Why Traffic Spikes Should Not Blow Up Your Authentication Bill

A successful campaign should create a traffic problem you are happy to have.

Your new product launches.

A social post takes off.

A newsletter mentions you.

A creator sends thousands of visitors.

Suddenly your application is handling ten times its normal traffic.

That should be good news.

But there is an important distinction:

Website traffic is not the same as authentication usage.

100,000 visitors do not automatically mean 100,000 billable users.

Some people leave without creating an account.

Others sign up but never return.

Existing users may log in several times.

Bots may hammer the signup or login endpoint.

Some users authenticate through social login.

Others trigger SMS verification.

And different identity providers may count all of this differently.

For example, Auth0 describes MAU as unique user IDs that issue tokens during a month. The same user can issue multiple tokens and still count as one MAU.

Firebase Authentication with Identity Platform also uses monthly active users for much of its paid authentication pricing, while phone authentication introduces separate SMS-related charges and limits.

Clerk uses a different concept called Monthly Retained Users, where a user is not counted as retained unless they return after the first 24 hours.

That is why you cannot estimate authentication costs from website sessions alone.

You need to understand exactly what your provider meters.

The goal is not to prevent traffic spikes.

It is to make sure a successful launch, marketing campaign, or viral moment does not expose a pricing model you never properly understood.

Chapters

Every software company dreams of the day their application goes viral. You architect your databases to scale, you set up your cloud infrastructure to auto-scale horizontally, and you use content delivery networks to absorb the shock of a massive influx of users.

You prepare for the compute costs to rise proportionally with the traffic. However, there is a hidden financial landmine in modern software architecture that many engineering and finance teams do not anticipate: the authentication bill.

When your application experiences a sudden surge in traffic, your compute and bandwidth costs increase based on actual hardware usage. But if you are using a legacy or heavily commercialized identity and access management (IAM) provider, your authentication costs do not scale based on CPU cycles or bandwidth. They scale based on arbitrary pricing tiers and Monthly Active Users (MAUs). This has led many organizations to explore modern IAM solution, including platforms such as Scalefusion OneIdP, that offer streamlined identity and access management capabilities..

This fundamental disconnect between the cost of delivering a digital service and the price you pay for user authentication is a growing problem. In a well-architected system, traffic spikes should test your servers, not bankrupt your runway. Here is a concrete look at why traffic spikes occur, the mechanics of authentication billing, and why your auth bill should remain predictable even when your user base explodes.

The Hidden Mechanics of Authentication Pricing

To understand why a traffic spike can ruin your monthly budget, you have to look at the concrete mechanics of how traditional authentication providers calculate their costs. Most software-as-a-service (SaaS) Auth providers bill based on MAUs or active tokens.

How Traditional Auth Providers Calculate Costs

In a standard MAU pricing model, a user is counted the moment they log in, sign up, or refresh a token within a 30-day window. If you run a typical B2B application with 10,000 users who log in every day, your MAU count is 10,000.

But what happens if you run a B2C application? Your baseline traffic might be 10,000 users, but a single marketing campaign or a viral social media post could drive 100,000 unique visitors to create an account or log in just one time. Under traditional MAU billing, your provider immediately bumps you into a higher, enterprise-level pricing tier. You are not paying for the few kilobytes of data or the millisecond of CPU time it took to generate a JSON Web Token (JWT). You are paying a premium tax for acquiring new users.

The Penalty for Viral Success

The physical cost of authenticating a user is incredibly low. Generating a cryptographic token, hashing a password with bcrypt or Argon2, and checking a database record consumes fractions of a cent in cloud compute resources.

Yet, when a traffic spike occurs, SaaS auth providers do not charge you for the compute. They charge you a penalty for crossing a predefined threshold. If your viral moment brings in users who log in once and never return, you are still billed for them for the entire month—and sometimes locked into that higher pricing tier for the rest of your annual contract. This transforms authentication from a predictable infrastructure cost into a volatile liability.

