Run production systems that are resilient, observable, and scalable. Establish operational excellence through comprehensive observability, structured incident response, and automation that eliminates toil.
Production is where your infrastructure proves its worth. Systems that seemed solid in development reveal their weaknesses under real load, real users, and real failures. Operational excellence isn't about preventing all failures—it's about detecting them fast, responding effectively, learning continuously, and building systems that gracefully handle the unexpected.
The best operations are invisible. Users experience reliability. Engineers sleep through the night. When incidents occur, teams respond with confidence, not panic. Our approach establishes the observability, processes, and automation that make this possible.
Six foundational principles that guide how we run cloud infrastructure that performs reliably at any scale.
Instrument systems comprehensively so that understanding state never requires heroics. Make the invisible visible.
Use Service Level Objectives to make principled tradeoffs between reliability and velocity. Stop chasing arbitrary nines.
Treat incidents as opportunities to strengthen systems and teams. Respond with structure, communicate with clarity, learn without blame.
Design systems that handle failure gracefully. Prove resilience through controlled experimentation, not production surprises.
Architect systems that grow smoothly with demand. Eliminate bottlenecks before they become incidents.
Eliminate repetitive operational work through automation. Free engineers to solve novel problems, not perform manual procedures.
Expert services to establish operational excellence that keeps your systems reliable and your teams effective.
Design and deploy comprehensive observability that gives you visibility into system behavior without drowning in data or cost.
Define meaningful SLOs aligned with user experience, implement error budgets, and establish the governance processes that make reliability data actionable.
Redesign incident response to be structured, effective, and continuously improving. Transform incidents from chaos into learning opportunities.
Build confidence in system reliability through failure mode analysis, chaos engineering practices, and game days that prove your systems can handle the unexpected.
Evaluate your current on-call burden and automation maturity. Identify opportunities to reduce toil, improve engineer quality of life, and increase operational efficiency.
Common questions about running cloud infrastructure that performs reliably at any scale.
Monitoring tells you when predefined things break. Observability helps you understand why things break—including failure modes you didn't anticipate. If debugging production issues requires tribal knowledge, if you can't trace a request across services, or if your dashboards don't help during incidents, you have monitoring but not observability. The distinction matters when you're troubleshooting at 3 AM.
Start with user journey mapping to understand what "reliable" means to your customers. Set initial SLOs based on business requirements and reasonable assumptions—they don't need to be perfect. Measure for 2-3 months, then refine based on actual data. The practice of measuring and discussing reliability is more valuable than perfect initial targets.
Alert fatigue usually stems from alerting on symptoms instead of impact, lack of severity differentiation, and missing context for response. We focus on alerting that indicates user-facing impact, clear severity levels that drive appropriate response, and runbooks that make alerts actionable. The goal is fewer, better alerts—not more coverage.
Done properly, chaos engineering reduces risk by finding weaknesses before customers do. We start with game days in non-production environments, graduate to controlled production experiments with limited blast radius, and always implement abort conditions. The risk of not testing resilience is discovering your systems can't handle failure during an actual incident.
Connect operational metrics to business outcomes. Incident frequency and duration impact customer experience and revenue. On-call burden affects retention and hiring. Toil consumes engineering capacity that could ship features. We help you build the business case using your own data—showing what reliability costs, what outages cost, and where investment has the best ROI.
Start by measuring the actual burden—page volume, hours interrupted, sleep impact. Then categorize: which alerts are actionable? Which indicate real problems vs. noise? Which could be automated? Often, 20% of alert types cause 80% of pages. Quick wins come from eliminating noise and automating common responses. Our On-Call & Automation Assessment provides a structured approach.
Prioritize by frequency × time × error rate. Tasks that happen often, take significant time, and are error-prone when done manually have the best automation ROI. Common high-value targets: environment provisioning, certificate rotation, log cleanup, common incident remediation, and deployment verification. Start with runbooks you already have documented—they're automation specifications waiting to be implemented.
We assess across dimensions: observability coverage, SLO adoption, incident response effectiveness, resilience practices, automation maturity, and on-call health. Each dimension has concrete indicators—not vanity metrics, but measures that correlate with actual operational outcomes. Our assessments provide a baseline and roadmap for improvement.
A focused, hands-on session
A focused, hands-on session where we review your observability, incident response, and operational practices. Walk away with clear priorities and practical next steps.
Recent insights on running resilient systems that perform reliably at any scale.
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Read moreWhether you're drowning in alerts, struggling with incident response, or ready to build real resilience—we can help you establish operational excellence.
30 minutes to discuss your operational challenges and explore how we can help