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Architecture Consulting

Infrastructure built
to 10x
without breaking.

Scale events, capacity ceilings, database migrations, multi-region failover. We design the infrastructure before the problem forces your hand.

BITHOST ARCHITECTURE REVIEW client: acme-corp · target: 10x growth · timeline: 90 days CAPACITY: CRITICAL v2.4 — APPROVED ◉ CURRENT — WILL FAIL AT 3x Single App Server 4 vCPU · 16GB · 1 AZ Single RDS (no replica) db.t3.medium · 1 AZ ⚠ No LB · No failover · No CDN ⚠ DB at 78% capacity now ⚠ p99 latency: 4,200ms REDESIGNED → ◉ TARGET — HANDLES 10x CloudFront CDN · Global edge · Cache-hit rate: 82% Application Load Balancer · Health checks · WAF App node 1 (AZ-a) 8 vCPU · 32GB App node 2 (AZ-b) 8 vCPU · 32GB App node 3 (AZ-c) 8 vCPU · 32GB ↕ Auto-scale min:3 max:20 target CPU: 60% Aurora PostgreSQL Cluster · Writer (AZ-a) · 2× Readers (AZ-b, AZ-c) db.r6g.2xlarge · Auto-scaling storage · PITR 35d · Read replica lag: 8ms ✓ p99 latency: 180ms ✓ 99.97% uptime SLA ✓ Cost: ▼18% vs naive CAPACITY FORECAST projected traffic growth vs infrastructure limit Now 28% capacity 3 mo 52% capacity 6 mo 68% ⚠ 12 mo OVER LIMIT ✗ Recommended action: upgrade before month 5 DB ARCHITECTURE DECISION Option A: Aurora sharding Cost: $2,400/mo · Write scale: 10x · Complexity: HIGH Option B: Aurora + read replicas ✓ RECOMMENDED Cost: $1,820/mo · Read scale: 15x · Complexity: LOW Option C: Migrate to PlanetScale Cost: $3,100/mo · Unlimited scale · Migration: 8 weeks Verdict: Option B handles 10x with current schema. Revisit Option C at 50x.
Scale target
10x
Designed and validated before build
Architecture outcome
p99: 180ms Cost: ▼18% 99.97% SLA
Capacity Planning Load Testing Multi-Region Failover DB Architecture Horizontal Scaling Disaster Recovery Performance Engineering Cost vs Availability Database Migration Traffic Spike Design Multi-Cloud Strategy Auto-scaling Capacity Planning Load Testing Multi-Region Failover DB Architecture
Questions we answer

The hard calls
before they cost you.

These are the decisions that feel expensive to get advice on and catastrophic to get wrong. We have made them dozens of times across different stacks and scales.

"We are expecting 10x traffic in 90 days. Will our infrastructure hold?"

We model your current throughput against the projected load, identify the bottlenecks in order and give you a sequenced upgrade plan with cost estimates for each step.

Capacity modelling
"Design us a multi-region failover strategy that keeps RTO under 5 minutes."

We design the active-passive or active-active topology, define the health check logic, DNS failover configuration and the runbook your team follows when a region goes down.

Disaster recovery design
"Our database is hitting limits. Should we shard, add read replicas, or migrate?"

We assess your query patterns, write-to-read ratio and growth trajectory and recommend the right lever with the migration path and expected cost for each option.

Database architecture
"How do we balance cost and availability for our specific workload?"

We map your availability requirements to the cheapest architecture that meets them. Most teams overprovision by 30 to 50 percent because no one has done this analysis deliberately.

Cost vs reliability
The stakes

Wrong decisions
are expensive.

Architecture mistakes compound. The cost of getting advice is always smaller than the cost of fixing a mistake at scale.

$6k+

One unplanned outage at scale

Revenue, SLA credits, customer churn and engineering time to fix an architecture that should have been designed correctly the first time.

40%

Average cloud bill reduction after rightsizing

Most teams that have never had an architecture review are running 30 to 50 percent more infrastructure than their actual load requires.

6 mo

Typical re-architecture project when done reactively

Planned at the right time it takes 6 weeks. Done under pressure after an outage or a scale failure it takes 6 months and costs 10x more.

0

Number of successful 10x migrations without prior planning

Every company that scaled successfully planned the architecture before they needed it. Every company that did not has a horror story.

What we deliver

Five high-value
engagements.

Each engagement produces a concrete deliverable: a diagram, a decision, a plan, a recommendation. Not a report that sits unread.

01

Infrastructure Design for Scale

Current state assessment, bottleneck identification, target architecture design and a sequenced upgrade plan with cost modelling for each milestone.

Load modelBottleneck mapCost forecast
02

Disaster Recovery Planning

Multi-region topology design, RTO and RPO targets defined, failover runbook written and tested, recovery procedures validated before you need them.

RTO / RPOFailover designRunbook
03

Database Architecture Consulting

Query pattern analysis, growth trajectory modelling, shard vs replica vs migration decision with comparative cost and complexity scoring and a migration plan.

Query analysisOption scoringMigration plan
04

Multi-Cloud Strategy

Workload-to-cloud mapping, vendor lock-in assessment, cost comparison across providers and a placement strategy that matches each workload to the platform that runs it best.

