Trust Line: 🛡️ SOC 2 Type II Audited | 🌏 APAC & EMEA Delivery: AU, UAE, India

The platform challenge

Growth adds complexity. Your platform needs to keep up.

As products grow, infrastructure complexity grows with them. Deployments become harder to manage, failures become more expensive, and engineering teams spend more time keeping systems running instead of improving them.

ISSUE_01

Unreliable Releases

Manual processes and varied environments contribute to slow and risky deployments.

ISSUE_02

Scaling Under Pressure

Increased traffic highlights inefficiencies within the infrastructure, database, network, and application design.

ISSUE_03

Limited Production Visibility

Lack of observability means issues are found by customers before the team is aware.

ISSUE_04

Operational Complexity

Managing infrastructure, CI/CD pipelines, security, and cloud resources becomes more challenging.

Our engineering approach

Engineering platforms for scale, resilience and reliability.

We combine platform architecture, automation and security engineering to build infrastructure that can support growing workloads while remaining reliable, maintainable and easier to operate.

Platform-First Architecture

Architect for high concurrency, elastic scalability, and resiliency right from the ground up.

Automated DevOps Workflows

Automation of CI/CD, infrastructure management, and operations to make your delivery process more consistent and reliable.

Security-First Engineering

Incorporation of SOC 2 Type II-aligned practices in your cloud platforms and delivery pipelines.

The Outcome

Well-engineered, high-performing platforms that are designed to scale and deliver reliably.

What We're Offering

Platform Engineering Capabilities

We specialize in the complex technical ecosystems that power today's enterprises and high-growth scale-ups.

01

Platform Architecture

Designing robust application and infrastructure architectures for scale, reliability and maintainability.

02

Cloud Infrastructure

Design & optimise AWS/Azure cloud environments for performance, availability and operational efficiency.

03

Infrastructure as Code

Repeatable, version controlled, and easier to manage infrastructure using Terraform/CloudFormation.

04

CI/CD & Release Engineering

Automated build, test and deployment pipelines that make releases safer and more predictable.

05

Observability & Monitoring

Metrics, logs, monitoring and alerting for teams to provide visibility into system health and performance

06

Reliability & Performance Engineering

Availability, resilience, database performance, concurrency and system behavior under load.

Platform Architecture

Applications & Microservices

Product architecture designed for scale, reliability and maintainability

CI/CD & Release Engineering

Automated build, test and deployment pipelines

Infrastructure as Code

Terraform / CloudFormation-managed, version-controlled infrastructure

Cloud Infrastructure

AWS / Azure environments engineered for performance and availability

Platform engineering vs. DevOps

Beyond pipelines. We engineer the platform behind them.

DevOps and Platform Engineering are related, but they answer different questions - and most teams need both.

DevOps Platform Engineering
Primary Focus Automates delivery and operations Builds the reusable engineering foundation those operations run on
Scope CI/CD pipelines, deployment workflows and day-to-day operations Architecture, cloud infrastructure, automation and reliability, engineered as a system
What It Improves Deployment speed and consistency Scalability, reliability and developer experience across the organisation
Orientation Tool and process-driven Architecture-driven, with automation and operations built on top
Outcome For The Team Helps teams operate software Helps teams build and operate software consistently, at scale

Zediant integrates all aspects of platform architecture, cloud, automation, observability, and reliability engineering to provide a base upon which your engineering team can build, and it is more than just a faster pipeline.

Operational efficiency

Reduce operational friction through automation.

Manual processes slow teams down and introduce risk. We automate all the infrastructure, deployment, and monitoring work that would otherwise eat up engineering hours - so your team can focus on the product, not keeping the lights on.

Diagram showing infrastructure automation, deployment automation, observability and alerting, and automated scaling connected in a continuous cycle
01

Infrastructure Automation

Standardisation of environment and infrastructure change using code to minimize configuration drift.

02

Deployment Automation

Minimize manual actions in releasing and making the deployment process consistent and independent from a specific individual.

03

Observability & Alerting

Provide earlier insight for engineering teams about potential problems regarding the performance and reliability of systems.

04

Automated Scaling

Adjust the infrastructure capacity to cope with different workloads and traffic pattern dynamically.

