TRACES
Distributed Tracing
Troubleshoot and analyze performance issues with LOGIQ.AI’s OpenTelemetry and Jaeger-compatible Distributed Tracing implementation.
Architecture and components
Inbound and outbound integrations
Security, Compliance and Scale
Log aggregation, management & analytics
Application & infrastructure metrics
Trace transactions between distributed services
Converge and analyze any data source
Optimize spend and remediate faster
Improve compliance and interpret better
Supercharge analytics and improve predictions
Send right data to right target every time
Instantly replay historical data to any target
Petabyte-scale indexing and instant retrieval
Instantly search and visualize at petabyte-scale
Instantly replay historical data to any target
Benefits of Operational Data Lake
One-up your Elastic cost with LOGIQ
Level up your AWS Observability
Topology-based Observability/Data Fabric
Achieve 100% pipeline-control with FLOW
IoT Observability with LOGIQ
FREE e-books on technology and observability topics
Learn how to use LOGIQ with our quick start guide
See how we stack against other vendors
Get the most out of LOGIQ though these video demos.
Learn more about LOGIQ in these product briefs.
Articles and guides that help you make data-driven decisions
Benefits of Operational Data Lake
One-up your Elastic cost with LOGIQ
Level up your AWS Observability
Topology-based Observability/Data Fabric
Achieve 100% pipeline-control with FLOW
IoT Observability with LOGIQ
Money, shares, credit, investments
Comply with industry regulations
Get control over Datadog observability
Facilitate the provision of healthcare to patients
Diagnose and troubleshoot complex problems
Reduce index and resource requirements in ELK deployment
Physical objects with sensors, processing ability, software etc.
Maintain high reliability for your business
Reduce Splunk costs, simplify long-term retention
Film, television, radio, print, and gaming
Secure hybrid cloud operations and protect your business
Reduce Sumo Logic costs and simplify long-term retention
Sale of goods and services to consumers
Benefits of Operational Data Lake
One-up your Elastic cost with LOGIQ
Level up your AWS Observability
Topology-based Observability/Data Fabric
Achieve 100% pipeline-control with FLOW
IoT Observability with LOGIQ
Step-by-Step instructions for common tasks
Step-by-Step instructions to deploy LOGIQ in Kubernetes
Learn more
Integrate with automation and scripted worflows.
Deploy LOGIQ on AWS using CloudFormation
FREE e-books on technology and observability topics
Get the most out of LOGIQ though these video demos.
Learn how to use LOGIQ with our quick start guide
Learn more about LOGIQ in these product briefs.
Articles and guides that help you make data-driven decisions
See how we stack against other vendors
Learn more
Step-by-Step instructions for common tasks
Free dashboards for popular applications
Integrate with automation and scripted worflows.
Step-by-Step instructions to deploy LOGIQ in Kubernetes
Deploy LOGIQ on AWS using CloudFormation
Run LOGIQ in a Docker Compose sandbox
TRACES
Troubleshoot and analyze performance issues with LOGIQ.AI’s OpenTelemetry and Jaeger-compatible Distributed Tracing implementation.
Distributed tracing can be complex to set up and maintain, especially in large and distributed systems.
Collecting and transmitting trace data can add significant overhead to application performance.
The amount of trace data that can be generated in a large and distributed system can be overwhelming and difficult to scale.
Storing and transmitting trace data can raise concerns about data privacy and security.
Analyzing and making sense of large amounts of trace data can be challenging, requiring specialized tools and expertise.
Correlating trace data across different services and systems can be difficult, especially when dealing with different data formats and structures.
BENEFITS
Correlate and analyze data from different parts of your system
View timings, errors, logs, and flows on one screen.
Save time by having all the relevant data in one place.
Trace the flow of a request to identify the root cause of an issue.
Troubleshoot your distributed applications quickly and easily.
FEATURES
HOW IT WORKS
Tracing refers to the process of tracking the flow of a request or transaction as it moves through an organization’s systems and applications. This involves tracking things like request latency, error rates, and the dependencies between different services.
Tracing transactions between distributed services can help developers understand the flow of data between different parts of their systems and identify bottlenecks or issues that may be impacting performance. However, Tracing transactions between distributed services can be challenging, as it requires tracking the flow of a request or transaction through multiple systems and components. This can involve collecting and analyzing data from various sources, such as log files, network packets, and application metrics.
In order to effectively trace transactions between distributed services, it is important to have a comprehensive and centralized view of an organization’s systems and applications. Our observability platform provides this view, allowing for a deeper understanding of your systems and making informed decisions about how to optimize their operations.
Distributed tracing is a technique used to profile and debug distributed systems. A distributed system is a system where components are distributed across multiple machines. Distributed tracing allows you to trace the flow of a request as it goes through the different components of a distributed system. OpenTelemetry and Jaeger are two of the most popular distributed tracing tools.
Distributed systems are systems that are made up of multiple components or services that communicate with each other over a network. These systems can be complex and difficult to understand, especially when things go wrong. Tracing can help to provide visibility into how these systems are functioning and identify potential issues.
Distributed tracing tracks the flow of a request as it travels through various components of a distributed system. It is particularly useful for identifying bottlenecks and debugging issues that may arise in such systems.
LOGIQ.AI ingests traces and logs from the OpenTelemetry collector and Jaeger agent. It implements scalable streaming and indexing of spans, traces and logs directly to any object storage. Users can search and visualize spans, traces, and logs using a simple intuitive built-in UI. Our UI borrows several key aspects from the Jaeger UI project while integrating it seamlessly with LOGIQ.AI’s infinitely scalable InstaStore backend built on top of object storage.
In the LOGIQ.AI UI, navigate to Traces under Explore in the navigational menu.
In the LOGIQ.AI UI, navigate to Traces under Explore in the navigational menu.
You can also click Analyze and get the full span and logs for the trace for download.
Logiq offers to trace capabilities that allow organizations to track the flow of transactions between distributed services.
Logiq.ai utilizes distributed tracing to provide a comprehensive view of the entire lifecycle of a request. This helps users to identify and fix problems more efficiently, as they can see exactly where the request is being slowed down or failing.
INTEGRATE WITH
*Trademarks belong to the respective owners.
The client is an online video & AI-enabled SaaS platform
that helps sales guys sell better over video calls.
Reduction in security analysis reporting time
Faster, easy and holistical data visualization
Queries on month-old data returned in under 5 seconds
Converged logs from AWS services
75TB of logs per month, 30K EPS, peak load of 160GB/h
Ingested and retained 2.5x more data at half the cost with zero storage tax
Note: The datasheet will be sent to your email.