Monitoring systems are critical for having a robust system running in production. When moving to microservices the increased complexity can make it difficult to understand the performance and troubleshooting problems. A robust monitoring system will allow you to gather metrics from services and infrastructure helping you tackle any issues.
With a well placed microservices monitoring, you are better prepared to react to unconventional issues and in predicting system behaviour.
There is a wide range of tools available to monitor microservices. We take a look at the top tools that are most suitable for your SaaS applications:
Logstash is a data pipeline which provides a centralized area where logs and data from a variety of systems are stored and are monitored if any further subsequent actions are required. With monitoring and pipeline viewer features, you can easily observe and study an active node or full deployment.
Logstash is preferred if you are building custom solutions as it’s API allows one to build plugins that work best for your pipeline.
Riemann is a monitoring tool which aggregates events from hosts & applications. It feeds them into a stream processing language to be summarized or edited. The idea behind Riemann is to make monitoring events as easy as possible.
Riemann tracks the state of incoming events and allows your to build checks that take advantage of sequences or combinations of events. It provides notifications, the ability to send events to other services and into storage, and a variety of other integrations. Overall, Riemann has lots of functionality that addresses all microservices monitoring needs.
Prometheus is an open source monitoring platform. Built primarily for monitoring containerized workloads, Prometheus is a popular tool for collecting time series data from instrumented jobs using an open, vendor-neutral, text-based exposition format.
It’s easy to ship your Prometheus metrics to Elasticsearch and unify them with logs and APM data for increased observability.
Prometheus’s main features are:
- a multi-dimensional data model with time series data identified by metric name and key/value pairs
- PromQL, a flexible query language to leverage this dimensionality
- no reliance on distributed storage; single server nodes are autonomous
- time series collection happens via a pull model over HTTP
- pushing time series is supported via an intermediary gateway
- targets are discovered via service discovery or static configuration
- multiple modes of graphing and dashboarding support
Kibana supports some features like interactive visualizations. It’s best suited for monitoring data across elastic stack can view the health and performance data for Elasticsearch, Logstash, and Beats in real time, as well as analyze past performance.
The dashboard makes it easy to share visualizations with your team members, customers, compliance managers etc. using the sharing option that works best for you.
Glowroot is the fast, simple and clean application performance monitoring tool that traces errors and slow requests. It also offers support for visualizing response time percentiles and breakdown in charts.
Glowroot comes in two flavors; first is having embedded-collector which is useful for profiling/monitoring stand-alone applications and another one is having central-collector which can be used to monitor the applications with distributed architecture or micro-service based architecture.
CloudWatch is an Amazon Web Services product that enables users to track, collect and analyze their performance and operational application data running on AWS services.
You can use CloudWatch to collect and store logs, monitor application and infrastructure metrics. It also provides unified dashboards, alarm systems, and logs & metrics correlation for actionable insights.
DataDog is a propriety SaaS tool that provides a range of products for application performance monitoring. Once you have signed up for a DataDog account, you can install DataDog agents to start sending performance data (logs, metrics, and traces) to DataDog Cloud for storage and analysis.
DataDog offers a range of products like log management, infrastructure monitoring, APM, and security monitoring which are available based on the pricing plan you choose.
As to which one is better suited for you – CloudWatch or Datadog; you can read this detailed comparison here.
LightStep delivers unified visibility and observability across the multi-layered architecture. It allows teams to identify and resolve regressions, regardless of the complexity and scale of the system. It helps to improve the way you build and operate microservices.
Graylog is used in conjunction with LogStash as a centralized server. With its usage, one can easily explore data within the system. Moreover, it’s easily scalable.