Re-evaluating Your Identity Provider: Open Source vs. Commercial

When a massive spike in logins results in an invoice that dwarfs your entire AWS or Google Cloud bill, it forces a hard conversation between the Chief Technology Officer and the Chief Financial Officer. This is the exact moment when organizations realize that tying authentication costs to user counts is an unsustainable business model.

To regain control over infrastructure costs, engineering teams inevitably begin to look for an Auth0 alternative that aligns better with modern, cloud-native billing practices. The goal is to find a provider or an open-source solution where the cost of identity management is decoupled from the sheer volume of users in the database.

Flat-Rate Infrastructure vs. Per-User Billing

When evaluating these alternatives, the most concrete difference lies in the architectural billing model. Modern identity platforms, particularly those rooted in open-source ecosystems, often offer infrastructure-based pricing.

In this model, you pay for the throughput, the specific premium features you need (like advanced multi-factor authentication or enterprise SSO), and the operational SLA. If your user base spikes from 10,000 to 1,000,000 overnight, your bill remains completely flat, provided the physical server throughput can handle the load. This mirrors how you pay for load balancers or virtual machines: you pay for the pipe, not for the number of people looking at the water.

Concrete Examples of Traffic Spikes (Typical and Untypical)

Traffic spikes are not always the result of a brilliant marketing campaign. In the real world of software engineering, traffic anomalies come in various forms, some of which do not even represent real human users.

Expected Surges (Retail and Media)

Typical traffic spikes are predictable and tied to external events. For an e-commerce platform, Black Friday and Cyber Monday will routinely push user logins to 10 or 20 times the normal volume. For a media streaming application, the release of a highly anticipated television finale or a live sporting event will cause a massive, concurrent flood of authentication requests in a very narrow time window.

Because these events are expected, engineering teams scale up their Kubernetes clusters and read-replicas. However, if the Auth provider bills by MAU, the company will pay a massive premium for users who are only active for a single weekend out of the entire year.

The Untypical Spikes (Botnets and Unplanned Virality)

Untypical traffic spikes are far more dangerous to your auth bill because they are unplanned, and often, they are not even real users.

• Credential Stuffing Attacks: In this scenario, a botnet acquires a list of compromised passwords from a previous data breach and attempts to log in to your application using millions of different email combinations.
• Malicious Account Creation: Automated scripts may create hundreds of thousands of fake accounts to exploit a promotional offer, scrape data, or manipulate platform metrics.

If your authentication provider counts every successful (or sometimes even attempted) login or account creation as an active user, a single botnet attack can instantly max out your MAU limits. You end up paying thousands of dollars for the “privilege” of being targeted by a cyberattack, simply because the pricing model is inherently flawed.

Architecting for Predictable Authentication Costs

To protect your business from unpredictable billing, you must architect your identity and access management layer with the same financial prudence you apply to your database storage or compute instances.

Decoupling identity from per-user pricing requires a shift in how you select your tech stack. You must look at the underlying technology of the provider. Are they hosting a multi-tenant environment where they limit your database rows to force an upgrade? Or are they providing a dedicated, scalable infrastructure where you own the data and control the throughput?

Strategies for Mitigating Bill Shock

Taking control of your authentication architecture involves several concrete technical and business decisions.

• Self-Hosting Open Source Solutions: Deploying open-source identity servers directly within your own cloud environment. You manage the database and the containers. Your only cost is the raw AWS or Azure compute, meaning 100,000 new users might cost you an extra three dollars in CPU time.
• Choosing Throughput-Based Managed Services: If you do not want to manage the infrastructure yourself, opt for managed identity providers that charge based on feature sets or operational bandwidth rather than headcounts.

Implementing rate limiting and strict bot protection at your Web Application Firewall (WAF) layer also prevents untypical spikes—like credential stuffing—from ever reaching your authentication servers. By stopping the bots at the edge of your network, you ensure that your identity provider only processes legitimate traffic.

