Analysis the ability to dissect the data by querying it and creating visualizations and dashboards on top of it. ![]() Storage : the ability to store data for extended time periods to allow for monitoring, trend analysis, and security use cases.Processing : the ability to transform log messages into meaningful data for easier analysis.Aggregation : the ability to collect and ship logs from multiple data sources.Modern log management and analysis solutions include the following key capabilities: This is where centralized log management and analytics solutions such as the ELK Stack come into the picture, allowing engineers, whether DevOps, IT Operations or SREs, to gain the visibility they need and ensure apps are available and perform ant at all times. This cannot be done in environments consisting of hundreds of containers generating TBs of log data a day. Long gone are the days when an engineer could simply SSH into a machine and grep a log file. Not only that, the sheer volume of data generated by these environments is constantly growing and constitutes a challenge in itself. Architecture has evolved into microservices, containers and orchestration infrastructure deployed on the cloud, across clouds or in hybrid environments. What has changed, though, is the underlying architecture of the environments generating these logs. Logs have always existed and so have the different tools available for analyzing them. This data, whether event logs or metrics, or both, enables monitoring of these systems and the identification and resolution of issues should they occur. To ensure apps are available, perform ant and secure at all times, engineers rely on the different types of data generated by their applications and the infrastructure supporting them. For the same reason, organizations cannot afford to be compromised as well, and not complying with regulatory standards can result in hefty fines and damage a business just as much as a performance issue. Performance issues can damage a brand and in some cases translate into a direct revenue loss. In today’s competitive world, organizations cannot afford one second of downtime or slow performance of their applications. Why is Log Analysis Becoming More Important? ELK is a simple but robust log management and analytics platform that costs a fraction of the price. ELK might not have all of the features of S plunk, but it does not need those analytical bells and whistles. S plunk has about 15,000 customers while ELK is downloaded more times in a single month than S plunk’s total customer count - and many times over at that. But its numerous functionalities are increasingly not worth the expensive price - especially for smaller companies such as SaaS products and tech startups. Sure, Splunk has long been a market leader in the space. Everyone knows how to use Kibana, right? Open source also means a vibrant community constantly driving new features and innovation and helping out in case of need. Using open source means organizations can avoid vendor lock-in and onboard new talent much more easily. With IT organizations favoring open source products, this alone could explain the popularity of the stack. The ELK Stack helps by providing users with a powerful platform that collects and processes data from multiple data sources, stores that data in one centralized data store that can scale as data grows, and that provides a set of tools to analyze the data. Monitoring modern applications and the IT infrastructure they are deployed on requires a log management and analytics solution that enables engineers to overcome the challenge of monitoring what are highly distributed, dynamic and noisy environments. The ELK Stack is popular because it fulfills a need in the log management and analytics space. ![]()
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