ELK Kubernetes Stack in Cloud-Native Way — Scope About Retail Industry

December 3, 2019

What is ELK Stack?

"ELK" is an acronym for three major open source projects: Elasticsearch, Logstash and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that simultaneously ingests data from multiple sources and transforms it, then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.

 

Why ELK stack?

When Data constantly flow into your systems, it can quickly grow to be fat and stale. As it grows larger, your analytics will slow up, resulting in sluggish insights, which is likely to be a serious business problem. So, the BIG question for your Big Data is how can you maintain valuable business insights?

The solution is ELK stack which makes it way easier and faster to search and analyze large data sets. A detailed description of this ELK is given below.

 

Elasticsearch — The Amazing Log Search Tool

Elasticsearch is an open-source, extensively distributable, promptly adaptable, web search tool that is available through a broad and expounds API. Elasticsearch can control incredibly quick searches that help your information revelation applications.

 

Elasticsearch is a powerful solution for your data extraction problems. A single developer can use it to find the needless data in the heap so that it saves both time and manpower. 

 

Few Elasticsearch features are listed below:

 

  1. Elasticsearch simplifies data ingest, visualization, and reporting.

  2. It helps in fast and Incisive search against large volumes of data.

  3. Real-time data and real-time analytics.

  4. Elasticsearch comes with a wide set of features like scalability, high-availability and multi-tenant.

Logstash — Routing Your Log Data

Logstash is one of the core products of the Elastic Stack, which is used to aggregate and process data and send it to Elasticsearch. Logstash is an open-source, server-side data processing pipeline that enables you to ingest data from multiple sources simultaneously and enrich and transform it before it is indexed into Elasticsearch.

 

Kibana — Visualizing Your Log Data

Kibana is a data visualization and management tool for Elasticsearch that provides real-time histograms, line graphs, pie charts, and maps. Kibana also includes advanced applications such as Canvas, which allows users to create custom dynamic infographics which are suitable for their data, and Elastic Maps for visualizing geospatial data.

 

Kibana is a stylish interface for visualizing logs and time-stamped data. When Logstash is used along with kibana it can also serve as an improvised dashboard for graphical analysis of any dataset.

 

ELK Stack Architecture

The following is the architecture of ELK Stack which shows the proper order of log flow within ELK. Here, the logs generated from various sources are collected and processed by Logstash, based on the provided filter criteria. Logstash then pipes those logs to Elasticsearch which then analyzes and searches the data. Finally, using Kibana, the logs are visualized and managed as per the requirements.

 

                                           Fig.1.:Architecture of ELK Stack. 

 

 

ELK in Production-Environment

For those companies who are receiving thousands of logs coming on every second and they need a centralized and scalable solution that would allow them to search across these logs quickly, then ELK stack is the best solution.

 

1: E Commerce Industry:

To build the new e-commerce platform, ELK stack was used to support the volume of transactions operated by stores on the platform. Below I have described How ELK stack is used in the E-commerce industry

 

2: Supply chain service Industry:

For supply chain services providers it helps to take a few decisions based on logs in less time which impacts cost, revenue, service and so on.

To maintain a high level of operations, these industries need to know everything that’s going on all the time. Every minute they capture the lot more data from the field, including the size, location, and status of all its shipments. It is difficult for them to analyze the data stored in databases like MongoDB or any other if the data size is bulk, so ELK stack helps them to solve all major issues regarding analyzing the data.

 

3: Insurance or finance companies:

Any Insurance or finance companies are no longer needs to write scripts or spend days to investigate IT events. They can gather and visualize the data they need and respond to events immediately. It reduced the complexity and cost of analytics and also Using Kibana has empowered everyone to analyze data, removing the need for data engineers to do the job.

 

How can we use the ELK stack to manage log data

 

Let us consider one example, here we took data of a company named GrabnPay.

 

Grabnpay India is a budget online store launched in India as a division of Grabnpay group UK. Over the years of its trustworthy services, Graclient satisfaction, and also the quality of products delivered to the shoppers, Grabnpay has evolved itself as darling alternative to stay themselves travel with the newest trends in fashion clothes, accessories, gifts and an exclusive collection of home & Kitchen accessories. The versatility and also the vary of products out there continuously build the shop distinctive.

 

This company is highly optimising their weekly to monthly operations by considering the analysis constantly and reducing the expenses gradually in product returns from customers, inventory management, regional delivery. Log on to their website to know more about them.

 

They are facing issues while analyzing their data such as:

  • How many orders dispatched per day?

  • Which state has more number of orders?

  • What is the revenue on a daily basis?

  • How many orders got returned every day/week? and so on

They got an optimized solution to all their problems with one powerful tool named ELK stack. This tool helps them to analyze the data easily and quickly.

 

They are trying to analyse the city which got more number of orders, so that they can concentrate more on shipping and placement of orders and also they can take special attention on those cities where the order traffic is less. But analysing manually causes more time consuming so Elk helps to overcome from this issue.

 

                               Fig.2.: Pie chart shows the list of orders received from the cities.

 

The above pie chart shows the cities which got the highest number of orders, where Kolkata ranks first and Secunderabad at last. This helps the user to analyze easily and graphical representation helps them to make decisions regarding the business fast. It depends on the user according to their convenience they can choose the chart type.

 

                                  Fig.3.: Pie chart shows the orders received from the states.

 

The above pie chart shows the states from where the orders are received. 

 

They were facing another issue regarding the cancellation of the order. When they analyzed it with the help of elk, they got to know that the cancellation of the order percentage is more, which was more due to the lack of communication between the customers. Later they started to interact with the customers, and find a solution to this problem. This reduces the issue and now the cancellation of order percentage is about 3.23%.

 

 

                          Fig.4.: Pie chart shows the order confirmations.

 

Summary:

 

The ELK stack finds a major role in the log analytics sector. The retail industry, e-commerce, healthcare services and most of the companies where the data are bulk and analyzing them takes a lot of time and effort finds this as an amazing tool. Kibana helps them to visualize the data in a graphical representation which makes the user easily understand the logs and helps them in taking effective business ideas.

 

For more details about cloud-native Microservices & cloud-native stack transformation, please refer to Yobitel Communications. 

 

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