![]() ![]() It’s a single point of information where you can find all the data that you need.ĮlasticSearch is a noSQL, document database, meant to store data that is time-related. This is a group of tools called ElasticSearch, Logstash and Kibana, which were created to help monitor your systems’ infrastructure and business goals. Some companies may have policies ensuring that their data does not leave their servers. All of those resources affect your clients’ experience. Sure, it’s a great tool, but due to its nature, it does not know much about your infrastructure, servers, ISP connection, servers’ CPU or RAM usage. You may say that answers for those questions can easily be found using tools such Google Analytics. Are you sure that your software product meets the Service Layer Agreement (SLA)? Are you sure that all payment transactions end with success? Are you sure that your clients love your product and will not give up before your goals are met? Nowadays failures may be intermittent and hard to find. Before Microservices, the Monolith crash was obvious – none of your clients could use it anymore. Creating tens, hundreds or thousands of Microservices creates a huge network of connections and dependencies between them ( Microservices hell ). You are happy that features are created quickly, developers are happy, but where is the catch?Īs we wrote size matters. They can use new technologies, learn while doing their job, thus their morale is high. Developers love new software – it is so clean, manageable, no dependencies, no legacy stuff. When you need to create new shiny features for your clients, developers create from scratch small software pieces. Getting into microservices seems easy at first glance. You may have a feeling that behind the horizon stands new danger for your ROI. Code becomes obsolete and hard to maintain. But you, reader, should know best that requirements always change. Those small, pretty small pieces of software that conquered the Monolith, split it into pieces and made changes to software easy again. And then out of nowhere Microservices arrived. The Monolith, the big, the scary, the unchangeable, the breakable, the Return of Investment (ROI) eater. We have no idea which was first: the chicken or the egg, but we know that the Monolith was the igniter of changes that we observe every day in IT. When properly used, ELK has the potential to reduce these risks and help you deliver quality in an efficient way. Microservices bring plenty of opportunity for a more efficient approach to creating software products, along with some drawbacks and potential risks. Beats is a family of lightweight data shippers that collect and send data from different machines and systems to the stack, in this case, to Logstash or Elasticsearch.In the following article we will explore the capacity of the ELK stack to get the most from a microservices approach to software development. ![]() K stands for Kibana: is a visutalization tool (a web interface) which is hosted through Nginx or Apacheįor a small-sized development environment, the classic architecture will look as follows.One more component is needed or Data collection called Beats, which led to the stack being rebranded as the Elastic Stack. ![]()
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