What Are the 7 Stages of the System Development Life Cycle?

Introduction to SDLC in the Security Era

Ever wonder why a simple login screen feels like a fortress in some apps and a screen door in others? It usually comes down to how well the team followed the system development life cycle—or sdlc—right from the start.

• Modern sdlc definition: It’s no longer just a linear path. While these stages look distinct on paper, in modern DevOps they actually happen in rapid, overlapping cycles called "sprints." It's a framework for building secure, scalable apps like those in healthcare or finance where 100% uptime is non-negotiable.
• Shift-left security: This means moving auth checks to the very first stage of planning so you don't end up with a messy api later. This includes running SAST (Static Analysis) early to catch bugs in the source code before it even runs.
• Avoiding leaked passwords: Poor planning in the early design phase is usually why we see database breaches in retail apps today. (What Database Design Mistakes Kill Mobile Apps Before ...)

I've seen too many devs jump straight into coding a node.js backend without thinking about how AWS Cognito or Auth0 will handle token refreshes. According to IBM's Cost of a Data Breach Report 2024, the average cost of a breach hit $4.88 million, which is a huge spike from previous years. This shows why getting the "Requirements" stage right is literally a multi-million dollar decision.

So, lets dive into how the first stage sets the tone for everything else.

Stage 1: Planning and Requirement Analysis

Ever tried building a house without checking if the ground is swampy? That’s what skipping the planning stage in software feels like, except instead of a sinking porch, you get a $5 million data breach.

This is where we decide if the app needs mfa or just a simple login. If you're building for healthcare, you’re looking at HIPAA compliance; for a retail app in Europe, it's all about GDPR.

• Access Level: Do we need sso for enterprise users or just social logins?
• Compliance: Mapping out data residency early prevents a total database rewrite later.
• UX vs Security: Finding that sweet spot so users don't hate your login screen.

I once saw a team forget to plan for password resets in a fintech app. They had to bolt it on later, which created a massive security hole. (Zello urges users to reset passwords following a cyber attack) According to the Verizon 2024 Data Breach Investigations Report, 68% of breaches involved a non-malicious human element, like falling for phishing or making configuration errors. Planning for things like FIDO2 support (which enables passwordless or biometric auth to stop phishing in its tracks) can kill those risks before the first line of code is even written.

Once you know what you're building, it's time to actually map out how the data flows.

Stage 2: Feasibility Study and Risk Assessment

So you've got a killer idea, but can you actually build it without breaking the bank or your servers? This stage is where we get real about the tech stack and the "what ifs" before wasting a single line of code in node.js.

We gotta look at three big things here:

• Technical feasibility: Can your current api handle biometric auth or will the latency kill the user experience?
• Build vs Buy: Is it cheaper to roll your own login logic or just pay for a service like Auth0? Usually, the maintenance on a custom db for passwords costs way more in the long run. (Why Total Cost of Ownership Is a Critical Metric in High-Availability ...)
• Threat Modeling: I like to map out the "attacker's path" to the login page now. If we're doing finance, we need way more protection than a local gym app.

A study by OWASP (2021) ranks identification and authentication failures as a top critical risk for web apps, which is why we vet this stuff early.

Honestly, I've seen projects die here because the "cool" security features were too expensive for the startup budget. Once the risks are cleared, we start drawing the actual blueprints.

Stage 3: Design and Architecture

Architecture is where we actually draw the blueprints before the hammers start swinging. If you screw this up, you're basically building a vault with a cardboard back door and trust me, fixing that in production is a nightmare.

We start by mapping out the logic. You gotta decide if you're using OIDC or SAML and how those tokens move between your frontend and the api. I usually wireframe the UX first to make sure we aren't making users jump through too many hoops, then I layer on the security.

• Database Schema: Never store passwords in plain text. Use a strong hashing algorithm like Argon2 or bcrypt with a unique salt for every user.
• Session Management: Decide if you're going stateless with JWTs or using server-side sessions. If it's a high-security finance app, I lean toward shorter token lifespans.
• Edge Cases: Plan for the "forgot password" flow and account recovery now so they aren't insecure afterthoughts.

