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Site Reliability Engineering Services

Make Production Reliability Measurable, Actionable, and Owned.

Mayan.Host helps engineering teams define reliability targets, build useful observability, improve incident response, and remove recurring production risks. We turn uptime, latency, errors, capacity, and recovery into an operating system your team can measure, prioritize, and improve without slowing product delivery.

SLO A reliability target tied to user experience and business impact
MTTR Recovery time measured and improved through response discipline
3 signals Metrics, logs, and traces connected for production diagnosis
1 loop Incidents, changes, capacity, and corrective work reviewed together

Best Fit

When SRE Services Are the Right Engagement

SRE creates the most value when production reliability affects revenue or trust, incidents recur without durable correction, and teams need measurable priorities instead of more alerts.

Incidents repeat without reducing future risk

Recovery is only half the job. Reliability stalls when root causes remain unclear, corrective actions lose ownership, and the same failure pattern returns.

  • Post-incident reviews describe events but do not drive completed work.
  • Temporary mitigations quietly become permanent operating procedures.
  • Recurring alerts and failure modes remain accepted as normal.

Monitoring produces noise instead of confidence

More telemetry does not automatically improve reliability. Teams need signals tied to service health, user impact, ownership, and a clear response.

  • Alert volume is high but actionable information is low.
  • Dashboards show infrastructure health without explaining customer impact.
  • Engineers search across disconnected logs, metrics, and traces during incidents.

Reliability work competes with every product priority

Without explicit targets and error budgets, reliability decisions become subjective and urgent work repeatedly interrupts planned delivery.

  • Teams cannot agree when reliability needs to take priority over features.
  • Capacity and performance work starts only after user impact appears.
  • Production ownership is concentrated in a few experienced engineers.

Scope

What We Measure and Improve

The scope connects reliability targets, telemetry, incident response, capacity, change risk, and operational learning into one production feedback system.

SLOs, SLIs, and error budgets

We translate user expectations and business impact into reliability measures that guide engineering priorities.

  • Service inventory, critical user journeys, dependencies, and ownership
  • Availability, latency, correctness, freshness, durability, and throughput indicators
  • SLO targets, measurement windows, error budgets, and decision policies

Observability architecture

We connect telemetry to the questions responders and service owners need to answer during normal operation and incidents.

  • OpenTelemetry, metrics, logs, traces, events, errors, and profiling
  • Service dashboards, dependency views, release markers, and user-impact signals
  • Retention, cardinality, sampling, cost, access, and telemetry pipeline design

Alerting and on-call readiness

Alerts are designed around urgent, actionable conditions with clear ownership and enough context to begin response.

  • Severity, thresholds, routing, deduplication, suppression, and escalation
  • Runbooks, responder roles, handoffs, communication, and status updates
  • On-call readiness reviews, exercises, and alert-quality improvement

Incident response and learning

We improve how teams detect, coordinate, recover, communicate, and learn from production incidents.

  • Incident command, triage, mitigation, stakeholder communication, and recovery
  • Timeline reconstruction, contributing factors, root-cause analysis, and evidence
  • Corrective actions prioritized by recurrence risk and tracked to completion

Capacity and performance

We identify limits before they become outages and tune systems against real traffic, latency, resource, and growth behavior.

  • Capacity models, demand trends, saturation signals, and scaling thresholds
  • Application, database, cache, queue, storage, network, and Kubernetes analysis
  • Load testing, bottleneck diagnosis, performance baselines, and growth planning

Change reliability and toil reduction

We reduce production risk by improving release controls and automating repetitive work that consumes engineering attention.

  • Change failure analysis, deployment health, rollback, and release guardrails
  • Toil inventory, automation priorities, runbook automation, and self-service
  • Reliability reviews connected to DevOps, security, and infrastructure work

Reliability Model

A Practical SRE Workflow From Baseline to Improvement

The goal is not perfect uptime at any cost. It is an explicit reliability target, fast recovery, controlled change, and a repeatable method for reducing the failures that matter.

01

Baseline production reliability

We map critical services, user journeys, incidents, telemetry, dependencies, ownership, and the risks already visible to your team.

