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Případové Studie

Match Worn Shirt

Match Worn Shirt | DevOpsGroup“Dáváme fanouškům po celém světě šanci vlastnit kus historie a zároveň získávat finanční prostředky pro charitu.”

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IEE Sensing

“IEE Sensing je ve světě dobře známá značka se značnými zkušenostmi jako dodavatel automobilových systémů a výrobce komponentů.”

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ParkDots

Inovační parkovací systém. Parkování ve vašem městě? ParkDots je ta apka. A tečka.

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T-Mobile CZ

T-Mobile CZ potřeboval zajistit bezpečnou, škálovatelnou a spolehlivou infrastrukturu pro platební systém”

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3D Hex Medium | DevOpsGroup
Match Worn Shirt | DevOpsGroup

“Giving fans around the world the chance to own a piece of history whilst raising funds for the charity.”

At a Glance

Challanges
  • Multiple GEO locations
  • GEO synchronised DB
  • Traffic Spikes
  • Scalable to new locations
  • All in 2 months
Benefits
  • Direct Cost : 19 900€
  • Scalable to new regions by variables

Objectives

As auction portal for mainly football shirts they were facing problem with latencies for multiple world locations and load spikes after football match ends and auction starts.

MWS needed scalable infrastructure in Terraform code for AWS which will be easy to use and understand with synchronised database per GEO locations with only one DNS name and possibility to scale to new locations without changing IaaC code.

Solution

DevOpsGroup did their best and provided scalable Iaac infrastructure which is driven by parameters and can by scaled up or down.

For Database was used Dynamo Global Tables with synchronisation.

For cost saving purposes, there was used local copy of OpenSearch in each region with Lambda sync script from Dynamo DB. Spikes were solved by Lambda serverless for affected components .

Other resources were in EKS (Kubernetes). MatchWornShirt runs their entire production on solution provided by DevopsGroup.

Kubernetes logo | DevOpsGroup
AWS logo | DevOpsGroup
Terraform logo | DevOpsGroup

Kevin Rombout

HEAD OF TECHNOLOGY

“DevOpsGroup gave us infrastructure as
code (IaC) solution that is easy to read, to
extend and to deploy by making use of
building blocks provided and supported by
AWS, Terraform and Github. Given the
complex requirements and customisations,
two months were really challenging.
Excellent work and excellent results.“

3D Hex Medium | DevOpsGroup
iee-sensing-logo
“We build Intelligent Sensing
Solutions for everyday life”

IEE Sensing is a well known brand in the world with considerable experience as an automotive system supplier and component manufacturer .

At a Glance

Challanges
  • Multiple GEO locations
  • machines with Windows operating system
  • Technical debt
Benefits
  • Fast integration and migration
  • Increased Availability
  • Reduced cost of operations

Objectives

IEE Company manufactures smart sensors in
production halls where downtimes are expensive,
production must run smoothly, with communication
between individual machines and components
without any interruptions.

When the company approached us, they expressed
interest in a Docker Swarm on-prem solution. However,
we proposed a more suitable option, the RKE2 Rancher
Kubernetes on-prem solution.

It allowed the company to manage their containerized
applications seamlessly and provided highavailability
and scalability to their infrastructure.

Solution

The DevOpsGroup has successfully provided a robust
infrastructure to their client, which is running on the
Kubernetes RKE2 Rancher on-prem solution with HAproxy
and Keepalived load balancing. DevOpsGroup set up an
entire infrastructure that includes a registry, GitLab,
SonarQube.


The automation with Ansible and CI/CD pipelines have
been put in place to ensure smooth operations.
As a result, the entire production of IEE is now running on
DevOpsGroup Kubernetes solution across multiple
countries such as China, Mexico, Slovakia and
Luxembourg.

Juraj Veverka
Solution Design Architect
“Lukas and his colleagues from DevOpsGroup has significantly helped with modernization of IEE Sensing on premise deployments. He and his team not only accelerated transition from bare-bone VMs to self managed k8s clusters, but also contributed with best practice ideas in DevOps area. One tear into infrastructure automation, and we can already see increased reliability, traceability and better deployment quality with new possibilities for integration testing.“
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