Reduce AWS costs and fix backend performance issues in scaling SaaS systems.We help engineering teams optimize, modernize, and stabilize backend infrastructure using Go, AWS Lambda, and serverless architecture.
AWS spend should not grow blindlyWe find waste and fix the architecture
Production load exposes real bottlenecksGo services, queues, data paths—engineered, not guessed
Serverless and events when they earn their placeLess ops drag, clearer boundaries
Most scaling systems fail in the same 3 ways
AWS costs outpace value
Monthly cloud spend grows with traffic while architecture stays unchanged. Waste hides in Lambda configuration, API Gateway, data transfer, and idle capacity.
APIs degrade under real load
Latency spikes, timeouts, and flaky dependencies show up in production—not in demos. Hot paths in Go services, queues, and databases need engineering, not more instances.
Legacy architecture slows shipping
Monoliths and manual ops block safe deploys. Teams want event-driven, serverless boundaries so they can release often without overnight maintenance windows.
Services
Productized backend engagements—clear scope, senior execution, no generic dev shop retainers.
AWS cost optimization audit
Baseline spend, find waste in compute, Lambda, API Gateway, networking, and storage, and deliver a prioritized savings plan your team can implement or we can execute with you.Get an AWS cost analysis
Backend performance engineering
Trace production bottlenecks, tune Go services and distributed workflows, and improve latency and reliability under load—not just load-test dashboards.Book a performance audit
Serverless migration
Design event-driven boundaries, move suitable workloads to AWS Lambda, and reduce operational overhead while keeping data consistency and observability explicit.Request a systems review
We work with
- SaaS companies moving from MVP to serious growth
- Engineering teams seeing AWS bills rise faster than revenue
- Startups where APIs or workers fail under production traffic
- CTOs modernizing legacy backends toward Lambda and event-driven design
Outcomes we target
Engineering-led engagements with measurable infrastructure results.
20–40% AWS cost reduction
After audit and remediation planning: rightsizing, Lambda and API Gateway tuning, caching, and cutting redundant spend—not generic “finops slides.”
2x–5x faster API paths (typical range)
Latency improvements from profiling Go services, fixing N+1 and IO patterns, queues, and concurrency—validated against production-like load.
Stability under production load
Fewer incidents from timeouts and overload when backpressure, limits, and failure domains are designed in—not bolted on after an outage.
Faster, safer deploy cycles
Serverless and event-driven boundaries reduce operational drag so teams ship smaller changes with less risk.
Representative case studies
Anonymized examples reflecting common engagement patterns. Your architecture and numbers will differ; the approach is the same.
B2B SaaS — runaway Lambda bill
Problem: Monthly AWS spend jumped 3x after a traffic milestone. Lambda concurrency, API Gateway, and outbound data dominated; no single owner for cost.
Solution: Cost audit, concurrency and memory tuning, API caching layer, and removal of redundant cross-region chatter. Documented guardrails for future changes.
Result: ~32% infrastructure cost reduction within one billing cycle; p95 API latency improved ~40% from fewer duplicate calls.
Growth-stage API — timeouts at peak
Problem: Core Go service showed acceptable latency in staging but 5xx and tail latency spiked under production concurrency; database and fan-out patterns were the suspects.
Solution: Production profiling, query and batching fixes, bounded worker pools, and queue-backed offload for non-critical work.
Result: p99 latency ~60% lower at peak; error rate dropped below prior SLO; team gained a repeatable load profile for releases.
Legacy monolith — slow, risky deploys
Problem: Single deployable blocked feature teams; scaling meant bigger instances; incident recovery was manual.
Solution: Strangled high-churn domains into Lambda handlers and event buses; kept transactional core on existing DB with clear boundaries and observability.
Result: Deploy frequency moved from bi-weekly to multiple times per week for migrated surfaces; on-call pages for that domain dropped sharply in the following quarter.
About Ciphergram
Ciphergram is a backend systems consultancy founded by engineers who specialize in Go, AWS, and distributed systems design. We focus on infrastructure-level problems that directly affect cost, performance, and scalability—not front-end experiments or generic product builds.
We work the way your CTO or platform lead would want: narrow scope, explicit tradeoffs, and recommendations you can implement or hand to your team with confidence.
Why technical leaders bring us in
- Deep Go backend engineering for services, workers, and high-throughput paths
- Hands-on AWS and Lambda experience—not slideware architecture
- Systems architecture background spanning event-driven design, reliability, and cost-aware scaling
Since 2014 we have shipped and advised on production systems. Today the practice is deliberately focused: AWS cost optimization, backend performance engineering, and serverless migration for SaaS and scaling startups.
When the bill or latency curve breaks, you need systems engineers—not a generic dev shop
Tell us about your stack, AWS footprint, and what production is doing under load. We respond with a scoped review or audit plan, not a pitch deck.
Engagements
Scoping starts with your stack, traffic patterns, and business constraints. Below are typical shapes of work—not shopping-cart SKUs.
Cost optimization audit
Fixed scope · 2–4 weeks typical
- Billing and resource inventory across AWS accounts
- Waste analysis: Lambda, API Gateway, data transfer, storage
- Prioritized remediation list with expected savings bands
- Optional implementation support
Performance engineering sprint
Time-boxed · senior engineers
- Production profiling and bottleneck analysis
- Go service and distributed systems tuning
- Load validation against agreed scenarios
- Runbooks and monitoring gaps called out explicitly
Serverless migration program
Phased · architecture-first
- Domain boundaries and event design
- Lambda, queues, and integration patterns
- Cutover plans with rollback and observability
- Knowledge transfer for your platform team
If you are unsure where to start, we begin with a short technical review and point you to the right engagement.
Request a backend systems reviewFrequently asked questions
What does Ciphergram do?
Ciphergram is a specialist backend systems consultancy. We help SaaS companies and scaling startups reduce AWS costs, improve backend performance, and modernize legacy systems using Go, AWS Lambda, and serverless architecture.
Who do you work best with?
SaaS teams scaling past MVP, engineering organizations with rising AWS bills, startups seeing production performance issues, and CTOs evolving legacy systems toward serverless and event-driven designs.
What is an AWS cost optimization audit?
A fixed-scope review of how your AWS bill maps to actual workloads: Lambda, API Gateway, compute, networking, and storage. You get a prioritized list of changes with expected savings and risk notes—not a generic dashboard export.
Do you work with existing Go codebases?
Yes. Go is a core language for our performance work. We profile services under load, tighten hot paths, and align concurrency and IO patterns with how your system runs in production.
How do engagements begin?
Most teams start with a backend systems review or a cost and performance audit. We clarify scope, access needs, and success metrics before work starts so expectations stay grounded in measurable infrastructure outcomes.
Request a backend systems review
Share your stack, symptoms, and AWS context. We reply with next steps for a cost analysis, performance audit, or migration assessment—usually within one business day.
CONTACT US
ADDRESS
20 North Orange Avenue, Unit 1100
Orlando, Florida 32801
CALL US
1-708-517-9987