SRE

Observability

OpenTelemetry

Prometheus

Updated Feb 2026

Observability, SRE & Reliability

Fewer surprises, faster recovery. We design full-stack observability platforms and embed SRE practices so your team detects issues in minutes, resolves them faster, and continuously raises the reliability bar.

Quick Answer

HostingX delivers end-to-end observability and SRE consulting — from Prometheus & Grafana stack design, SLO/SLI frameworks, and distributed tracing with OpenTelemetry to chaos engineering game days and 24/7 incident management. Teams we work with typically see 25-40% less alert noise, sub-5-minute mean time to detection, and 60%+ faster mean time to resolution.

What Observability Capabilities Do We Provide?

Six pillars of modern observability and reliability engineering — each tailored to your stack, team size, and SLO targets.

SLIs/SLOs & Alert Design

Define meaningful service level indicators tied to business outcomes. We build error budget policies, burn-rate alerts, and multi-window alerting strategies that surface real problems — not noise.

Distributed Tracing (OpenTelemetry)

Instrument your services with OpenTelemetry for end-to-end request tracing across microservices, queues, and third-party APIs. Pinpoint latency bottlenecks in minutes, not hours.

Log Aggregation & Analysis

Centralize logs with Loki, Elasticsearch, or CloudWatch. Structured logging pipelines, retention policies, and correlation with traces give you full context when investigating incidents.

Chaos Engineering & Resilience

Proactively discover weaknesses with Litmus and Gremlin. Game days, steady-state hypothesis validation, and blast-radius analysis ensure your systems survive real-world failures.

Capacity Planning & Performance

Forecast resource demand using historical metrics and traffic models. Right-size clusters, predict scaling events, and avoid both over-provisioning waste and under-provisioning outages.

Incident Management & On-Call

Structured runbooks, automated escalation chains, and blameless post-mortems. We integrate PagerDuty, Opsgenie, and Slack to reduce cognitive load and accelerate recovery.

What Results Can You Expect?

25-40%

Less alert noise

<5 min

MTTD

99.9%+

SLO attainment

60%+

Faster MTTR

Why Choose HostingX for SRE & Observability?

Hands-on reliability engineers who have operated production systems at scale — not just consultants with slide decks.

End-to-End Visibility

Unified dashboards spanning metrics, logs, and traces — from infrastructure to application to user experience — so no blind spots remain.

Proactive, Not Reactive

Predictive alerting and anomaly detection catch issues before they become incidents, keeping your users unaffected and your SLOs intact.

Cost-Efficient Observability

Smart sampling, tiered retention, and open-source tooling (Prometheus, Grafana, Loki) keep observability costs under control without sacrificing depth.

Continuous Improvement Culture

Blameless post-mortems, SLO reviews, and reliability roadmaps embed SRE culture into your engineering team — not just your ops team.

How Do We Build Observability & SRE Programs?

We follow a structured approach to observability that starts with business outcomes and works backward to instrumentation.

SLO-First Methodology

We begin by defining Service Level Objectives tied to user-facing outcomes — not infrastructure metrics. This means measuring request latency at the 99th percentile, error rates as seen by end users, and availability from the customer's perspective. We then establish error budgets that give engineering teams a quantitative framework for balancing reliability investment against feature velocity. When error budget burns faster than expected, it triggers automated alerts and predefined response procedures.

Full-Stack Instrumentation

We instrument your entire stack with OpenTelemetry for vendor-neutral telemetry collection — metrics, logs, and distributed traces flowing through a unified pipeline. This means you can trace a single user request from the load balancer through API gateways, microservices, message queues, and database queries. We deploy Prometheus for metrics collection, Grafana for visualization, Loki for log aggregation, and Tempo for distributed tracing — providing the three pillars of observability in a cohesive, cost-effective stack that avoids expensive vendor lock-in.

Intelligent Alerting Design

Most organizations suffer from alert fatigue — too many alerts, too little signal. We redesign alerting from scratch using symptom-based detection (what users experience) rather than cause-based alerts (what infrastructure does). We implement multi-window, multi-burn-rate SLO alerting that catches real issues early without firing on transient spikes. Each alert includes a linked runbook with diagnostic steps, remediation procedures, and escalation criteria. The result: fewer pages, faster resolution, and on-call engineers who can actually sleep.

Resilience Validation & Game Days

We don't just build monitoring — we validate it works under failure conditions. Using chaos engineering tools (Litmus, Gremlin), we inject failures into your production environment in controlled experiments: network partitions, pod kills, disk pressure, dependency outages. Game days bring your engineering team together to practice incident response procedures, identify gaps in monitoring coverage, and build confidence in your recovery capabilities. Every experiment produces documentation that feeds back into improved runbooks and monitoring rules.

Case Study Highlight

E-commerce Platform: From Alert Chaos to SLO-Driven Operations

A high-traffic e-commerce platform was generating 400+ alerts per week across 25 microservices, with an on-call team experiencing severe burnout and a 45-minute average MTTR. We implemented an SLO-driven observability stack with OpenTelemetry instrumentation, redesigned alerting around error budgets, and built comprehensive Grafana dashboards for each service team. Results after 12 weeks: 38 actionable alerts/week (90% noise reduction), 4-minute average MTTD, 12-minute MTTR, 99.95% SLO attainment (up from 99.7%), and the on-call rotation expanded to voluntary participation because pages became rare and well-documented.

Frequently Asked Questions

Common questions about our observability and SRE engagements.

We work across the modern observability stack: Prometheus and Thanos for metrics, Grafana for dashboards, Loki for logs, Tempo for traces, and OpenTelemetry for vendor-neutral instrumentation. For managed solutions we also integrate Datadog, New Relic, and PagerDuty for alerting and incident response.

We start by mapping business-critical user journeys to measurable service level indicators (SLIs) — availability, latency, throughput, and error rate. From there we define SLO targets with error budget policies and configure burn-rate alerts that trigger before customers are impacted.

Every alert must be actionable. We implement deduplication, correlation rules, and severity-based routing so on-call engineers receive only the alerts that matter. Escalation policies, silencing windows, and regular alert-hygiene reviews keep noise below 5% of total volume.

Yes. We run controlled fault-injection experiments using Litmus and Gremlin, paired with scheduled game days. Dependency mapping identifies blast radius, and steady-state hypotheses validate that your system degrades gracefully under real-world failure conditions.

We implement a structured incident response framework: automated detection, severity classification, role-based escalation, and real-time communication via Slack or Teams. Every incident concludes with a blameless post-mortem and follow-up action items tracked to completion, driving continuous improvement.