Observability stack

An observability stack is an essential part of a project's success

An observability stack is a set of tools for monitoring and analyzing the performance of applications and infrastructure. Such a stack usually employs several tools that work together to provide full visibility into how the system operates.

There is a great variety of tools that perform these functions, but we'll look at the most popular and actively developing examples.

Grafana is a visual tool for monitoring and analyzing data. It lets you create graphs, charts, and dashboards to track the performance of applications and infrastructure. Grafana integrates with many other monitoring tools, including Prometheus, InfluxDB, Elasticsearch, Graphite, and many others.

One of Grafana's main features is its flexibility and customizability. It lets you create custom panels and graphs, as well as use various types of data visualization, such as graphs, charts, tables, and so on. In addition, Grafana has a wide range of plugins that allow you to add new functionality and integrate with other tools.

Grafana also has many features for access management and security, which allow you to restrict access to data and dashboards to only the right users. In addition, it can create and send notifications by email or to messengers when certain metric thresholds are exceeded.

Overall, Grafana is a powerful tool for monitoring and analyzing data that can be used to track the performance of applications and infrastructure in real time, as well as to analyze and optimize the operation of the system as a whole.

Grafana Labs, the developer of Grafana, also offers a range of other closely related monitoring products, such as Loki (for collecting logs) and Tempo (for distributed metrics).

Prometheus is a tool for collecting and storing metrics from applications and infrastructure. It uses the PromQL query language to analyze data and provides a web interface for visualizing metrics. Prometheus also lets you create alerts based on changes in metrics. One of Prometheus's main features is its data model, which is based on time-series data. It collects metrics from many sources using its own data-collection protocol, called Prometheus Remote Procedure Call (RPC). After collecting the data, Prometheus stores it locally in a time-series format, which makes it possible to analyze the data and provide access to it through the web interface.

Prometheus also has the powerful PromQL query language, which lets you analyze and filter metrics, as well as build graphs and charts based on that data.

In addition, Prometheus has many monitoring and alerting features that let you receive notifications when metric thresholds are exceeded, as well as analyze and optimize system performance.

OpenTelemetry is a set of tools for monitoring applications and infrastructure that lets you collect various types of data, including metrics, logs, and request tracing. It supports many programming languages and integrates with many other monitoring tools, including Grafana and Prometheus. OpenTelemetry supports languages such as Java, Python, Go, C#, and others. It includes two main components — the OpenTelemetry Collector and the OpenTelemetry SDK.

The OpenTelemetry Collector is a component responsible for collecting and transmitting data from applications and infrastructure to various monitoring tools. It supports many data formats, including metrics, logs, and request tracing, and also lets you convert data between different formats.

The OpenTelemetry SDK is a component used inside applications to collect and process monitoring data. It lets you integrate OpenTelemetry into applications and collect monitoring data such as metrics, logs, and request tracing.

OpenTelemetry also has many integrations with other monitoring tools, including Grafana, Prometheus, Jaeger, and Zipkin. This makes it possible to use OpenTelemetry together with other monitoring and data-analysis tools.

Together, these tools make up an observability stack that lets developers and engineers keep an eye on the performance of applications and infrastructure, quickly find and fix problems, and improve the quality of the system's operation.