In this blog, we will see how we can deploy the Elasticsearch, Fluent-bit, and Kibana (EFK) stack on Kubernetes. EFK stack’s prime objective is to reliably and securely retrieve data from the K8s cluster in any format, as well as to facilitate anytime searching, analyzing, and visualizing of the data.
What is EFK Stack?
EFK stands for Elasticsearch, Fluent bit, and Kibana.
Elasticsearch is a scalable and distributed search engine that is commonly used to store large amounts of log data. It is a NoSQL database. Its primary function is to store and retrieve logs from fluent bit.
Fluent Bit is a logging and metrics processor and forwarder that is extremely fast, lightweight, and highly scalable. Because of its performance-oriented design, it is simple to collect events from various sources and ship them to various destinations without complexity.
Redis is a popular open-source in-memory database that supports multiple data structures like strings, hashes, lists, and sets. But similar to other tools, we can scale standalone Redis to a particular extent, but not beyond that. That’s why we have a cluster mode setup in which we can scale Redis nodes horizontally and then distribute data among those nodes.
Generally, we categorize the Redis setup into three different types:
In a Standalone setup, the complexity is minimal, but we cannot scale the solution if the data increases. Also, the fail-over and high availability will not be supported inside it.
Monitoring a Kubernetes Cluster is the need of the hour for any application following a microservices architecture. There are a bunch of solutions that one can implement to monitor their Kubernetes workload and one of them is Prometheus and Grafana. This article will help you to deploy Prometheus and Grafana in your kubernetes cluster with the help of prometheus-operator.
But before setting up these components let’s understand a bit about each of them.
Prometheus is a pull-based open-source monitoring and alerting tool originally built by SoundCloud. It works on a time-series database and scrapes metrics at a given interval from HTTP endpoints. After Kubernetes, Prometheus joined the Cloud Native Computing Foundation in 2016 as the second hosted project.
The Alertmanager takes care of alerts sent by alerting tools such as the Prometheus server. It handles grouping, silencing, and routing them to the correct receiver integration such as email, PagerDuty, Slack, etc. It also supports the inhibition of alerts.
Grafana is the visual representation of metrics collected by a data source which in our case happens to be Prometheus. We can create or import dashboards for grafana which will make use of promQL to visually represent metrics collected by Prometheus.
Before we deep dive into the topic let’s focus on why we need this tool and why we need this feature in our toolbox. In the world of errors and bugs, we will find many errors to debug and keep our system stable. So many applications need monitoring to analyze the performance of running application but what if:
we are not getting 100% analysis
only got the handled error exceptions
our applications have some anonymous errors which weren’t tracked in our system status error code and that continuously increased the load or downtime, and many more.
Will you actually debug that kind of error? How difficult is it to identify what caused Application Crash? Some organizations have set custom status codes for similar or multiple look-alike error strings but what if they are actually not similar, and you would be like “ignore, that’s our handled one we are throwing that status code”.
In the current era, organizations demand high-quality working data, and management systems that can scale, deploy quickly, robustly, are highly available, and highly secure for any unfortunate incidents. Traditionally, applications used relational databases as the primary data stores but in today’s need for data-driven applications, developers lean towards alternative databases like NoSQL(Not Only Structured Query Language).
NoSQL databases enable speed, flexibility, and scalability in this era of growing development in the cloud. Moreover, NoSQL databases also support JSON-like documents which are commonly used formats to share data in modern web applications.