Building for the Future

Authentication is a fundamental utility of the internet, much like DNS or TLS encryption. It is a mathematical process of verifying identity, generating a token, and managing a session state. It is not a premium marketing feature, and it should not be billed like one.

When you build a digital product, you want to encourage user growth, not fear it. Traffic spikes, whether from a viral marketing success or an unexpected media mention, should be celebrated by your entire organization. By moving away from legacy MAU pricing models and adopting infrastructure-aligned identity solutions, you guarantee that your application can scale infinitely without turning your next great success into a financial disaster.

Traffic, Signups, Logins, and Billable Users Are Different Metrics

Marketing teams usually think in:

• Visitors
• Sessions
• Clicks
• Leads
• Signups
• Conversions

Authentication platforms may think in:

• Monthly active users
• Monthly retained users
• Daily active users
• Successful authentications
• Tokens
• SMS messages
• Enterprise connections
• Machine-to-machine tokens
• Organizations
• Fraud checks

Those numbers are related.

They are not interchangeable.

Consider a campaign generating 100,000 visits.

The headline traffic number is therefore a poor predictor of the authentication invoice.

Model the conversion path instead.

Understand the Billing Unit Before You Compare Authentication Providers

Two identity providers may both advertise:

50,000 users included.

That does not necessarily mean the same thing.

One may meter MAUs.

Another may meter retained users.

Another may charge separately for SSO connections.

Another may include authentication but charge per verification SMS.

Another may price machine-to-machine authentication separately.

Before comparing prices, identify the billing unit.

The word user is not specific enough.

Ask how the vendor defines one.

MAU Does Not Always Mean the Same Thing

“Monthly active user” sounds like an industry-standard unit.

The implementation can still differ by provider.

Auth0 currently counts unique user IDs that issue tokens during the month. Once that user is active, issuing additional access tokens does not repeatedly increase the MAU count for the same user.

Firebase Authentication with Identity Platform defines an active user as someone who uses their account during the billing period, with a no-cost allowance before paid MAU pricing begins.

Stytch also currently uses MAUs in its pricing, while separately pricing items such as additional SSO/SCIM connections, M2M tokens, and optional fraud-prevention usage.

So instead of asking:

How much do you charge per MAU?

ask:

Exactly what event turns someone into a billable MAU?

That one question can materially change your forecast.

A Viral Signup Is Not Necessarily a Valuable User

Imagine 50,000 people create accounts after your product goes viral.

That looks fantastic in a growth dashboard.

Thirty days later:

45,000 never came back.

Your marketing team may call them signups.

Your authentication provider may still have counted many of them for billing purposes depending on its pricing model.

That creates a useful metric:

Authentication cost per retained user

Instead of looking only at:

Authentication bill ÷ signups

consider:

Authentication bill ÷ users who actually return and use the product

That gives product, marketing, and finance teams a more realistic view of whether acquisition and infrastructure economics are aligned.

Model Authentication Costs Before a Large Campaign

Marketing forecasts usually include:

• Ad spend
• CPM
• CPC
• Conversion rate
• Leads
• Sales
• Revenue

For a product requiring accounts, add authentication.

Suppose you expect:

500,000 landing-page visitors.

20% reach signup.

40% complete signup.

That produces:

40,000 new accounts.

Now ask:

How many will authenticate?

How many will return?

How many require SMS?

How many use enterprise login?

How many are existing users?

How many fake accounts might be blocked before reaching the identity provider?

A basic forecast could look like this:

Take those numbers to the pricing calculator.

Do not take:

500,000 visitors.

This also makes collaboration between marketing and engineering much easier.

Marketing knows what it wants to generate.

Engineering understands what that activity means for infrastructure and identity usage.

Forecast More Than One Traffic Scenario

Campaign plans are usually built around the expected outcome.

