Observability
We help DevOps teams build or refine OpenTelemetry stacks to control costs, reduce troubleshooting time and improve detection of business-impact incidents.
Running Prometheus and Grafana, but still in the dark?
We help our clients reduce observability costs while gaining sharper insights.
Ask us how our HELM-based stack and OpenTelemetry know-how can work for you.
Metrics everywhere.
Clarity nowhere.
Our optimization sprint will tune your dashboards, alerts, and pipelines for signal, not noise.
Planning a Kubernetes rollout? Observability isn't optional.
We help organizations design future-proof, cloud-native observability built to scale with the organization.
We offer focused sprints or medium-term projects - modular, time-bound packages designed to deliver tangible value within 1 to 3 months. Each serves as a starting point and can be customized to meet your technical goals, resource constraints, and organizational context.
Observability Services Offerings
Observability Posture Assessment
Evaluate current observability maturity
Production-Grade Stack Deployment
Deploy reliable observability stack
Observability Optimization Sprint
Tune configurations of efficiency
Observability for AI Systems
Instrument AI systems with Observability
1 Observability Posture Assessment
Duration: 2–4 weeks
Target: Organizations unsure about their current observability maturity or planning improvements.
What We Do:
- Evaluation of your current observability architecture and maturity against industry benchmark and OpenTelemetry standards.
- Benchmarking operational and cost efficiency by improving various fields such as reduced outages, defining error budgets, and improving overall cost (FinOps)
- Gap analysis against modern best practices - find the blind spots within your current monitoring, logging, and tracing
Deliverables:
- Executive summary
- Technical Action Plan
- Prioritized recommendations
- Team readiness assessment
Best For: CTOs, SREs, or DevOps leads looking for clarity before investing in tools or changes.
2 Production-Grade
Observability Stack
Deployment
Duration: 4–8 weeks
Target: Organizations needing quick and reliable observability enablement.
What We Do:
- Deploy a production-grade observability stack (Grafana, Loki, Prometheus, VictoriaMetrics) using our customizable HELM template.
- Cloud-agnostic deployment (supports AWS, GCP, Azure, and on-prem).
- Logging, metrics, and alerting pipelines integrated via OpenTelemetry.
- Cost-optimized configuration and scaling.
Deliverables:
- Fully deployed and documented observability stack.
- Team walkthrough and operational handover.
Optional Add-On: 3–6 months of support and optimization.
3 Observability Optimization
Sprint
Duration: 4–8 weeks
Target: Teams already using observability tools but facing cost bloat or noisy signals.
What We Do:
- Tune your Grafana, Prometheus, and Loki configurations.
- Eliminate redundant metrics and logs.
- Refactor dashboards for clarity and actionability.
- Optimize scraping intervals, retention policies, and storage use.
Deliverables:
- A streamlined configuration for Prometheus, Grafana, and Loki.
- Consolidated and deduplicated metrics/logs.
- Reworked dashboards with clear visual hierarchies and alerting logic.
Impact: Lower cloud/storage costs, faster incident response, and happier engineers.
4 Observability for
AI and LLM Systems
Duration: 4–8 weeks
Target: Teams building AI-driven applications (chatbots, copilots, retrieval-augmented generation, etc.)
What We Do:
- Instrument LLM request lifecycles using OpenTelemetry.
- Set up prompt and output logging with cost tracking
- Create dashboards with token-level usage metrics and trends.
- Define alerting on degraded performance, latency spikes, or abnormal token spend.
- Integrate observability with vector DBs, embedding pipelines, and frontends.
Deliverables:
- End-to-end tracing of LLM API calls.
- Operational dashboards for token usage, latency, and error rates.