  • Review architecture, service health, alerts, incidents, changes, and support workflows.
  • Identify reliability gaps, noisy signals, fragile dependencies, and concentrated knowledge.
  • Agree on the services and user outcomes that need measurement first.
02

Define targets and response

We create the reliability baseline your team will use to make decisions and respond consistently.

  • Define SLIs, SLOs, error budgets, service ownership, and reporting.
  • Improve dashboards, alerts, runbooks, severity, and escalation paths.
  • Set incident, review, communication, and corrective-action practices.
03

Implement the highest-value improvements

We address the reliability gaps with the strongest user impact and recurrence risk before expanding the program.

  • Instrument services and connect metrics, logs, traces, and release context.
  • Resolve alerting, capacity, performance, recovery, and change-control gaps.
  • Automate repetitive response and operational work where it reduces toil.
04

Operate the reliability loop

Reliability improves through regular review of service levels, incidents, changes, capacity, and completed corrective work.

  • Review SLO performance, error-budget consumption, incidents, and alert quality.
  • Prioritize reliability work against product delivery using shared evidence.
  • Improve targets, automation, capacity, and response as systems evolve.

Deliverables

What You Get

  • Production reliability assessment and prioritized improvement backlog
  • Service inventory, ownership map, critical user journeys, SLIs, and SLOs
  • Error-budget policy and reliability reporting for engineering decisions
  • Observability architecture, instrumentation, dashboards, and actionable alerting
  • Incident response roles, severity, escalation, communication, and runbooks
  • Root-cause analysis process with corrective-action ownership and tracking
  • Capacity, performance, change-risk, toil, and reliability automation support

Outcomes

What Changes

  • Reliability priorities tied to user impact instead of subjective urgency
  • Faster diagnosis and recovery through connected telemetry and clear response
  • Fewer recurring incidents because corrective work remains owned and visible
  • Lower alert noise and less operational interruption for product engineers
  • Earlier capacity and performance decisions before customers feel saturation
  • A repeatable reliability program that scales beyond individual engineers

Keep Your Current Platform. Improve How Reliability Is Managed.

SRE improvement does not require an immediate migration or tooling replacement. We can establish reliability practices across your existing AWS, GCP, private-cloud, Kubernetes, VM, or hybrid environment, then recommend platform changes only where they clearly reduce production risk.

Request an SRE ReviewReview Managed InfrastructureReview DevOps Services

Start the Review

Share your production reliability context.

Use the form to request an SRE review. A Mayan.Host engineer will assess your services, incidents, telemetry, reliability targets, capacity risks, and the level of implementation or ongoing reliability ownership you need.

  • Tell us which production services and user journeys are most critical.
  • Mention recurring incidents, alert noise, recovery, performance, or capacity problems.
  • Include current monitoring tools, uptime targets, support model, and compliance needs.

Request SRE Reliability Review

FAQ

SRE Services FAQ

Do we need existing SLOs before starting an SRE engagement?

No. We can begin by mapping critical services, user journeys, dependencies, incidents, and available telemetry. From that baseline, we define practical SLIs and SLOs that your team can measure and use for engineering decisions.

Can you improve our current monitoring stack?

Yes. We assess instrumentation, dashboards, alerts, logs, metrics, traces, retention, access, and operating workflows. We retain useful tooling, close visibility gaps, reduce noise, and replace components only when the expected value justifies migration.

Do you provide incident response and root-cause analysis?

Yes. We can help define incident command and escalation, support active triage and recovery within the agreed operating scope, facilitate post-incident reviews, and track corrective actions so recurring risks do not disappear into documentation.

How are SRE services different from managed infrastructure?

SRE focuses on measurable reliability, SLOs, observability, incident learning, capacity, performance, change risk, and toil reduction. Managed infrastructure focuses on ongoing operational ownership such as monitoring, patching, backups, maintenance, and production support.

Can SRE work alongside our DevOps or platform team?

Yes. We commonly work with application, DevOps, platform, security, and infrastructure teams. Responsibility boundaries, service ownership, escalation, implementation work, and operational handoffs are agreed during the assessment.

Can you support AWS, GCP, private cloud, and Kubernetes?

Yes. SRE practices apply across providers and platforms. We work with AWS, GCP, Kubernetes, private cloud, Linux infrastructure, databases, queues, storage, networking, and hybrid systems, using the telemetry and operational tools appropriate to the environment.