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Logz.io Launches Distributed Tracing

Logz.io announced the launch of the Jaeger-based Distributed Tracing solution.

Distributed Tracing enhances and completes Logz.io’s ground-breaking observability mission of providing the best-of-breed open source monitoring tools on a fully managed SaaS platform.

Logz.io now enables engineers to collect, analyze and correlate logs, metrics and traces on a single, open source-based platform to make production monitoring and troubleshooting faster and easier.

As engineering teams continue to develop microservices based applications, the complexities of this increasingly distributed architecture have made it harder to identify and isolate production issues. The open source tracing project, Jaeger, governed and supported by the Cloud Native Computing Foundation, was conceived at Uber in response to these monitoring challenges and their business need to build a microservices and cloud native architecture to meet demands for scale. Jaeger responds to the fundamental shift in the development and operational needs of engineers by supporting the monitoring, verification, debugging, and performance of cloud native applications. According to the recent DevOps Pulse 2020 from Logz.io, Jaeger and other tracing solutions are emerging, with 68% of the 1,000+ engineers surveyed stating that the technology “plays an important role in their observability strategy.”

The Logz.io Distributed Tracing solution complements the ELK-based Log Management and open source Grafana-based Infrastructure Monitoring offerings to provide engineers with an easy-to-use, fully managed and integrated platform. Logz.io Distributed Tracing is completely cloud-based, easy to deploy and onboard. Engineers can use Distributed Tracing to gain a system-wide view of their architecture, stay alerted on failed or high latency requests, and quickly drill into end-to-end call sequences of selected requests of intercommunicating microservices. Users can also reduce time to detect and time to resolve by navigating between traces, logs and metrics. The launch of Jaeger-based Distributed Tracing further solidifies Logz.io’s commitment to the open source community by contributing features and fixes to Jaeger.

Key benefits of Distributed Tracing include:

- Unification with Log Management and Infrastructure Monitoring: - Engineers can monitor and analyze logs, metrics, and traces based on ELK, open-source Grafana, and Jaeger on one unified platform. Jaeger, along with Logz.io’s offering, adheres to the open source projects OpenTracing and OpenTelemetry and guarantees that application instrumentation and trace data will remain relevant across frameworks now and into the future.

- Open Source + Advanced Analytics: Distributed Tracing enables seamless alerting and correlation between logs and traces. This workflow unifies monitoring and troubleshooting to facilitate faster root cause analysis.

- Ease of Use and Cost Efficiency: The solution supports the rich ecosystem of instrumented tracing frameworks, databases and programming languages. Engineers can easily deploy Distributed Tracing and avoid the steep costs of leading proprietary APM-based solutions, and the overhead of managing open source components at scale.

“This solution marks a significant milestone in the development of our end-to-end observability platform,” said Tomer Levy, CEO and Co-founder of Logz.io. “Engineers can now quickly and easily deploy an open source-based tracing solution that allows fast and seamless correlation between logs, metrics and traces on one unified SaaS platform.”

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Logz.io Launches Distributed Tracing

Logz.io announced the launch of the Jaeger-based Distributed Tracing solution.

Distributed Tracing enhances and completes Logz.io’s ground-breaking observability mission of providing the best-of-breed open source monitoring tools on a fully managed SaaS platform.

Logz.io now enables engineers to collect, analyze and correlate logs, metrics and traces on a single, open source-based platform to make production monitoring and troubleshooting faster and easier.

As engineering teams continue to develop microservices based applications, the complexities of this increasingly distributed architecture have made it harder to identify and isolate production issues. The open source tracing project, Jaeger, governed and supported by the Cloud Native Computing Foundation, was conceived at Uber in response to these monitoring challenges and their business need to build a microservices and cloud native architecture to meet demands for scale. Jaeger responds to the fundamental shift in the development and operational needs of engineers by supporting the monitoring, verification, debugging, and performance of cloud native applications. According to the recent DevOps Pulse 2020 from Logz.io, Jaeger and other tracing solutions are emerging, with 68% of the 1,000+ engineers surveyed stating that the technology “plays an important role in their observability strategy.”

The Logz.io Distributed Tracing solution complements the ELK-based Log Management and open source Grafana-based Infrastructure Monitoring offerings to provide engineers with an easy-to-use, fully managed and integrated platform. Logz.io Distributed Tracing is completely cloud-based, easy to deploy and onboard. Engineers can use Distributed Tracing to gain a system-wide view of their architecture, stay alerted on failed or high latency requests, and quickly drill into end-to-end call sequences of selected requests of intercommunicating microservices. Users can also reduce time to detect and time to resolve by navigating between traces, logs and metrics. The launch of Jaeger-based Distributed Tracing further solidifies Logz.io’s commitment to the open source community by contributing features and fixes to Jaeger.

Key benefits of Distributed Tracing include:

- Unification with Log Management and Infrastructure Monitoring: - Engineers can monitor and analyze logs, metrics, and traces based on ELK, open-source Grafana, and Jaeger on one unified platform. Jaeger, along with Logz.io’s offering, adheres to the open source projects OpenTracing and OpenTelemetry and guarantees that application instrumentation and trace data will remain relevant across frameworks now and into the future.

- Open Source + Advanced Analytics: Distributed Tracing enables seamless alerting and correlation between logs and traces. This workflow unifies monitoring and troubleshooting to facilitate faster root cause analysis.

- Ease of Use and Cost Efficiency: The solution supports the rich ecosystem of instrumented tracing frameworks, databases and programming languages. Engineers can easily deploy Distributed Tracing and avoid the steep costs of leading proprietary APM-based solutions, and the overhead of managing open source components at scale.

“This solution marks a significant milestone in the development of our end-to-end observability platform,” said Tomer Levy, CEO and Co-founder of Logz.io. “Engineers can now quickly and easily deploy an open source-based tracing solution that allows fast and seamless correlation between logs, metrics and traces on one unified SaaS platform.”

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In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

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Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

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