Infrastructure planning should include the unexpected one.

Model at least:

You do not need to predict which one will occur.

The exercise tells you whether the cost curve remains acceptable if it does.

Watch for Pricing Cliffs

Usage-based pricing is easiest to forecast when additional usage increases costs gradually.

Problems appear when pricing contains cliffs.

For example:

Up to 50,000 users = Plan A.

50,001 users = much more expensive contract.

That extra user did not suddenly make authentication dramatically harder to provide.

But commercially, it may put you into another pricing category.

Before signing a contract, model what happens at:

• 10,000 users
• 25,000 users
• 50,000 users
• 100,000 users
• 500,000 users
• 1 million users

Do not ask only:

What does authentication cost us today?

Ask:

What happens if we succeed?

Include SMS Authentication in Your Cost Model

Phone authentication creates a separate cost category that is easy to overlook.

Firebase, for example, bills phone authentication based on SMS messages and applies separate phone-authentication quotas and limits.

Suppose a campaign generates 25,000 new users.

If each user receives:

1 signup verification message

and some require:

1 retry

and later:

1 passwordless login message

your SMS volume can be much higher than the number of new users.

Model:

users × average messages per user × SMS cost

Also watch for:

• Repeated verification attempts
• Invalid numbers
• International destinations
• Bot-generated requests
• Passwordless login frequency
• MFA messages

A user-based authentication plan can look predictable while messaging costs quietly grow beside it.

Protect SMS Endpoints From Abuse

SMS endpoints are attractive targets because attackers can generate a real financial cost.

A script does not necessarily need to compromise an account.

It may simply trigger thousands of verification requests.

Set protections around:

• Signup
• Login
• Password reset
• MFA
• Phone-number verification

Firebase itself enforces limits on verification requests and SMS sending, including per-IP limits for some operations.

Your application should have its own abuse controls too.

Consider:

• Rate limits
• CAPTCHA or bot challenges
• Device signals
• Per-account limits
• Per-phone-number limits
• IP intelligence
• Risk-based authentication

Protect the expensive action.

Not only the page leading to it.

Bot Traffic Can Distort Both Security and Cost

A sudden login spike does not necessarily mean your marketing finally worked.

It could be:

• Credential stuffing
• Password spraying
• Brute-force activity
• Fake account creation
• Promotional abuse
• Scraping
• Automated testing

OWASP specifically identifies credential stuffing and automated account creation as common automated threats against authentication systems.

That means authentication monitoring needs to separate:

human growth

from:

automated abuse

Otherwise your dashboard might celebrate a traffic spike while security is fighting an attack and finance is watching usage charges climb.

Rate-Limit Authentication Endpoints Separately

Your homepage and login endpoint do not have the same risk.

Do not necessarily give them the same traffic rules.

OWASP recommends endpoint-specific defenses for automated abuse and notes that login endpoints can benefit from rate limits combined with additional signals.

AWS WAF similarly documents rate-based rules scoped specifically to login URLs rather than throttling the entire website.

That distinction is useful.

Your marketing campaign should be able to send massive traffic to:

/pricing

without automatically permitting the same request rate to:

/login

or:

/send-verification-code

Protect sensitive endpoints individually.

Do Not Rely on IP Rate Limiting Alone

A simple rule might say:

Block an IP after 100 failed login attempts.

That helps.

But sophisticated attacks can use thousands of IP addresses.

OWASP recommends layered defenses because credential stuffing can be distributed across large proxy networks, making basic IP blocking or per-IP thresholds insufficient on their own.

Useful signals can include:

• Account
• IP
• IP range
• ASN
• Device
• Geography
• Login velocity
• Failed attempts
• Number of accounts targeted
• Known proxy infrastructure
• Browser behavior

The purpose is not to make login difficult for everyone.

It is to make automated abuse expensive while legitimate users continue normally.

