Introduction
In this article, we would like to share our team's positive experience with ZincSearch. We will discuss how we incorporated this solution into our workflow and explain why we chose it. Prior to using ZincSearch, our developers spent approximately an hour per day on log indexing tasks. This prompted us to seek out a more effective solution that could optimize our log indexing software. Our primary objective was to enhance resource efficiency and simplify access to relevant logs for our developers.
Choosing the Right Log Indexing Solution
Initially, we considered using ElasticSearch or OpenSearch, given their popularity. However, we were aware of the significant resources required to operate them reliably.
Discovering ZincSearch
In light of this, we decided to explore innovative solutions and ultimately found that ZincSearch was the best fit for our needs. ZincSearch provides full-text search capabilities and is built using Golang, along with an open-source indexing library for Go called Bluge. As a lightweight alternative to Elasticsearch, ZincSearch is quickly becoming the leading player in the document search category. Moreover, ZincSearch offers Elasticsearch-compatible APIs for applications that plan to switch from Elasticsearch to ZincSearch. GitHub's statistics confirm that ZincSearch is the fastest-growing project, further demonstrating the demand for a user-friendly and lightweight alternative to Elasticsearch.
Managing Log Storage
We found ZincSearch's Helm chart to be particularly useful, as it made deployment in the K8S much simpler.
We chose FluentBit to collect logs due to its low resource usage, resulting in a FluentBit+ZincSearch setup.
However, we did notice that the storage was filling up too quickly, and there was no option to remove old logs. To address this issue, we wrote a script to delete data older than two weeks and set it up as a cronjob to run automatically in the K8S.
Advantages of ZincSearch
When comparing Elasticsearch and ZincSearch, it is worth noting that ZincSearch offers several advantages. It is an innovative, user-friendly, and lightweight alternative to Elasticsearch, offering the same Elasticsearch-compatible APIs for easy integration with existing applications.
Conclusion
In conclusion, we have learned that there are several logging options available, and it may not always be wise to rely solely on the most popular tools. Since adopting ZincSearch, we have realized substantial business advantages. Most notably, we have saved 20% of our working hours per month, which has allowed our teams to focus on more strategic tasks, accelerating our project timelines. Additionally, we've achieved a 15% reduction in resource utilization, leading to significant cost savings. This newfound efficiency has translated into improved overall system performance.With ZincSearch, we have successfully implemented a cost-effective solution that we use regularly with great success. The software provides an efficient and reliable way to handle logs, which is essential for any project that requires quick and easy access to log data.
This article aims to provide a comprehensive account of our experience working with ZincSearch, including our integration process and our reasons for choosing this particular software. Our primary objective was to find a log indexing software that would be resource-efficient, allowing developers to quickly and easily access the relevant logs.
Initially, we considered using ElasticSearch or OpenSearch, given their popularity. However, we were aware of the significant resources required to operate them reliably. In light of this, we decided to explore innovative solutions and ultimately found that ZincSearch was the best fit for our needs. ZincSearch provides full-text search capabilities and is built using Golang, along with an open-source indexing library for Go called Bluge. As a lightweight alternative to Elasticsearch, ZincSearch is quickly becoming the leading player in the document search category. Moreover, ZincSearch offers Elasticsearch-compatible APIs for applications that plan to switch from Elasticsearch to ZincSearch. GitHub's statistics confirm that ZincSearch is the fastest-growing project, further demonstrating the demand for a user-friendly and lightweight alternative to Elasticsearch.
We found ZincSearch's Helm chart to be particularly useful, as it made deployment in the K8S much simpler. We chose FluentBit to collect logs due to its low resource usage, resulting in a FluentBit+ZincSearch setup. However, we did notice that the storage was filling up too quickly, and there was no option to remove old logs. To address this issue, we wrote a script to delete data older than two weeks and set it up as a cronjob to run automatically in the K8S.
When comparing Elasticsearch and ZincSearch, it is worth noting that ZincSearch offers several advantages. It is an innovative, user-friendly, and lightweight alternative to Elasticsearch, offering the same Elasticsearch-compatible APIs for easy integration with existing applications.
In conclusion, we have learned that there are several logging options available, and it may not always be wise to rely solely on the most popular tools. With ZincSearch, we have successfully implemented a cost-effective solution that we use regularly with great success. The software provides an efficient and reliable way to handle logs, which is essential for any project that requires quick and easy access to log data.