Workload mappingCost comparisonPlacement plan
05

Performance Engineering Retainer

Ongoing architecture guidance as your stack grows. Monthly capacity reviews, performance regression alerts and ad-hoc design consultations when decisions need to be made fast.

Monthly reviewRegression alertsAd-hoc consult
06

Load Testing and Capacity Validation

Synthetic load generation against your production-like environment, failure point identification, auto-scaling behaviour validation and a written capacity report.

Load generationFailure pointsCapacity report
How we work

From question
to decision.

01
Architecture discovery

We map your current stack, traffic patterns, growth targets and constraints. We ask about your business plans not just your tech stack.

02
Load and capacity modelling

We model your current headroom against projected growth and identify the exact components that will fail first and at what load.

03
Options and trade-offs

We produce two or three concrete options with cost, complexity and risk scored for each. You make an informed decision rather than guessing.

04
Architecture document delivered

A written architecture decision record, diagram and implementation plan. Concrete enough for your engineers to build from without interpretation.

Step 1 — Architecture discovery Example engagement
Current state — what we mapped on day one
Single-AZ application tier with no load balancerOne server handling all traffic. Any failure means full downtime.
Database at 78% capacity on a db.t3.mediumAt projected growth rate this hits ceiling in approximately 14 weeks.
No CDN. All requests hitting the origin serverStatic assets consuming 65% of application server CPU unnecessarily.
p99 latency already at 4,200ms under current loadWill reach 12 seconds at 2x. User abandonment begins above 3 seconds.
Daily automated backups in placeGood. Recovery point is acceptable. Recovery time is not.

This architecture will not survive 3x traffic. The ceiling is the database followed immediately by the single app server. Both need to be addressed before month 4.

Capacity model — load vs headroom
App tier now
28%
DB now
78%
App at 3x traffic
84%
DB at 3x traffic
FAIL
App at 10x (new)
60%
DB at 10x (new)
45%

Database fails first at 3x. The application tier needs a load balancer and auto-scaling but has more runway. The redesigned architecture handles 10x with 40 to 55% headroom on both tiers.

Options scored — cost vs complexity vs risk
Option A: Aurora + read replicas — $1,820/monthHandles 10x reads. Low complexity. Recommended for current trajectory.
Option B: Database sharding — $2,400/monthHandles 10x writes. High complexity. Only needed if write volume dominates.
Option C: PlanetScale migration — $3,100/monthUnlimited scale. 8-week migration. Best choice at 50x not 10x.
App tier: ALB + Auto Scaling + CloudFrontEstimated cost $620/month additional. Resolves latency and availability simultaneously.

Recommendation: Option A for database, ALB plus CDN for app tier. Total additional spend: $2,440/month. Headroom until 10x growth with no further changes required.

Deliverable — what you receive
Architecture diagram: before and afterAWS-standard notation. Usable directly in engineering planning sessions.
Capacity model spreadsheetYour growth projections mapped to infrastructure headroom. Updateable as assumptions change.
Decision record: database optionsThree options with cost, complexity and risk scored. Recommendation written and justified.
Implementation sequencePrioritised by risk reduction per dollar. Which change to make first and why.
Terraform templates for target architectureInfrastructure code for the recommended state. Your team can deploy directly.

Delivered in 5 to 10 business days for most architecture reviews. Complex multi-region or multi-cloud engagements are scoped individually.

10× avg
scale target clients
design for
5–10 days
architecture review
to deliverable
40%
average cloud cost
reduction after review
0
generic templates.
every design is bespoke.
FAQ

Before you
book the call.

If you are seeing latency increase or error rates rise as traffic grows, the problem is usually architecture rather than observability. Monitoring tells you something is wrong. Architecture review tells you why it is wrong and what to do about it. If your system handles load fine but you do not know when it will stop doing so, a capacity planning engagement is what you need rather than a full review.
The answer depends almost entirely on your write-to-read ratio and query pattern. Most teams that think they have a write scaling problem actually have a read scaling problem, which read replicas solve at a fraction of the cost and complexity of sharding. We analyse your actual query distribution before recommending anything. Migration to a different database engine is the right call far less often than the database vendors would have you believe.
Active-active is significantly more expensive and complex and is the right choice only if you genuinely need zero-downtime in the event of a full regional failure. Most businesses need a recovery time objective measured in minutes rather than milliseconds, which active-passive with automated DNS failover achieves at 20 to 40 percent of the cost. We define your actual RTO and RPO requirements first and then match the architecture to them.
We pull 90 days of utilisation data across compute, database, storage and network transfer and compare actual peak usage to provisioned capacity. The waste is almost always in compute instances sized for peaks that only occur during deployments or load tests, and in databases running at 20 percent utilisation because someone picked a large instance to be safe. We typically find 25 to 45 percent savings within the first week of analysis.
A standard review takes 5 to 10 business days depending on the complexity of your stack. You receive a before-and-after architecture diagram, a capacity model showing your growth headroom, a decision record for any major technology choices with options scored by cost, complexity and risk, and a prioritised implementation sequence. For clients who want us to implement the changes we scope that as a separate engagement.

Design it right
before the
traffic forces you to.

A 60-minute discovery call to map your current architecture and identify where the ceiling is. No commitment beyond the call.

Book a design review
Capacity planning · Disaster recovery · Database architecture · Multi-cloud strategy