Use MFA Strategically

Multi-factor authentication can greatly reduce the risk of compromised passwords being reused successfully.

OWASP describes MFA as one of the strongest defenses against credential stuffing and password spraying and also recommends risk-based approaches where additional verification is triggered by suspicious conditions.

For example, additional authentication may be appropriate when:

• A device is new
• Location changes dramatically
• An IP has targeted many accounts
• Login behavior appears automated
• A user attempts a sensitive action

This can reduce unnecessary friction compared with treating every login identically.

It can also affect cost if your MFA method uses paid SMS.

Security architecture and billing architecture are connected.

Separate Human Authentication From Machine Authentication

Modern applications increasingly authenticate more than people.

You may also have:

• Backend services
• APIs
• Scheduled jobs
• AI agents
• Integrations
• Partner applications
• Internal automation

These often use machine-to-machine credentials or tokens rather than human login sessions.

Some identity providers price these separately.

Stytch, for example, currently includes a specific allowance for M2M tokens and prices additional usage separately from its user allowance.

When forecasting authentication costs, create separate categories:

Human identity

and:

Machine identity

A company can have 5,000 employees but hundreds of thousands of service interactions.

Do not assume one pricing unit covers both.

Anonymous Accounts Need Special Attention

Some apps create anonymous users before someone registers.

That can improve onboarding.

It can also create enormous user counts.

Imagine every visitor automatically receives an anonymous account.

A viral campaign sends 1 million visitors.

Suddenly you have an identity problem much larger than your actual registered customer base.

Check how your identity provider treats anonymous users.

Firebase Authentication with Identity Platform, for example, provides an option to automatically clean up anonymous accounts older than 30 days, and accounts covered by that cleanup are not counted toward its billing and usage quotas.

If your product uses anonymous authentication, understand:

• When the account is created
• When it becomes billable
• When it expires
• Whether it is automatically deleted
• How it converts to a permanent account

Anonymous identity is still identity infrastructure.

Do Not Force Authentication Too Early

There is also a product-design solution to authentication costs:

Do users need an account yet?

Some products require login immediately.

Others could allow visitors to:

• Browse
• Search
• Preview
• Calculate
• Configure
• Explore
• Read documentation
• Test limited functionality

before registration.

That can improve the user experience while reducing unnecessary account creation.

Instead of:

Landing page → Signup → Product

consider:

Landing page → Product experience → Signup when value is clear

The right design depends on your product.

But authentication should solve a real access or identity requirement.

It should not automatically become the first screen simply because every SaaS product seems to have a login box.

Monitor Authentication Like a Business Metric

Engineering monitors uptime.

Marketing monitors conversions.

Finance monitors invoices.

Authentication costs sit between all three.

Create visibility around:

Once these metrics are visible together, surprise bills become much less surprising.

Create Authentication Cost Alerts

Do not discover a spike when the invoice arrives.

Create alerts for:

• Unexpected signup growth
• Sudden MAU acceleration
• SMS volume
• Failed login spikes
• Password reset spikes
• New account velocity
• Bot activity
• Authentication API volume
• Fraud-check consumption
• Budget thresholds

Useful alerts could include:

50% increase in daily account creation

SMS usage exceeds expected campaign volume

Failed logins exceed normal baseline by 5x

Projected MAU usage approaching plan threshold

The exact thresholds depend on your product.

The important part is monitoring the trend before billing closes.

Marketing Should Tell Engineering Before a Big Campaign

A surprising amount of infrastructure pain can be prevented by one message:

We are launching a large campaign on Monday.

Marketing often knows when traffic may increase.

Engineering may know what that traffic means for:

• Servers
• Databases
• Authentication
• Email
• SMS
• APIs
• Rate limits

Connect those teams before launch.

A simple campaign brief could include:

A marketing win should not surprise the technical team responsible for serving it.

Ask These Questions Before Signing an Authentication Contract

Pricing pages rarely answer every edge case.

