Capillary reduced ops tickets by 95%

“Our releases are fast. And with less developer time needed our teams can focus on building exciting features. We’ve saved countless hours and costs.”

Piyush K,
Chief Architect, Capillary Technologies,

Treebo reduced production issues by 70%

"With Facets, our staging environments look identical to production environments. So in case of production issues, we can be sure there are no infra drifts."

Kadam Jeet Jain,
Co-Founder & CTO, Treebo Hotels and Hotel Superhero.

GGX switched from AWS to GCP in 2 weeks

"Facets has radically changed our DevOps for the better. They did all the heavy lifting and saved us precious time and resources in our when we switched from AWS to GCP."

Kaustubh Bhoyar,
Head of engineering, GGX

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Observability

Prometheus

An open-source monitoring and alerting toolkit designed for reliability, scalability, and observability in dynamic cloud-native environments

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Summary

A monitoring and alerting toolkit tailored for cloud-native environments. It provides powerful capabilities for collecting, storing, and querying time-series data, enabling users to gain valuable insights into the performance and health of their systems and applications. With its flexible architecture, robust querying language, and rich ecosystem of integrations, Prometheus empowers organizations to monitor complex infrastructures effectively and proactively detect and resolve issues before they impact business operations.

Key Features

1. Prometheus efficiently collects and stores time-series data from various sources, allowing users to monitor metrics in real-time.
2. Prometheus Query Language (PromQL) enables users to perform flexible and expressive queries to analyze and visualize metrics data.
3. Supports alerting based on predefined conditions, allowing users to set up alerts and receive notifications via various channels.
4. Prometheus has a rich ecosystem of exporters, integrations, and community-developed tools that extend its functionality and enable seamless integration with other monitoring solutions.

How does it work?

Real world example

Pros

1. Prometheus offers powerful monitoring capabilities for time-series data, making it suitable for monitoring complex systems and environments.
2. Its flexible querying language, PromQL, allows users to perform advanced analytics and gain insights into their systems' performance.
3. Prometheus is highly scalable, capable of handling large-scale deployments with ease, making it suitable for both small and large organizations.
4. Being open-source, Prometheus is freely available and can be customized to meet specific monitoring requirements.

Cons

1. Running Prometheus at scale can require significant computational resources and storage capacity, especially for long-term retention of metrics data.
2.  Mastering PromQL and understanding Prometheus's configuration can be challenging for beginners, requiring a steep learning curve.
3. Prometheus relies on external storage solutions for long-term data retention, which adds complexity to the deployment and management of the monitoring system.
4. Setting up high availability configurations for Prometheus can be complex and may require additional components like Thanos or Cortex to achieve fault tolerance and reliability.

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Capillary reduced ops tickets by 95%

“Our releases are fast. And with less developer time needed our teams can focus on building exciting features. We’ve saved countless hours and costs.”

Piyush K,
Chief Architect, Capillary Technologies,

Treebo reduced production issues by 70%

"With Facets, our staging environments look identical to production environments. So in case of production issues, we can be sure there are no infra drifts."

Kadam Jeet Jain,
Co-Founder & CTO, Treebo Hotels and Hotel Superhero.

GGX switched from AWS to GCP in 2 weeks

"Facets has radically changed our DevOps for the better. They did all the heavy lifting and saved us precious time and resources in our when we switched from AWS to GCP."

Kaustubh Bhoyar,
Head of engineering, GGX

Trusted by companies to run production at scale

Capillary | FacetsMPL | FacetsTreebo | FacetsPurplle | Facets

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