Built-in Observability

Built-in Observability

Observability is the measure of how well its external outputs can determine the internal states of a system. In other words, Observability describes the degree to which systems and services are behaving based on collected data.

A metric represents a measurement of some activity performed by services. Whereas logging tracks discreet historical events, metrics provide service data activity in aggregate, over time. While logging provides qualitative data, metrics provide quantitative data. A trace represents a series of causally related distributed events that encode the end-to-end request flow through a distributed system.

There are many benefits to using Kubernetes and ongoing challenges due to its ephemeral and dynamic nature. One of the main challenges is centralizing Kubernetes logs and metrics. In Kubernetes, when pods are evicted, crashed, deleted, or scheduled on a different node, the logs from the containers are gone. The system cleans up after itself without losing any information about why the anomaly occurred. The transient nature of default logging in Kubernetes makes it crucial to implement a centralized log management solution.

This limited Observability is why it’s so difficult to troubleshoot problems with Kubernetes. Although there are many open sources and commercial tools/products/services for monitoring, logging, alerting, tracing, and visualizations, DevOps teams need to integrate them into a Kubernetes environment, which means additional overhead to manage and maintain them. They need to learn each app, including its configurations, backup plans, APIs, and storage, making the overall management complicated.

The snapblocs SaaS-based UI helps DevOps monitor and manage the operational health of stacks. With built-in Observability to analyze deployed stacks gaining actionable insights quickly and securely, including metrics, logs, APM data, and alerts.

Kubernetes recommends two options: send all logs to Elasticsearch, or use a third-party logging tool of choice. For example, this Kubernetes document describes how to send all logs to Elasticsearch. snapblocs implements centralized cluster-level logging by default to provide built-in Observability features out of the box. Each snapblocs Architecture Blueprint uses Elastic Stack ELK, Grafana, Prometheus, and Kubernetes dashboard UI to provide Observability. Elastic Stack ELK consists of Elasticsearch, Logstash, Kibana, MetricBeats, FileBeats. 

snapblocs enables DevOps to inspect the entire architecture through its built-in operational dashboard. DevOps can quickly gain insights into infrastructure, applications, and data through centrally collected and aggregated metrics and logs.

snapblocs stacks, using Architecture Blueprints, are deployed with built-in Observability using Elastic Stack and other monitoring tools.

Elastic Beats includes Filebeat, Metricbeat, and Packetbeat, installed as a Kubernetes DaemonSet to ensure a running instance on each cluster node. Use instances to retrieve most logs and metrics from the host and all the services running on top of Kubernetes.

This diagram shows the architecture of snapblocs Architecture Blueprints with default built-in Observability features.

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