Premier Support Partners
Get expert support across Prometheus, Thanos and related open-source observability technologies.
Observability Consulting
Implement monitoring, logging and tracing across distributed systems with expert guidance for Prometheus, Grafana, Loki, OpenTelemetry and modern observability pipelines.

Build scalable and cost-effective observability solutions around open standards, open-source technologies and high-performance telemetry pipelines.
Get expert support across Prometheus, Thanos and related open-source observability technologies.
Design observability solutions using Grafana, Loki, Prometheus, OpenTelemetry, ClickHouse and other telemetry pipeline technologies.
Reduce vendor lock-in and licensing costs through open-source observability architectures designed around your infrastructure.
Build scalable and high-performance telemetry pipelines that consolidate observability data across distributed systems.
Implement OpenTelemetry instrumentation, APM integrations and dashboards to improve visibility across applications and infrastructure.

Improve visibility into Kubernetes and container environments with proactive infrastructure and workload monitoring.
Use technologies such as Thanos, Cortex, Grafana Mimir and VictoriaMetrics to retain Prometheus data over longer periods.
Build telemetry pipelines using tools such as Vector and Logstash to process, route and transform observability data efficiently.
Move from costly proprietary observability platforms to open-source alternatives while maintaining visibility throughout the migration.
Design alerting and incident-response workflows that reduce noise and help engineering teams identify and resolve issues quickly.
Proprietary observability platforms can become increasingly expensive as infrastructure, metric volume, retention requirements and team size grow. Open-source observability provides greater control over telemetry, architecture and long-term operating costs.
76%
of organisations use open-source licensing for observability, with investment in open standards continuing to grow.
Up to 50%
potential cost reduction when moving from proprietary observability platforms to open-source alternatives.
100%
data ownership when telemetry remains inside infrastructure controlled by your organization.
Per-host, per-metric and retention-based pricing can increase rapidly as infrastructure and telemetry volume grow.
Vendor-specific instrumentation makes future migrations expensive. Open standards reduce the need to re-instrument applications when changing backends.
High-cardinality metrics are valuable for debugging modern distributed systems but may be expensive or restricted on proprietary platforms.
Open-source deployment models help organizations keep telemetry inside their own controlled infrastructure where data-location requirements demand it.
Implement metrics collection, visualization and alerting around your infrastructure and operational requirements.
Design scalable and highly available metrics storage with appropriate retention for long-term analysis.
Implement open-source log aggregation suited to retention needs and common query patterns.
Instrument applications once using open telemetry standards and export data to different observability backends when requirements change.
Migrate from commercial observability systems to open-source architectures while maintaining monitoring coverage throughout the transition.
Observability Costs
Compare how different observability platforms and self-hosted architectures scale with usage and retention before committing to a long-term platform strategy.
Traditional infrastructure monitoring does not fully capture the behavior of AI systems. LLM observability brings prompts, completions, token consumption, quality signals and agent workflows into the same operational view.
Trace LLM calls, tool invocations and multi-step agent workflows using OpenTelemetry-compatible instrumentation.
Track token consumption, model costs and cost attribution across teams or applications so expensive AI workflows can be identified and optimized.
Use automated evaluation and production-quality checks to identify hallucinations, response drift and degraded AI output.
Monitor retrieval quality, embedding latency, context-window utilization and reranking behavior across retrieval-augmented generation pipelines.
Trace execution paths across multiple agents, tool calls, memory lookups and inter-agent handoffs.
Export LLM metrics and traces into the same Prometheus and Grafana pipelines used for infrastructure observability.
Improve visibility across distributed systems with a scalable observability architecture and expert support for implementation and operations.
Gain real-time visibility across distributed systems and scale monitoring as infrastructure and workload complexity grow.
Get support for architecture, integration and operation of open-source observability technologies.
Support production Prometheus, Thanos and related observability environments through experienced architecture and operational guidance.
A guide to monitoring, tracing, securing and optimizing production LLM systems.
Learn how to design telemetry pipelines that support data protection and compliance requirements using OpenTelemetry.
Explore a large-scale migration from InfluxDB to Grafana Mimir involving historical metrics, dashboard conversion and observability architecture modernization.
Explore open-source logging technologies for cloud-native monitoring and troubleshooting.
A practical guide to evaluating observability platforms based on technical and operational requirements.
Explore how OpenTelemetry can improve visibility into CI/CD performance, troubleshooting and scalability.
Learn Prometheus monitoring fundamentals, PromQL, alerting and Kubernetes/Grafana integration.
Explore Prometheus scaling with Thanos for long-term storage, global querying and large Kubernetes environments.
Review Prometheus practices for metrics naming, labels, queries, storage, alerting, scaling and access security.