1
Request traffic
Traffic-heavy APIs
Scale HTTP and gRPC services from live request pressure.
Who’s it for?
Cloud bills keep climbing when teams overprovision compute, hand-tune YAML, and fight cold-start incidents. Engineering time gets lost, finance needs clear ROI, and customers feel every latency spike.
Industries That Feel the
Pain First
FinTech / Finance
Trigger: Transaction spikes, strict SLAs
Kedify: Aligns infra cost with unpredictable peaks
Ecommerce & Retail
Trigger: Flash sales, seasonal peaks
Kedify: Scale to zero between campaigns
Travel & Hospitality
Trigger: Search surges, fare crawls
Kedify: Keeps latency low without idle clusters
Utilities
& IoT
Trigger: Sensor bursts, meter reads
Kedify: Handles queue-based workloads reliably
Media & Streaming
Trigger: Event traffic, live sports
Kedify: Burst-friendly scaling with no cold starts
Data heavy, AI heavy, traffic heavy
Workloads Kedify Fits Best
For workloads where demand, latency, or spend moves fast.
2
AI demand
AI and GPU inference
Keep inference capacity ready without leaving GPUs idle.
3
Scheduled work
Batch and ETL jobs
Run workers for queue depth or scheduled windows.
4
Backlog control
Streaming data pipelines
Add consumers from lag before backlogs become incidents.
5
Spend evidence
FinOps and right-sizing
Find oversized CPU and memory requests and show saved capacity.
6
Ephemeral compute
CI/CD test farms
Scale runners and preview environments to zero between builds.
How we fix it
Demand, resources, and cost in one loop
Managed KEDA autoscaling, right-sizing, and FinOps evidence for your clusters.
1
Inputs
Observe signals
Requests, queues, OTel, GPU demand, pod pressure, and history.
2
Insights
Recommend fit
CPU and memory recommendations before scaling acts.
3
Actions
Scale workloads
APIs, queues, jobs, inference, and pod resources.
4
Fleet
Coordinate clusters
Weights, failover, tenants, and guardrails.
5
FinOps
Prove savings
Saved pod-hours, node-hours, CPU, memory, and GPU.
Customer outcomes
Real-World Proof
The same autoscaling, right-sizing, and cost visibility capabilities are already reducing operational work and infrastructure waste in production Kubernetes estates.
200x
traffic burst handled
“Before Kedify, scaling up was a constant challenge. Now, our platform adapts instantly to our users’ needs, and we’ve freed up our team to focus on new features rather than managing resource spikes.”
- Rafael Tovar, Cloud Operations Leader, Tao Testing
With Kedify, Tao Testing handled a 200× traffic burst with zero downtime and ~40% lower spend.
150-200
preview environments
“With Kedify, our developers get the best of both worlds, cost-efficient scaling like Google Cloud Run, but fully integrated within our Kubernetes-based platform.”
- Jakub Sacha, SRE, Trivago
Trivago migrated 150–200 preview environments from Cloud Run to Kubernetes while keeping scale to zero efficiency.
Who Already Uses The Technology
KEDA powers autoscaling for companies you know including Microsoft, FedEx, Grab,
Qonto, Alibaba Cloud, Red Hat and many more. Kedify gives these capabilities turnkey
to enterprises that don’t want to build and maintain it themselves.
Who Signs the PO (Buyers)
CFO / FinOps
Owns cloud spend, payback, and proof that saved capacity reaches the budget.
CTO / VP Engineering
Needs reliability and delivery speed without adding platform headcount.
CEO / Founder
Balances innovation speed with cost control and brand risk.
Who Benefits Day-to-Day
Platform & DevOps teams
Ditch homegrown scripts and pager fatigue.
SREs
Fewer scaling incidents, clearer SLOs.
Developers
Preview environments on demand, zero wait time.
FinOps & finance
Saved pod-hours, node-hours, CPU, memory and GPU capacity turned into spend evidence.
Is Kedify For You?
If you’re running Kubernetes, spending >$1M/year on cloud, and your
workloads spike, batch, stream, or need right-sizing, you’re in the sweet spot. Book
a 15-minute
fit check and see how fast autoscaling can pay for itself.