Platform reliability is not a state you reach, it is an ongoing operational practice. Gigamatics delivers SRE-principled managed operations across your platform stack: proactive performance monitoring, SLO governance, capacity planning, incident coordination, and observability engineering — so your engineering teams ship product, not incidents.
Nine structured operational pillars, each documented, governed, and calibrated to your platform architecture, SLO targets, and engineering team's working model.
Continuous monitoring of latency, throughput, error rates, and saturation, with alerting designed to detect degradation before users do.
Define, instrument, and continuously track SLOs with error budget accounting that gives clear, data-driven signals to engineering teams.
Forward-looking capacity analysis translating growth projections into infrastructure provisioning recommendations.
Structured incident response with a named senior SRE who coordinates containment, communication, and resolution.
Structured diagnostic analysis identifying performance bottlenecks and architectural inefficiencies.
Design and ongoing governance of auto-scaling policies, ensuring scaling behaviour is predictable and cost-efficient.
Continuous analysis identifying architectural changes and process improvements that reduce operational risk.
Structured review ensuring metrics, logs, and traces actually inform reliability decisions.
Continuous maintenance of operational runbooks and incident playbooks, current and tested.
AI-driven anomaly detection helps our SRE team catch performance degradation earlier than static thresholds alone, with AI-assisted incident documentation speeding up post-incident review.
See how AI supports our delivery →Most organisations treat reliability as a reactive discipline, scrambling when things break. Gigamatics applies SRE principles to managed operations: structured measurement, proactive intervention, and continuous improvement as an ongoing practice.
We move your reliability conversation from vague "five-nines" aspirations to precisely defined, measured Service Level Objectives.
Error budget management gives engineering leadership a quantitative framework for balancing reliability against feature velocity.
Capacity forecasting and operational improvement recommendations shift the team's orientation toward preventing incidents.
We engineer and operate observability stacks that give your team genuine signal, not a wall of dashboards and an alert queue nobody trusts.
Prometheus, Datadog, New Relic, Dynatrace, CloudWatch, configured and continuously optimised.
ELK Stack, Loki, Splunk, Datadog Logs, structured log pipeline design and alerting integration.
kube-state-metrics, cAdvisor, OpenTelemetry, full visibility across EKS, AKS, and GKE.
Jaeger, Tempo, Datadog APM, AWS X-Ray, cross-service dependency visibility.
Grafana, Kibana, Datadog dashboards, maintained SLO dashboards and executive scorecards.
PagerDuty, OpsGenie, Alertmanager, escalation policy design and alert fatigue reduction.
Every reliability operation runs on a defined, documented schedule. Nothing is left to ad-hoc discretion, every activity has an owner, a cadence, and a documented output.
| Activity | Description | Cadence |
|---|---|---|
| Platform Performance Monitoring | Continuous collection and analysis of platform metrics, availability, latency, throughput, error rate, and resource saturation, with immediate alerting on threshold breach or anomaly detection. | Continuous |
| SLO Compliance Tracking | Real-time SLO attainment measurement against defined targets, with error budget burn rate monitoring and proactive alerting when burn rate indicates breach risk. | Continuous |
| Auto-Scaling Policy Monitoring | Continuous oversight of scaling behaviour across compute and Kubernetes workloads, confirming that scaling events trigger correctly and complete successfully. | Continuous |
| Incident Detection & Response | Alert triage, severity classification, and coordinated response, P1 incidents acknowledged within 15 minutes, with named SRE ownership through to closure. | Continuous |
| Performance Trend Analysis | Weekly structured review of performance metric trends, identifying gradual degradation and emerging bottlenecks that do not yet trigger alerts. | Weekly |
| Alert Threshold Review | Review and recalibration of alert thresholds based on recent incident data and traffic pattern changes, maintaining signal quality as the platform evolves. | Weekly |
| Post-Incident Review (RCA) | Blameless root cause analysis for every P1 or P2 incident, documenting cause, timeline, contributing factors, and preventive recommendations. | Post-Incident |
| Observability Stack Review | Monthly review of observability coverage, dashboard utility, metric cardinality, and trace sampling rates, with optimisation recommendations. | Monthly |
| Operational Improvement Report | Monthly register of identified reliability improvement opportunities, covering architecture gaps, toil candidates, and scaling policy refinements. | Monthly |
| Monthly SRE Performance Report | Structured report covering SLO attainment, error budget consumption, incident summary, capacity status, and improvement actions. | Monthly |
| Capacity Planning Review | Quarterly capacity analysis reviewing utilisation trends against growth projections, headroom adequacy, and scaling policy calibration. | Quarterly |
| Runbook & Knowledge Base Review | Quarterly review and validation of all operational runbooks and platform documentation, confirming accuracy against current platform state. | Quarterly |
Most managed monitoring services forward alerts and wait for your team to respond. Gigamatics applies real SRE principles to keep your platform reliable and your engineering team focused on product.
Engineers who have designed distributed systems and built SLO frameworks at scale.
A shared, quantitative framework for reliability investment decisions.
Monthly operational improvement recommendations mean your reliability posture improves continuously.
Knowledge transfer and documentation are built into the service, not left as dependency.
Many clients engage Gigamatics to augment existing SRE capability, providing additional coverage, specialist Kubernetes expertise, or dedicated observability engineering with clearly defined responsibilities.
Yes, this is a common starting point. SLO definition and instrumentation workshops are a standard part of onboarding, developed collaboratively with your engineering and product teams.
Yes. We integrate with your existing stack, whether Datadog, Prometheus and Grafana, New Relic, or Dynatrace, optimising configuration rather than replacing tools unnecessarily.
Incident coordination covers detection, triage, containment, and communication. For platform-layer incidents, our SRE team leads from detection to resolution; for application-level fixes, we coordinate while your team implements.
Yes. Kubernetes management is core to the service, covering cluster health, HPA/VPA tuning, and control plane health across EKS, AKS, GKE, and self-managed clusters.
Whether your team is spending too much time on incidents or you need experienced SRE capacity — let's have an honest conversation.
A structured conversation covering your current platform, incident history, and operational gaps — with no commitment required.
For qualifying engagements, we provide a documented assessment of your platform reliability posture and recommended managed service scope.
You speak with the practitioner who would manage your environment — not a pre-sales representative. Every conversation is technically informed.