I like using tools like Firebase Auth or Passport.js to scaffold out the auth modules early. It saves a ton of time on the boilerplate so I can focus on the complex logic.

Getting the architecture right here prevents "spaghetti code" later when you try to add things like social logins. Next, we actually start writing the code in the development phase.

Stage 4: Development and Coding

This is where the rubber meets the road. We take those design docs and actually start building the node.js backend or whatever stack you picked, but the goal is to write code that doesn't leak data like a sieve.

I always tell my team to stop reinventing the wheel with password storage. If you're manually writing a hashing function, you're doing it wrong. Use a library like argon2 or bcrypt and let it handle the heavy lifting.

• Password Hashing: Use a work factor that’s high enough to slow down attackers but won't melt your server cpu.
• mfa integration: This isn't optional anymore for apps in finance or healthcare. I like to build hooks for TOTP early so we can support apps like Google Authenticator.
• ai tools: Don't be afraid to use an ai-powered login builder to scaffold the frontend, it saves hours on css and basic api calls.

Here is a quick snippet for hashing in a Python app:

from passlib.hash import argon2

password = "super-secret-password"
hashed = argon2.hash(password)
is_correct = argon2.verify("user-input", hashed)

While using libraries like passlib makes development easier, you must also ensure the libraries themselves are secure. Honestly, I’ve seen devs get lazy here and skip input validation on the login api. Bad move. According to Snyk's 2023 State of Open Source Security, 80% of organizations have seen vulnerabilities in their third-party libraries, so keep your dependencies updated.

Once the code is written, we gotta make sure it actually works under pressure in the testing phase.

Stage 5: Testing and Integration

So you've written the code, but does it actually hold up when a bot tries to hammer your login api with a million requests? This is where we break things on purpose to make sure they don't break for real later.

I always start with automated tools to find the low-hanging fruit. You should be running DAST (Dynamic Application Security Testing) to check for things like sql injection in your username fields or cross-site scripting (XSS) in the error messages while the app is running. This contrasts with the SAST we did earlier which just looks at the raw code.

• Brute Force Testing: I set up a script to see if our rate limiting actually kicks in after five failed tries. If it doesn't, your server cpu will melt during a real attack.
• Integration Checks: We gotta make sure the node.js backend talks to AWS Cognito or your db without leaking secrets in the logs.
• User Acceptance (UAT): This is where real humans try the flow. If the mfa text takes ten minutes to arrive, users are gonna hate it.

A 2023 study by Snyk found that 80% of organizations found vulnerabilities in their third-party code, so checking your npm or pip packages here is huge.

Honestly, I’ve seen teams skip the "stress test" part and then wonder why their login service crashes on Black Friday. Once we know the app won't fall over, we move to getting it live.

Stage 6: Deployment and Implementation

Deployment is where the stress really kicks in. You’re pushing to prod and praying the api doesn't choke on live traffic.

• Staged Rollout: Use canary releases so a bad mfa config doesn't lock out everyone at once.
• Monitoring: Watch for spikes in 401 errors; it usually means a broken token flow.
• Secrets: Double-check that production keys aren't hardcoded in your docker files.

I usually use a script in a CI/CD pre-deploy hook to verify environment variables before the final push:

if [ -z "$AUTH0_DOMAIN" ]; then
  echo "missing auth0 config!"
  exit 1
else
  echo "Config verified. Proceeding to deploy..."
fi

Now that it’s live, we gotta keep it running smoothly.

Stage 7: Operations and Maintenance

Maintenance is where the real work begins. You can’t just "set and forget" a login system unless you want a disaster on your hands later.

• ai analytics: Use tools to spot weird login patterns.
• Library Patches: Keep your npm dependencies fresh.
• Hardware evolution: Update hashing cost factors or iteration counts as gpus get faster. If you don't increase the work factor, your old hashes become easy to crack on modern hardware.

According to GitLab's 2024 Global DevSecOps Report, security remains a top priority for developers, with many integrating automated scanning into their daily workflows to catch vulnerabilities early.

Stay vigilant, folks.