Ask the vendor directly.

User Counting

• What exactly makes someone billable?
• Are first-time users counted?
• Are anonymous users counted?
• Are inactive stored users counted?
• What happens when an account is deleted?

Authentication Activity

• Do repeated logins change billing?
• Are refresh-token exchanges billable?
• Are failed login attempts billable?
• Are verification requests billable?

Messaging

• How are SMS messages charged?
• Are email verification messages included?
• Are international SMS rates different?

B2B Features

• How are SSO connections priced?
• Is SCIM separate?
• Are organizations or tenants billed?

Machine Identity

• How are M2M tokens priced?
• Are API clients billed separately?

Abuse

• Can bot-generated accounts become billable?
• Are fraud checks included?
• What protections exist against signup abuse?

Growth

• What happens when we cross the plan limit?
• Is there a grace period?
• Is pricing progressive or does the entire account move tiers?
• Can usage automatically trigger an enterprise contract?

Contract

• Can pricing change during the term?
• Is there a minimum commitment?
• Are overages automatic?
• Can we export our identities if we leave?

Get the answers before your user graph looks like a hockey stick.

Calculate the Real Authentication Cost

Do not compare providers using only:

base monthly subscription

Build a broader model.

A simplified calculation could include:

Base plan

plus:

Billable users

plus:

Enterprise connections

plus:

SMS

plus:

M2M

plus:

Fraud prevention

plus:

Support

plus:

Operational cost

plus:

Migration cost

The cheapest-looking login provider can become expensive if your application heavily uses separately billed features.

The reverse can also happen.

A platform with a higher base fee may simplify enough infrastructure to reduce engineering work elsewhere.

Compare total cost.

Not one row on a pricing page.

Authentication Pricing Comparison Checklist

When Should You Re-Evaluate Your Authentication Provider?

Do not migrate identity infrastructure every time another vendor becomes slightly cheaper.

Authentication is critical infrastructure.

Migration has real cost and risk.

But review the setup when:

• User growth changes dramatically
• Authentication becomes a meaningful infrastructure expense
• MAU pricing no longer matches your business model
• Enterprise SSO grows rapidly
• SMS costs become significant
• Bot activity creates unpredictable usage
• Machine identities become a larger part of the system
• Required security features are locked behind expensive tiers
• Your current provider creates a major pricing cliff
• You cannot forecast next year’s authentication spend

Sometimes negotiation solves the problem.

Sometimes architecture solves it.

Sometimes another identity provider genuinely makes more sense.

Do Not Optimize Authentication Cost at the Expense of Security

Predictable billing matters.

Security matters more.

Do not respond to high authentication costs by weakening:

• MFA
• Password hashing
• Session security
• Bot protection
• Rate limiting
• Monitoring
• Account recovery
• Fraud prevention

The objective is:

secure authentication with understandable economics.

Not:

the cheapest possible login endpoint.

A lower invoice is not a win if account takeovers increase.

Do Not Optimize Security at the Expense of Legitimate Growth Either

The opposite mistake also happens.

A company experiences bot traffic and responds by making signup painful for everyone.

Now real customers face:

• Multiple CAPTCHAs
• Aggressive blocks
• Verification loops
• False-positive fraud detection
• Slow login flows

OWASP recommends layered, risk-based defenses rather than relying on a single crude control.

The goal is to identify abnormal behavior while allowing legitimate growth.

A viral campaign should not look identical to a credential-stuffing attack just because both create traffic spikes.

Context matters.

Frequently Asked Questions

Can Website Traffic Increase My Authentication Bill?

Not necessarily.

Normal anonymous website traffic may never reach the authentication provider.

Costs usually depend on the specific billable actions defined by your identity provider, such as active users, retained users, SMS verification, enterprise connections, machine tokens, or other usage.

What Is a Monthly Active User in Authentication?

A monthly active user is generally a unique user who performs qualifying authentication activity during a billing month.

