just the pipeline tooling that gets code into production in the first place.

3. Predictive Service Management

Once products are in production, they must be actively maintained. In many DevOps teams, a developer informally assumes responsibility for monitoring and patching applications. This approach does not scale and creates single points of failure as the application portfolio grows.

Effective predictive service management requires a centralized console from which all products can be monitored in accordance with the service levels they must deliver. This monitoring capability must be predictive — not just reactive — and should incorporate risk assessment based on the business criticality of each monitored service.

Mature predictive service management includes the following capabilities:

• Full-stack visibility across both cloud and on-premises environments.
• Automated runbooks for investigation, escalation, and remediation workflows.
• Intelligent runbook selection, where the system automatically identifies and triggers the appropriate remediation procedure based on detected conditions.
• Business-impact-aware alerting that prioritizes incidents by their effect on critical services.

4. Continuous Feedback

A critical but frequently overlooked element of digital transformation is the systematic collection and routing of feedback. In most organizations, this process is ad hoc and inconsistent — feedback generated by operations teams, help desk groups, and monitoring systems rarely finds its way to the product teams who can act on it.

A continuous feedback loop requires building a system that automatically collects signals from production operations and service management, then routes that information to the right people. At a minimum, feedback should reach the product development team so it can be incorporated into ongoing development efforts. Ideally, the most actionable insights should travel further upstream to planning and portfolio management, where they can influence prioritization and future product design.

Without a structured feedback mechanism, development teams are effectively working blind — optimizing for assumptions rather than observed reality.

5. Continuous Exploration

Continuous exploration complements continuous feedback, and it addresses one of the most persistent challenges in large enterprises: managing a portfolio of thousands of products and applications while continuously aligning that portfolio to evolving business needs.

A static, annual planning cycle cannot keep pace with the rate of change in modern markets. Instead, organizations need a dynamic planning model that creates a continuous dialogue between what is being developed and what the business is actually requesting. This requires the ability to:

• Continuously revise scope and budget allocations across development teams.
• Respond to new business requirements in near-real time rather than at fixed planning intervals.
• Incorporate user and market feedback directly into prioritization decisions.

In short, true agile development must not be constrained by a waterfall-style planning process. Continuous exploration ensures that how the organization spends its development investment is always aligned with current business reality — and that alignment is revisited constantly, not once a year.

6. Service Onboarding and Consumption

When an organization deploys a product, it is really deploying a system that enables the consumption of services. Users are not asking for a product in the abstract — they are asking for a capability: the ability to send an email, pay an invoice, generate a report, or access data.

This distinction matters because it points to the need for a centralized service catalog: a governed registry through which users can discover and consume services, and through which the organization can maintain visibility into service ownership, state, and usage patterns.

Many organizations skip this step entirely. Services are pushed into production and become available to everyone, with no formal onboarding process and no accountability for ownership or lifecycle management. The alternative failure mode is equally common: each service has its own bespoke onboarding and lifecycle process, making it impossible to manage consumption at scale.

A well-designed service catalog solves both problems by providing:

• A consistent onboarding process for all new services.
• Clear ownership and accountability for each service.
• Usage monitoring and governance across the entire service portfolio.
• A discoverable interface for end users to find and request the services they need.

Putting It All Together

Deploying these six value streams across your IT infrastructure creates a genuinely efficient and standardized IT management system. Together they cover the full lifecycle of digital service delivery — from initial planning and exploration, through build and deployment, to in-production management, feedback collection, and service consumption governance.

The relationship between the six streams is not linear. Continuous feedback feeds continuous exploration. Predictive service management informs continuous deployment. Service onboarding and consumption depend on everything upstream working reliably. The value of the framework comes from treating these streams as interconnected, not as isolated practices.

The Open Group’s IT4IT Reference Architecture provides a structured basis for implementing these value streams at enterprise scale. The framework is designed to help organizations transform IT in manageable steps, leverage automation to reduce risk, and design operating models that can adapt continuously to changing business demands. Organizations that want to begin this work do not need to wait for any particular standard revision — the principles are actionable today.

