+351 913 512 237 [email protected]

Vendor-Neutral Observability for Logs, Metrics and Traces

We are an observability engineering company that designs and implements OpenTelemetry-based architectures for legacy and distributed systems

From Kubernetes and cloud to on-prem environments, we standardize telemetry collection, correlate data end-to-end and apply governance with SLO/SLI, ILM and CI/CD validation to reduce MTTR and keep costs predictable.

Talk to an Observability Specialist See How We Work

Open-Source Observability

SigNoz: The Open-Source Alternative Compatible with OpenTelemetry

By Monitoring Framework Reading time: 7–9 min

In a landscape where observability is essential for any company running distributed applications, SigNoz stands out as a robust, modern, open-source alternative that is fully compatible with OpenTelemetry. If your organization aims to reduce costs, eliminate vendor lock-in and keep full control over logs, metrics and traces — this article is for you.

The Origin of SigNoz: Transparency and Freedom of Choice

SigNoz was created in 2020 by Pranay Prateek and Ankit Nayan to democratize observability. At the time, the market was dominated by closed, expensive commercial tools — efficient, but with complex pricing models and strong vendor dependency.

Inspired by open-source solutions such as Prometheus, Grafana and Jaeger, SigNoz was born to unify metrics, logs and traces in a single pane, reducing setup time and operational complexity. Today, it is maintained by SigNoz Inc. and an active community.

What SigNoz Offers: End-to-End Observability

SigNoz includes everything a company needs to monitor applications, microservices and infrastructure — without relying on external services.

  • Unified collection (logs, metrics and traces) via the OpenTelemetry Collector.
  • Dashboards that are ready-made and customizable for performance and availability.
  • Visual Query Builder for metrics and traces (no PromQL required).
  • Native integration with Kubernetes, containers and distributed workloads.
  • Alerts and infrastructure metrics (CPU, memory, latency, throughput).
  • Correlation between logs and traces for faster troubleshooting.
  • Flexible deployment via Docker, Helm, or directly on Kubernetes.

Why It’s Gaining Popularity

  1. Predictable costs with no licenses — open-source project.
  2. Full data control — you decide where to store and for how long.
  3. OpenTelemetry compatibility — a modern, vendor-neutral standard.

OTel compatibility enables instrumentation for .NET, Java, Python, Node.js, Go and Kubernetes workloads using a standardized, extensible configuration.

How SigNoz Integrates with OpenTelemetry

Typical telemetry pipeline with SigNoz:

Application → OpenTelemetry SDK → OpenTelemetry Collector → SigNoz

This enables correlated metrics, logs and traces — something that used to require three separate tools (Prometheus, Loki, Jaeger). The operational simplicity benefits DevOps, SRE teams and observability architects.

Benefits of SigNoz for Companies

  • Governance and compliance over retention, access and anonymization.
  • Compatibility with corporate frameworks (ILM, standards, instrumentation templates).
  • Hybrid environments (cloud + on-premise) without SaaS dependency.
  • Horizontal scalability for high-volume Kubernetes environments.
  • Cost reduction on licensing and data ingestion.

SigNoz + Monitoring Framework: Governed Observability

In the vendor-neutral approach of the Monitoring Framework, SigNoz works as a unified backend for logs, metrics and traces; it pairs with Elastic, Prometheus and Grafana depending on organizational maturity; and it adheres to standard OpenTelemetry pipelines, simplifying governance at scale across multiple environments.

Conclusion

SigNoz is a milestone in open-source observability. With it, companies build modern, scalable and governed pipelines — maintaining autonomy and making data-driven decisions without closed ecosystems.

SigNoz OpenTelemetry Open-Source Observability Kubernetes Monitoring Datadog Alternative

Perfect For Your Stack

Whether you're running microservices, serverless or hybrid infrastructure

Microservices

Track distributed traces across hundreds of services with unified correlation IDs and context propagation

  • Service mesh integration
  • Auto-discovery of dependencies
  • Cross-service tracing

Kubernetes

Full visibility into containerized workloads with automated pod discovery and cluster-wide metrics

  • DaemonSet collectors
  • Resource tracking
  • Pod-level insights

Serverless

Monitor ephemeral functions with cold start tracking, invocation traces and cost attribution

  • Lambda/Function tracking
  • Cold start analysis
  • Event source mapping
Discuss Your Infrastructure

The Observability Challenge

Modern distributed systems create complexity that traditional monitoring can't handle

Lack of Visibility

Blind spots across microservices, Kubernetes clusters and cloud providers make troubleshooting impossible

Disconnected Metrics

Logs, metrics, and traces living in silos prevent correlation and root cause analysis

