Run · Service
Performance and reliability
that make production faster, more resilient and easier to trust.
We identify and improve the bottlenecks, failure modes and operational weaknesses that affect real users — strengthening application performance, resilience, capacity and recovery around the service levels the business actually needs.
When production starts to feel unreliable
Reliability problems often exist before anything is technically “down”.
A system can remain available while becoming slower, less predictable or increasingly difficult to recover. Reliability work begins when user experience, operational effort or business confidence starts depending on how the system behaves under load, failure and change.
- 01Performance degrades as usage growsResponse times, throughput or background processing begin to suffer when demand increases.
- 02The same failures keep returningIncidents are resolved, but the underlying weaknesses remain and reappear under similar conditions.
- 03Dependencies make the system fragileDatabases, APIs, queues, infrastructure or third-party services can cause wider degradation when they slow down or fail.
- 04Recovery takes too long or depends on specialist knowledgeThe system can be restored, but diagnosis and recovery are slower or less predictable than the business can comfortably tolerate.
The reliability decisions
Before optimising the system, decide what “reliable enough” actually means.
- 01Which user journeys matter most?What interactions, transactions or operational workflows should remain fast and available even under stress?
- 02What service levels does the business need?Which availability, latency, throughput or recovery expectations are important enough to make explicit?
- 03Where can failure propagate?Which dependencies or shared components can turn a local problem into a wider service issue?
- 04What should happen under load?How should the system scale, degrade or prioritise work when demand exceeds normal conditions?
- 05How should failure be contained?Where are timeouts, retries, queues, isolation, fallback or circuit-breaking behaviours needed?
- 06How quickly should service recover?What recovery objectives and operational paths should exist when something does fail?
What Performance & Reliability can include
Reliability engineering improves how the system behaves when conditions stop being ideal.
- 01Performance engineeringAnalyse and improve application response time, throughput, resource use and processing efficiency.
- 02Load & capacity engineeringUnderstand system limits and establish how infrastructure and applications should behave as demand changes.
- 03Reliability engineeringIdentify recurring failure modes and strengthen the system’s ability to continue or recover safely.
- 04Resilience patternsIntroduce appropriate redundancy, timeout, retry, fallback, queueing and isolation strategies.
- 05SLOs & service healthDefine measurable expectations around availability, latency, errors and other service outcomes.
- 06Recovery & failure testingValidate behaviour under infrastructure loss, dependency failure, degraded services and other realistic scenarios.
Related reliability & operations areas
Reliability work depends on good production evidence, suitable infrastructure and safe delivery practices.
Engagement scope
What we actually do.
- 01Performance & reliability assessmentReview architecture, telemetry, incidents, workload behaviour and known bottlenecks to identify the most important risks.
- 02Bottleneck & dependency analysisTrace latency, contention, resource pressure and dependency behaviour across application, data and infrastructure layers.
- 03Capacity & scalability engineeringModel and test demand patterns, concurrency and resource requirements to understand when and how the system needs to scale.
- 04Resilience & failure-mode designImprove timeouts, retries, isolation, fallback, redundancy and recovery behaviour around realistic failure scenarios.
- 05SLO & reliability frameworkDefine service-level objectives, indicators and operational thresholds around the outcomes that matter most.
- 06Reliability validation & improvementTest the system under realistic load and failure conditions, verify the effect of changes and use production evidence to guide the next reliability priorities.
Engagement options
Ways we can improve reliability with you.
Not sure which starting point fits? We will help you choose.
- Performance assessment & optimisationInvestigate a defined performance problem and improve the most important application or infrastructure bottlenecks.Useful whenUsers are experiencing slowness, timeouts or inconsistent performance but the cause is not yet clear.
- Reliability improvement programmeAddress recurring incidents, weak dependencies, recovery paths and service-level expectations across a business-critical system.Useful whenThe system works, but production behaviour is not dependable enough for the business.
- Embedded reliability engineeringWork alongside application, platform and operations teams to continuously improve performance, capacity and resilience.Useful whenReliability needs sustained engineering attention rather than a one-time intervention.
What you leave with
A system that behaves more predictably when load, change and failure put it under pressure.
The exact outputs depend on the system, but the engagement should leave teams with clearer service expectations, fewer known failure paths and stronger evidence that production can meet real operating demands.
- 01A reliability baselineClear understanding of current performance, availability, failure modes and operating constraints.
- 02Prioritised bottlenecksThe performance and resilience issues that materially affect users or operational risk identified and ranked.
- 03Defined service objectivesExplicit availability, latency, error or recovery expectations for the services that matter most.
- 04Stronger failure behaviourResilience patterns and recovery paths designed to contain or reduce the impact of common failures.
- 05Validated capacityEvidence of how the system behaves under expected, peak and elevated demand — and where the practical limits currently sit.
- 06A reliability improvement roadmapA practical sequence of engineering changes based on impact, risk and production evidence.
Our approach
Strengthen the failure path — not just the happy path.
- 01Start with real service behaviourUse incidents, telemetry, user impact and workload patterns to understand where reliability is actually being lost.
- 02Find the constraining componentTrace performance and failure across application, data, infrastructure and external dependencies.
- 03Improve the architecture deliberatelyAddress bottlenecks, resilience gaps and recovery behaviour without adding unnecessary complexity.
- 04Test under realistic conditionsValidate load, failure and recovery using scenarios that reflect how the system is actually used.
- 05Measure and improve continuouslyUse service-level evidence and production behaviour to keep reliability work focused on what matters most.
From production visibility to dependable operation
Seeing the failure is a milestone. The system still has to become less likely to fail the same way again.
Performance & Reliability can move directly into the capabilities required to improve production behaviour, release safety and ongoing technical ownership.
FAQ
Common questions about Performance & Reliability.
Performance engineering is the analysis and improvement of how efficiently a system responds, processes work and uses resources under realistic operating conditions.
Reliability engineering focuses on how consistently a system delivers the expected service and how well it contains and recovers from failures.
Monitoring & Observability helps teams see and understand production behaviour. Performance & Reliability uses that evidence to improve bottlenecks, resilience, capacity and recovery.
Yes. We can analyse application code, databases, infrastructure, network behaviour and external dependencies to identify where latency or resource contention is occurring.
Yes. Testing can be designed around expected concurrency, transaction volume, background workloads and other realistic demand patterns.
Yes. We can help define service-level objectives and indicators around availability, latency, errors or other service outcomes important to users and the business.
Yes. We can assess and improve redundancy, dependency handling, recovery and resilience where the business impact justifies it.
Yes. Database behaviour can form an important part of performance work, including query behaviour, contention, indexing, connection use and architecture.
Yes. We can design timeouts, retries, queues, fallbacks and isolation patterns that reduce the effect of unreliable external dependencies.
Yes. Where appropriate, we can validate behaviour under dependency loss, degraded infrastructure, resource pressure and other controlled failure scenarios.
Yes. We can use workload evidence and performance testing to understand current limits and define more appropriate scaling behaviour.
Yes. Reliability improvement can continue through Managed Application Services, observability, cloud operations and embedded engineering arrangements.