This article is based on concepts drawn from The Open Group’s IT4IT Reference Architecture and originally sourced from TechBeacon.

What Is the Gartner Peer Insights Customers’ Choice Distinction?

The Gartner Peer Insights Customers’ Choice designation is awarded based on aggregated feedback from verified IT practitioners and technology decision-makers on the Gartner Peer Insights platform. It reflects real-world experience from professionals who have gone through the purchasing, implementation, and day-to-day use of a product. The distinction is not an analyst opinion or a Gartner endorsement; it represents the voice of the customer.

This was the second time GitLab received a Gartner Peer Insights Customers’ Choice award, having previously earned the distinction for Application Release Orchestration (ARO) in December 2018.

What Are Enterprise Agile Planning Tools?

Gartner defines Enterprise Agile Planning (EAP) tools as software that helps organizations apply agile practices at scale across the enterprise. These tools move beyond single-team or project-centric agile tooling and support:

• Business-outcome-driven planning
• Customer-centric development priorities
• Cross-team collaboration and cooperation
• Continual stakeholder feedback loops
• Work-item tracking as a central hub for application development lifecycle management (ADLM)

EAP tools represent an evolution from traditional project-centric agile tools, bridging the gap between engineering execution and broader business strategy.

What Customers Said About GitLab

The following reviews were submitted by verified users on Gartner Peer Insights at the time of the announcement:

“It is amazing how a tool can be a new face for a company as a whole. GitLab is here to stay in our organization. It is an indispensable tool, today, for a good and complete project management. All our plans go through GitLab. Our team records all the events, ideas and plans in this tool. In addition, we use GitLab in software development. Our programmers can register and merge all your project changes. This brings an incredible and surreal organization to our company.”

— COO, Communications

“GitLab is undoubtedly the best tool available in the market for the organization and monitoring of projects and ideas. With it, our teams and projects manager can administrate efforts and resources very simply and quickly. In addition, we can have control of the accomplishment of tasks and activities of each one in the project through the commits.”

— Analyst, Services

“I’m working with GitLab Team from last 4-5 years, really enjoying. The biggest thing would be having all those tickets, all of those changes, closely correlated with the actual changes in Git. For feature or changes on Git, you do not have to read codebase or fire up the whole application.”

— Analyst, Services

“This platform is expertise in version control, code review, issue tracking, etc. People can develop their software with this without physically present at one place which makes it a good project management tool and it can also be easily integrated with Atlassian and Jenkins.”

— R&D/Product Development, Services

GitLab’s Product Vision for Enterprise Agile Planning

Responding to the recognition, Sid Sijbrandij, CEO and co-founder of GitLab, stated:

“Our vision for our product is to enable all people in organizations of all sizes to innovate and organize ideas into transparent, multi-level adjustable plans that cut across departments and stakeholders (internal and external) using the same set of single-source-of-truth artifacts in a single application.”

— Sid Sijbrandij, CEO and Co-founder, GitLab

GitLab’s single-application approach means that planning artifacts — epics, milestones, issues, and boards — live in the same platform as source control, CI/CD pipelines, and security scanning. This reduces context-switching and keeps traceability intact from idea to production deployment.

About Gartner Peer Insights

Gartner Peer Insights is an online platform of ratings and reviews written by IT professionals and technology decision-makers. Its goal is to help IT leaders make more informed purchase decisions and provide technology vendors with objective, verified customer feedback. At the time of this announcement, the platform hosted more than 215,000 verified reviews across more than 340 technology markets.

For more information, visit www.gartner.com/reviews/home.

Gartner Peer Insights Customers’ Choice distinctions constitute the subjective opinions of individual end-user reviews, ratings, and data applied against a documented methodology; they neither represent the views of, nor constitute an endorsement by, Gartner or its affiliates.