The Outcome

Faster, more consistent deployments with fewer manual errors and less operational overhead.

How We Work

From Platform Assessment to Production Reliability

Platform Engineering is not something you just do once, but how your platform scales with your product. Our process takes you from an assessment of your current environment to a platform designed to evolve along with it.

01

Assess

Architecture, infrastructure and reliability review

02

Architect

Target architecture and automation strategy

03

Implement

Platform, CI/CD and observability build-out

04

Optimise

Performance, reliability and continuous evolution

↻ Continuous Platform Evolution
01

Assess

First, we gain an understanding of your existing architecture, infrastructure, release process, reliability concerns, and operational constraints so that the recommended approach always considers your systems in their current form.

02

Architect

Next, we specify the desired target platform architecture, infrastructure patterns, automation approach, and reliability constraints - defining the roadmap for the journey to get there.

03

Implement

Third, we implement the new platform (including the required infrastructure, CI/CD pipelines and observability), implementing changes incrementally in order to give your team visibility and keep delivery going.

04

Optimise

We measure behavior of your systems, optimise their performance and reliability, and continuously evolve the platform based on your evolving requirements - in a cycle that leads to the next round of assessment.

There's no endpoint to platform engineering: each new cycle of assessment and optimisation will ensure that your infrastructure remains aligned with the future direction of your product.

What you get

What better platform engineering delivers

Our reliability, scalability, and confidence in our releases comes from our architecture and operations, not a process or tool. The platform engineering practice we follow is intended to deliver:

High Availability

Reliability

Ensure availability and reduce consequences of infrastructure and application failures.

Scalability

Scalability

Enable scalability without having to continuously modify the core platform.

Faster Deployments

Release Assurance

Improve repeatability, visibility, and recoverability at the time of release.

Resilience & Fault Tolerance

Operational Resilience

Failures should be detected, isolated, and recovered to prevent business impact.

Platform readiness

Is your platform ready to scale?

Whether you are planning for rapid expansion, infrastructure updates, or increased complexities in your operations, we can help pinpoint where your system will need to adapt.

Platform engineering in practice

Engineering platforms built for real-world scale.

From high concurrency systems to multi environment systems, observe the architecture and infrastructure that we have designed to run such stringent production environments.

High-Concurrency Cloud Platform Engineering

11Wickets: Cloud Autoscaling & High-Availability Architecture

A high-traffic fantasy sports platform faced severe latency and database bottlenecks during live cricket tournaments. Zediant re-architected their AWS infrastructure with dynamic autoscaling and multi-master MySQL Galera clustering, delivering sub-second response times under peak load while cutting off-peak cloud costs by up to 40%.

Key Results

99.99% Peak event uptime
30% to 40% Cloud cost savings

Services:

Cloud Architecture, Autoscaling Groups, MySQL Galera Clustering, DevOps & Infrastructure as Code

Read 11Wickets Platform Case Study
Enterprise Integration Middleware Platform

Multi-DMS Middleware Integration for Automotive Dealer Networks

Automotive dealer networks struggled with disconnected, on-premise dealer management systems that delayed inventory, customer, and sales synchronisation. Zediant engineered an asynchronous middleware integration engine using Java Spring and message queues to bridge CDK, ERA, and Pentana systems with cloud platforms.

Key Results

60% to 70% Manual re-entry cut
40% to 50% Faster record sync

Services:

Middleware Platform Engineering, Asynchronous Message Queuing (JMS/ActiveMQ), Adapter Architecture, REST API Gateway

Read DMS Middleware Case Study
View all case studies

Security & governance

Security and governance built into the platform

Security is not another process and is not an analysis that happens after the implementation; on the contrary, security turns into a natural part of the development of the platform itself. The Zediant platform adheres to the security standards which are SOC 2 Type II certified for infrastructure, deployment pipeline, and access management.

Secure Infrastructure

Security measures that are built into the infrastructure design and environment from the start, not as an add-on.

Secure Delivery Pipelines

Security measures that are integrated into the delivery process, ensuring any risks are identified prior to the deployment.

Identity & Access

Access control that is applied through proper authentication and authorization measures.

Data Protection

Controls that are implemented to provide protection for sensitive data.