- Prometheus is a powerful open-source system for service monitoring and time series data storage.

- Thanos is a companion tool that adds high availability and long-term storage capabilities to Prometheus.

- Thanos seamlessly integrates with Prometheus and provides object storage for historical data.

- It ensures rapid query response times and offers a global query view for real-time data merging.

- Thanos enables high availability for Prometheus and allows for long-term metrics retention.

- It simplifies the backup process and facilitates cross-cluster scalability.

- Thanos provides cost-effective data access and enhances Prometheus' scalability and reliability.

- Scaling Prometheus with Thanos involves storage configuration, utilizing the Thanos Sidecar, setting up Thanos Query, and aggregating Thanos Query nodes.

- LOGIQ.AI offers a comprehensive platform, LOGIQ Stack, for scaling Prometheus using Thanos.

Fluentbit is an open-source log management tool that enables users to gather data from multiple sources, apply filters, and transmit it to compatible destinations.

Vector by Datadog is a data pipeline for observability that offers cost savings, advanced data enrichment, and enhanced data security.

Fluentd is a lightweight log management tool that supports a wide range of data sources and formats with high customizability.

Logstash is a robust logging tool used for managing logs with powerful transformation capabilities.

Syslog-ng offers tamper-proof storage and rapid search capabilities.

LOGIQ.AI provides reliable integration with open-source observability collectors and processors, enabling users to monitor the performance and health of their systems in order to support improved system performance, security, and overall business outcomes.

The DevOps market is projected to hit $20.53 billion by 2026.
With the growing importance of DevOps, comes a growing set of challenges.

Explore the top 5 DevOps challenges related to observability, and how LOGIQ solves them.

The challenges are the complexity of distributed systems, high cardinality of data, siloed monitoring tools, alert fatigue, and real-time analysis and response.

LOGIQ offers a comprehensive observability platform that integrates seamlessly with service meshes and reduces alert noise through automation.

Kubernetes monitoring is the practice of observing and measuring the health and performance of a Kubernetes cluster and its components.

The main goal is to ensure the availability, reliability, and scalability of the cluster and the applications running on it.

Key metrics to measure include those related to clusters, nodes, pods, deployments, services, containers, and applications.

Best practices for monitoring K8S involve examining details in granular level data; gathering historical system data beyond metrics; understanding control plane monitoring; creating an instrumentation strategy with alerting; using a platform to run containers on physical/virtual machine clusters; utilizing Prometheus; selecting comprehensive Kubernetes monitoring tools.

Popular Kubernetes monitoring tools include Prometheus, Grafana, Fluentd, LOGIQ, and ELK Stack.

The unprecedented growth of data in recent years has led to a demand for evolution in traditional monitoring practices.

The current observability maturity model is a good solution but needs further augmentations.

The widely accepted model includes the following stages:

1) Monitoring (Is everything in working order?)

2) Observability (Why is it not working?)

3) Full-Stack Observability (What is the origin of the problem, and what are its consequences?)

4) Intelligent Observability (How to predict anomalies and automate response?)

LOGIQ is supporting the next stage in the model i.e, Federated Observability. In other words, data availability for consumers with on-demand convenience.