We help teams improve production reliability through measurable service objectives, incident response processes, capacity planning and practical operational automation.
Reliable systems are the result of deliberate practice, not chance. Site Reliability Engineering applies engineering rigor — measurement, targets, trade-off analysis — to what is often treated as purely reactive operational firefighting.
We help teams define meaningful Service Level Indicators and Objectives, understand the error budget those objectives create, build observability around them, and put practical incident response and capacity planning processes in place.
Nobody has agreed what "reliable enough" actually means for this system.
Incidents are handled ad hoc, with no clear ownership or escalation path.
Every sprint, reliability work loses out to new features with no data to inform the trade-off.
A DR plan exists on paper but has never actually been rehearsed.
Define meaningful reliability indicators, objectives and the error budget they create.
Monitor important service and infrastructure signals against defined targets.
Create practical processes for detecting, responding to and learning from incidents.
Understand infrastructure capacity and future workload requirements.
Improve failure-handling patterns and recovery planning, tested rather than assumed.
Automate repetitive operational work to reduce toil and human error.
Review current reliability posture.
Define SLIs, SLOs and error budgets.
Address gaps in resilience.
Test failure handling and recovery.
Run with practical incident processes.
Review current reliability posture.
Define SLIs, SLOs and error budgets.
Address gaps in resilience.
Test failure handling and recovery.
Run with practical incident processes.
Defined SLIs and SLOs guide priorities.
Practical processes for detecting and responding to issues.
Planning based on real workload growth.
Disaster recovery planning kept current and tested.
We bring metrics, logs and traces together — using Prometheus, Grafana, AWS CloudWatch and the ELK Stack — to help engineering teams understand system behavior, identify issues and respond with real operational context.
We assess and strengthen cloud security posture — identity and access management, network security, secrets management and audit visibility — across AWS, Microsoft Azure and Google Cloud environments.
We help teams maintain cloud infrastructure through monitoring, maintenance, operational support, backup oversight, security practices and continuous improvement.
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An SLI (Service Level Indicator) is a specific measured metric, like the percentage of requests served under 300ms. An SLO (Objective) is your internal target for that indicator, like 99.9% over 30 days. An SLA (Agreement) is a customer-facing commitment, often with consequences if missed. We help define SLIs and SLOs first — SLAs are a business decision built on top of those.
Tell us what you're building, where you're facing infrastructure challenges, and what you want to improve.