Vendor Lock-in Risk

Proprietary tools create dependency, inflated costs and limited flexibility

Our Solution

Clear Pipelines

End-to-end observability pipelines built on OpenTelemetry standards

Standardization

Unified schema (ECS), structured logging (Serilog) and consistent instrumentation

Governance

ILM policies, retention strategies and cost optimization built-in from day one

Our Methodology

A proven approach to implementing world-class observability

1

Diagnosis

Assessment of current monitoring state, pain points and infrastructure landscape

2

Pipeline Design

Architecture of vendor-neutral observability pipelines tailored to your stack

3

OpenTelemetry Instrumentation

Implementation of standardized telemetry collection across all services

4

Governance & Templates

Setup of ILM policies, retention rules and reusable instrumentation templates

5

Insights Dashboards

Creating dashboards and visualizations in a variety of tools for real-time visibility

Why Choose Our Consultancy

Built for modern infrastructure, designed for enterprise scale

Clear & Reliable Observability

Unified view across all systems with correlated logs, metrics and traces

Resilience & Scalability

Battle-tested patterns that grow with your infrastructure

Multi-Cloud Flexibility

Vendor-neutral architecture works with any cloud provider or on-premises

Optimized Costs

Smart data lifecycle management and efficient resource utilization

The Transformation

See how teams move from chaos to clarity with our framework

Before

  • Multiple disconnected monitoring tools
  • Hours spent correlating logs and metrics manually
  • Unpredictable observability costs
  • Blind spots in critical services
  • Vendor lock-in anxiety

After

  • Unified observability pipeline
  • Automatic correlation across all telemetry
  • Predictable, optimized costs with ILM
  • Complete visibility with zero blind spots
  • Freedom to choose any backend
Start Your Transformation

Built by Experts, Proven in Production

Created by professionals with extensive experience in high-volume, mission-critical distributed systems

Our methodology has been battle-tested in environments processing millions of events per second, ensuring your observability infrastructure can handle whatever comes its way.

Ready to Transform Your Observability?

Let's discuss how our expertise can bring clarity, governance and control to your distributed systems.

Schedule a Conversation

Common Questions

Everything you need to know about implementing the framework

How long does implementation typically take?

Most organizations see their first pipelines operational within 2-4 weeks. Full implementation across all services typically takes 6-12 weeks, depending on infrastructure complexity and team availability.

Do we need to replace our existing monitoring tools?

Not necessarily. Our framework is designed to work alongside existing tools during migration. You can gradually transition services while maintaining your current setup, ensuring zero disruption to operations.

Which backends are supported?

We work with vendor-neutral frameworks and works with any OpenTelemetry-compatible backend: Elasticsearch, Grafana Stack, Prometheus, Jaeger or commercial solutions like Datadog and New Relic. You maintain full flexibility.

How does this reduce costs?

Through intelligent data lifecycle management (ILM), sampling strategies and efficient storage policies. Most teams see 30-60% reduction in observability costs while improving data quality and retention.

What kind of support is included?

We provide hands-on implementation support, architecture reviews, template customization and team training. Post-implementation, you'll have documentation and best practices to maintain and evolve your observability infrastructure independently.

What is vendor-neutral observability and why does it matter?

Vendor-neutral observability means your telemetry architecture is based on open standards like OpenTelemetry instead of a single monitoring vendor. This protects your data portability, reduces lock-in and gives you flexibility to route logs, metrics and traces to the best backend for cost and performance.

How do you implement OpenTelemetry for logs, metrics and distributed tracing?

We standardize instrumentation across services, deploy scalable OpenTelemetry Collector pipelines, and enforce semantic conventions for telemetry correlation. This enables reliable distributed tracing, complete request context and faster root-cause analysis in microservices environments.

Can this observability framework run on Kubernetes, cloud and on-premise?

Yes. The framework is designed for hybrid environments, including Kubernetes clusters, multi-cloud, and on-premise workloads. We define ingestion and routing patterns that keep telemetry consistent across platforms while preserving governance, security and performance.

How do SLO and SLI practices improve incident response and MTTR?

By defining service-level indicators and objectives tied to business outcomes, teams detect degradations earlier and prioritize alerts by user impact. Combined with trace and metric correlation, this approach reduces noisy alerts and helps lower mean time to resolution (MTTR).

How does observability governance control telemetry volume and cost predictability?

We apply governance policies for instrumentation quality, sampling, retention and index lifecycle management (ILM). These controls reduce high-cardinality noise, optimize storage usage and create predictable observability costs without losing critical diagnostic signals.

Do you integrate observability checks into CI/CD pipelines?

