Service-level & integration testing
Per-service suites plus cross-service flows with contract validation at every seam, so a deploy to one service can't silently break three others.
Quality Engineering
Distributed systems fail in distributed ways
The postmortem said one slow dependency took three services down, and no feature test could have seen it coming. Microservices, containers, and managed queues fail partially, intermittently, and at the seams. Testing them means testing the architecture (timeouts, retries, scaling, configuration) as deliberately as the features.
Engineering-led cybersecurity and quality engineering since 2020, delivered by 100+security & quality engineers on platforms we build and run ourselves.
The failure modes that take cloud systems down (cascading timeouts, retry storms, mis-scoped IAM, autoscaling lag) are invisible to feature tests. They surface in production, at load, usually during your worst possible week.
What we do
Resilience validation
Timeout, retry, circuit-breaker, and degradation behavior tested by injecting the failures your architecture claims to survive.
Scaling & configuration testing
Autoscaling behavior, cold-start costs, resource limits, and environment-config drift, verified, not assumed.
Data & messaging integrity
Event ordering, idempotency, exactly-once assumptions, and dead-letter handling across queues and streams, so a replayed event can't quietly corrupt an order or a balance.
How it’s delivered
01
Map
Architecture review: services, seams, and failure assumptions.
02
Prioritize
Rank seams and failure modes by blast radius.
03
Test
Automated suites plus targeted failure-injection sessions.
04
Harden
Retest after fixes; leave the suites running in your CI.
Tools & standards
- Platforms
- AWS, Azure, GCP, Oracle Cloud; Kubernetes and container runtimes
- Frameworks
- k6, Playwright, REST Assured, contract testing at service seams
What you receive
- Seam-mapped test architecture for your service topology
- Automated cross-service regression in CI
- Resilience findings with reproduction and blast-radius analysis
- Scaling and configuration validation report
Evidence
Judge the discipline before you engage
Engagements end in evidence: what was tested, what failed, what was fixed, and what proves it. Our methodology, from scoping to handover, is published for review.
How we deliver →Engagement
Ways to engage the same senior bench
Buy it as a scoped project, embed it in your team, or run it as a managed service. The engineers and the governance stay the same, whichever shape fits.
Scoped project
A defined piece of work with a fixed outcome (a test suite built, a release hardened, a backlog cleared), delivered by our team and handed over with documentation.
Embedded QE
Our engineers work inside your sprint teams, on your tools and cadence, owning quality alongside your developers rather than testing from the outside.
Managed QE service
We own the discipline as an ongoing service (coverage, execution, and reporting), scaling the bench up or down as your release pressure moves.
Who this is for
- Teams mid-migration from monolith to services, finding integration bugs weekly
- Platform engineering groups who own reliability but not the feature teams' test suites
- Products on Kubernetes whose failure testing is 'we have replicas'
Common questions
What's different about testing microservices?
They fail partially and at the seams: cascading timeouts, retry storms, autoscaling lag. We test the architecture (resilience, scaling, configuration) by injecting the failures it claims to survive.
Do you cover Kubernetes and container configuration?
Yes. Orchestration and container configuration are part of the surface: resource limits, health checks, autoscaling behavior, and the failure modes that only appear under real load and partial outage.
Who actually does the work?
Senior engineers from our own team, and the ones who scope your engagement stay on it through delivery. Across the practice, 63% of our engineers hold industry certifications, spanning ISTQB, AWS, CISSP, CEH, and eCPPT.
In the assurance loop
Distributed systems fail in ways single-service tests miss. Findings from those failure modes, security ones included, become standing checks in the pipeline. See how the loop connects →
Test the architecture before it tests you
Describe your service topology and the failures that worry you most. A QE lead ranks the seams by blast radius and shapes the suites to cover them.