Senior Platform / Solution Architect

Role Purpose

• The Senior Platform/Solution Architect – Capacity Planning, Performance & Cloud Infrastructure Architecture is responsible for translating business demand, application traffic and workload characteristics into quantifiable infrastructure requirements across microservices, Kubernetes/OpenShift, cloud and on-premises environments.
• The role provides the technical capability to determine CPU, memory, pod/replica, node, cluster, database, storage and network requirements while ensuring performance, scalability, resilience, availability and cost efficiency.

Core Responsibilities

• Lead capacity planning and infrastructure dimensioning for applications, platforms and microservices-based services.
• Translate business growth, transaction volumes and traffic forecasts into infrastructure capacity requirements.
• Develop quantitative workload models covering normal, peak, burst and exceptional traffic conditions.
• Determine appropriate CPU, memory, pod/replica, node and cluster requirements for application services.
• Develop capacity forecasts and infrastructure roadmaps covering short-, medium- and long-term demand.
• Ensure capacity plans support availability, resilience, disaster recovery and business continuity requirements.
• Provide architecture and capacity recommendations for both cloud and on-premises environments.
• Review existing environments to identify over-provisioning, under-provisioning, bottlenecks and capacity risks.

Microservices Capacity Planning & Dimensioning:

• Assess resource consumption and performance characteristics of individual microservices.
• Determine minimum, normal and maximum pod/replica requirements based on workload and service-level objectives.
• Define CPU and memory requests and limits for containers.
• Assess horizontal and vertical scaling requirements and define appropriate scaling policies.
• Determine node density, resource utilisation and cluster capacity requirements.
• Account for service-to-service communication, platform overhead and infrastructure reserve capacity.
• Establish repeatable sizing methodologies for new applications and services.
• Validate sizing assumptions through performance and capacity testing.

Capacity Planning Parameters & Metrics:

• Define and maintain standard parameters for application and infrastructure capacity planning.
• Analyse requests per second (RPS), transactions per second (TPS), concurrent users, sessions and transaction volumes.
• Analyse average, peak and burst traffic and associated growth patterns.
• Assess CPU utilisation, CPU consumption per transaction, memory utilisation, memory peaks and application heap requirements.
• Assess pod counts, replica requirements, scaling thresholds and scaling response times.
• Determine node CPU, node memory and allocatable cluster capacity.
• Assess database TPS, connections, CPU, memory, IOPS and throughput.
• Assess storage capacity, IOPS, throughput and growth.
• Assess network bandwidth, latency and packet rates.
• Factor in high availability, N+1/N+2 resilience, disaster recovery, growth headroom and operational reserve.

Performance Engineering:

• Lead performance engineering and capacity validation for critical applications and platforms.
• Define and oversee load, stress, endurance, spike, scalability and capacity testing.
• Analyse throughput, response time, latency, concurrency and resource utilisation.
• Identify application, platform, database, storage and network bottlenecks.
• Establish performance baselines and capacity thresholds.
• Use performance test results to validate CPU, memory, pod, node and cluster sizing.
• Work with engineering teams to optimise resource consumption and application performance.

Observability & Data-Driven Capacity Planning:

• Use production telemetry and historical data to drive capacity decisions and improvements.
• Implement dashboards and reports to monitor resource utilisation, performance and capacity trends.
• Collaborate with SRE/Platform teams to ensure observability and proactive capacity management.

Required Qualifications (as implied by responsibilities):

• Strong experience in capacity planning, performance engineering, and cloud/on-premises infrastructure design.
• Experience with microservices architectures, Kubernetes/OpenShift, and hybrid cloud environments.
• Ability to translate business demand into actionable infrastructure requirements.
• Familiarity with workload modelling, SLOs/SLIs, and scaling policies.
• Knowledge of telemetry, monitoring, and observability practices.

Industry

• Software / Technology