Yes. We integrate instrumentation validation into CI/CD so teams can detect missing spans, broken attributes and telemetry regressions before production. This keeps observability quality high as services evolve and deployment frequency increases.

Still have questions?

Let's Talk About Your Needs

The Future of Observability is Open and Governed

Why vendor-neutral observability with OpenTelemetry is redefining reliability, cost control, and incident response across Kubernetes, cloud, and on-prem environments

Modern observability is no longer about isolated dashboards. In distributed architectures, teams need end-to-end visibility across services, queues, and data stores. Without that context, incidents take longer to diagnose, escalation costs rise, and customer-facing risk increases.

The core challenge is vendor lock-in. Many organizations still depend on proprietary monitoring stacks that drive up telemetry costs and limit architecture evolution. As data volume grows, observability becomes harder to scale and less predictable to budget.

That is why vendor-neutral observability based on OpenTelemetry has become a strategic priority. Open standards let you correlate logs, metrics, and traces while maintaining flexibility to integrate Elastic, Datadog, Grafana, and other backends without re-instrumenting every service.

"The organizations winning at observability aren't those with the most expensive tools. They're the ones with clear pipelines, governed data lifecycles, and the flexibility to adapt as their infrastructure evolves."

Openness alone, however, is not enough. Without governance, telemetry quality degrades fast: inconsistent attributes, cardinality spikes, duplicated events, and alert fatigue. Observability frameworks solve this by standardizing instrumentation, collector pipelines, and data lifecycle policies.

High-performing teams treat observability as an engineering discipline. In practice, that means:

  • Decoupled ingestion architecture for scalability and backend flexibility.
  • Distributed tracing standards for faster root-cause analysis in microservices.
  • SLO/SLI-driven operations to prioritize alerts by business impact.
  • ILM and retention governance to improve telemetry cost predictability.
  • CI/CD instrumentation validation to prevent observability regressions before production.

What changes in day-to-day operations

With mature observability governance, engineering and SRE teams reduce noise and focus on meaningful signals. Correlated traces and metrics shorten troubleshooting loops, reduce mean time to resolution (MTTR), and improve release confidence in fast-moving environments.

Financial outcomes improve as well. Intelligent sampling, retention, and indexing policies remove low-value telemetry while preserving critical diagnostics. The result is better operational visibility with more predictable spend.

Why this matters now

As architectures become event-driven and multi-platform, relying on one observability vendor is an increasing strategic risk. Teams that adopt open, governed frameworks gain the flexibility to evolve technology choices without sacrificing reliability or speed.

In short: the future of observability is not more data, but better-governed data. Organizations that move early will improve resilience, accelerate incident response, and build a stronger foundation for growth.

Framework de observabilidade bancária Lisboa Framework de observabilidade financeira Lisboa Governança de observabilidade financeira Lisboa Governança OpenTelemetry Lisboa Monitorização bancária Lisboa Monitorização com correlação de métricas Lisboa Monitorização com ILM financeiro Lisboa Monitorização com OpenTelemetry Collector Lisboa Monitorização com Prometheus e Grafana Lisboa Monitorização com PromQL e KQL Lisboa Monitorização com SigNoz Lisboa Monitorização de APIs financeiras Lisboa Monitorização de aplicações financeiras Lisboa Monitorização de bases de dados bancárias Lisboa Monitorização de compliance financeira Lisboa Monitorização de eventos financeiros Lisboa Monitorização de infraestrutura financeira Lisboa Monitorização de logs e métricas financeiras Lisboa Monitorização de métricas financeiras Lisboa Monitorização de performance financeira Lisboa Monitorização de pipelines financeiros Lisboa Monitorização de serviços bancários Lisboa Monitorização de sistemas de pagamento Lisboa Monitorização de transações financeiras Lisboa Observabilidade com Datadog Lisboa Observabilidade com Elastic APM Lisboa Observabilidade com Elastic Stack Lisboa Observabilidade com tracing distribuído Lisboa Observabilidade com Uptrace Lisboa Observabilidade corporativa Lisboa Observabilidade de APIs de pagamento Lisboa Observabilidade de microserviços bancários Lisboa Observabilidade distribuída Lisboa Observabilidade em aplicações bancárias Lisboa Observabilidade em cloud híbrida Lisboa Observabilidade em fintechs Lisboa Observabilidade em Kubernetes financeiro Lisboa Observabilidade financeira Lisboa Observabilidade multi-cloud financeira Lisboa Observabilidade resiliente Lisboa Observabilidade vendor-neutral Lisboa OpenTelemetry bancário Lisboa
Falar no WhatsApp WhatsApp Falar no Telegram Telegram Falar no Slack Slack