Telemetry architecture
Metrics, logs, traces, instrumentation conventions, and data collection.
SRE and observability consulting for systems your engineers need to understand.
Dashboards are useful only when they help engineers make decisions. Alerts are useful only when someone knows how to act on them. We improve observability and site reliability practices so teams can detect meaningful failures, investigate incidents, and make informed decisions about reliability, capacity, and operational risk.
The problem
You have monitoring tools. Production is still difficult to understand.
The tools are already installed. The incidents still depend on whoever remembers the system.
One incident
As found
- not traced
Metrics in dashboard, Traces in partial tracing, Logs in log search, each on its own time axis. 9 alerts: pages without context.
01
Telemetry is inconsistent
Services expose different metrics, logs, and tracing information, making incidents across multiple components difficult to investigate.
02
Alerts create noise
Teams receive pages they cannot act on, while important failure conditions remain poorly covered.
03
Reliability targets are disconnected from operations
SLOs exist in documents but do not guide alerting, release decisions, or engineering priorities.
04
Incident response depends on individuals
The same engineers are needed to diagnose recurring failures because relevant context and procedures are missing.
What changes
Turn telemetry into decisions engineers can act on.
Useful failure detection
Monitoring focuses on service health and conditions that require action.
One incident
- not traced
- same moment
Metrics in dashboard, Traces in partial tracing, Logs in log search, each on its own time axis. 9 alerts: pages without context.
Objective, Metrics, Traces, Logs on one shared time axis, marked at the same moment. One alert, from the objective, linked to a runbook.
Faster diagnosis
Consistent signals and operational context make it easier to identify where failures originate.
Reliability becomes planned work
Incident findings, SLOs, and recurring operational problems inform engineering priorities.
Reliability engineering and observability services.
Observability implementation
Prometheus, Grafana, OpenTelemetry, logging, tracing, and suitable existing tools.
Alerting
Actionable alerts, escalation policies, and improvements to signal quality.
SLOs and SLIs
Indicators tied to important user-facing behavior, with appropriate error-budget policies.
Incident response
Diagnostic workflows, responsibilities, incident reviews, and operational documentation.
Capacity and performance
Resource utilization, saturation signals, scaling decisions, and operational risk.
Begin with the incidents your monitoring should have helped resolve.
How the work runs
01
Review recent incidents
Identify missing signals, delayed diagnosis, alert noise, and recurring dependencies.
02
Define useful service indicators
Choose the behaviors and failure conditions that matter to users and operators.
03
Implement the instrumentation
Improve telemetry, dashboards, alerts, and relevant operating procedures.
04
Validate the response
Test whether engineers can investigate realistic failures using the new information.
Technologies
Used when they fit the system you already run. Not as a checklist.
Prometheus · Grafana · OpenTelemetry · Loki · Tempo · Alertmanager · CloudWatch
Common questions
Do we need to replace our monitoring tools?
Usually not. We can improve instrumentation, labels, alerting, and operational practices using your existing tools. A migration should solve a specific technical or cost problem.
Do we need SLOs for every service?
No. SLOs are most useful when tied to important user journeys and service expectations. Not every internal component needs a separate formal reliability objective.
Is this an observability installation or SRE consulting?
Both implementation and engineering practices are in scope. The purpose of the tooling is to support reliable operation, incident response, and better engineering decisions.
Do you provide 24/7 incident response?
No. We help teams improve their operational capabilities and can provide agreed ongoing engineering support, but we do not sell a round-the-clock operations desk.
Related
- Kubernetes
A production cluster needs more than a working deployment. We help with cluster design, upgrades, workload configuration, networking, security, and operations. We also evaluate whether Kubernetes is still the right choice.
- Platform engineering
Developers should not need to understand the entire infrastructure stack to ship a service. We create supported development and deployment workflows, reusable templates, and self-service capabilities that reduce dependence on a handful of infrastructure specialists.
- DevOps & CI/CD
Releasing software should not require undocumented procedures or fragile pipelines. We improve builds, tests, deployment automation, GitOps, and release workflows so changes move through a clear and repeatable process.
- Cloud cost optimization
Cloud spending needs context before it can be controlled. We identify waste, investigate costly architecture decisions, improve cost allocation, and help engineering teams manage infrastructure spending without relying on arbitrary savings targets.
Platform assessment
Know what needs fixing before committing to a rebuild.
Our Platform & DevOps Assessment examines the infrastructure, delivery process, operational risks, and cloud costs you already have. You receive prioritized findings and a practical 90-day roadmap, including what to fix first, what can wait, and what should be left alone.