The exact definition varies by identity provider.

Auth0, for example, currently counts unique user IDs that issue tokens during the month.

Always check the provider’s own billing definition.

What Is the Difference Between MAU and MRU?

MAU usually means Monthly Active User.

MRU means Monthly Retained User.

Clerk currently uses MRU and only considers a user retained if they return to the app more than 24 hours after initially signing up.

This means a burst of one-time signups can affect MAU and MRU pricing models differently.

Can One User Be Counted Multiple Times in the Same Month?

It depends on the billing model.

Under Auth0’s current MAU definition, the same user can issue many access tokens during a month and still count as one MAU.

Request-based or messaging-based charges may behave differently.

Does SMS Authentication Cost Extra?

It can.

Firebase, for example, bills phone authentication SMS separately and applies additional quotas and limits to verification traffic.

Check the per-message price for the countries where your users are located.

Can Bot Traffic Increase Authentication Costs?

Potentially.

The impact depends on what the provider meters and how far the automated traffic gets through your authentication flow.

Fake account creation, repeated verification messages, fraud checks, and other activity may consume billable resources.

Use bot protection and rate limiting around sensitive authentication endpoints.

What Is Credential Stuffing?

Credential stuffing is an automated attack where username and password combinations obtained from previous breaches are tested against another service.

OWASP recommends layered defenses including MFA, rate limiting, bot detection, IP intelligence, and other risk signals.

Should I Rate-Limit My Login Page?

Usually, yes, but the implementation matters.

OWASP recommends layered authentication defenses and warns that attackers can distribute credential-stuffing attempts across many IP addresses.

AWS WAF also supports rate-based rules scoped specifically to login paths.

Does MFA Increase Authentication Costs?

It can depending on the MFA method and provider.

SMS-based MFA may create messaging charges.

Authenticator apps, passkeys, hardware keys, and other factors have different infrastructure and pricing characteristics.

Consider both security and operating cost when choosing the method.

How Do I Estimate Authentication Costs for a Marketing Campaign?

Forecast:

• Campaign visitors.
• Signup-page visitors.
• Completed accounts.
• Successfully authenticated users.
• Returning users.
• SMS verification volume.
• Enterprise or machine authentication where applicable.
• Expected bot or abuse traffic.

Then map those numbers to your provider’s actual billing rules.

Should Marketing Teams Care About Authentication Pricing?

If campaigns drive account creation, yes.

Marketing does not need to manage the identity infrastructure, but teams should understand whether significant signup growth can affect variable platform costs.

Large campaigns are easier to support when marketing, product, engineering, security, and finance share forecasts before launch.

What Authentication Metrics Should We Monitor?

Useful metrics include:

• New accounts
• Active users
• Retained users
• Login attempts
• Failed logins
• SMS messages
• Password resets
• Bot blocks
• M2M usage
• Authentication cost
• Authentication cost per active user
• Authentication cost per retained user

Is Self-Hosted Authentication Always Cheaper?

No.

Self-hosting can remove some SaaS pricing structures, but it introduces other costs.

You become responsible for more of:

• Infrastructure
• Security
• Availability
• Updates
• Monitoring
• Incident response
• Compliance
• Engineering maintenance

Compare total cost and operational risk rather than subscription price alone.

Growth Should Be Good News

The wrong time to learn how authentication pricing works is the morning after your product goes viral.

Know the billing unit before launch.

Understand what makes a user billable.

Separate traffic from identity activity.

Forecast SMS and machine authentication separately.

Protect signup and login endpoints from automated abuse.

Monitor authentication usage before invoices arrive.

And model what happens when user growth is dramatically better than expected.

Your authentication system should be able to answer two questions:

Can we handle the traffic?

and:

Can we afford the traffic?

If the answer to either one is unclear, there is work to do.

A traffic spike should make your team think:

Great, people found us.

Not:

Please don’t let them log in.

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