Log-Aggregator Microservice Design Pattern Tutorial with Examples for Software Programmers
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In this video we will
In this video we will learn about Log Aggregator design pattern for microservices. This is the 1st design principle in Observability design patterns category for microservices.
Log aggregation is the mechanism for capturing, normalizing, and consolidating logs from different sources to a centralized platform for correlating and analyzing the data. This aggregated data then acts as a single source of truth for different use cases, including troubleshooting application performance issues or errors, identifying infrastructure bottlenecks, or finding the root cause of a cyberattack.
In Microservice architecture the application consists of multiple services and service instances that are running on multiple machines. Each service instance generates information about what it is doing to a log file in a standardized format.
Log aggregation is the process of collecting, standardizing, and consolidating log data from across an IT environment in order to facilitate streamlined log analysis. Without log aggregation, developers would have to manually organize, prepare, and search through log data from numerous sources in order to extract useful information from it.
Problem Statement - Microservices generate and store logs individually within their isolated environments. This can make it difficult to audit or report on solution-wide log data that spans multiple microservices.
Solution - A log aggregator mechanism can be utilized to actively retrieve log data from individual microservice log stores (as well as log information from other solution components), and write the collected log data into a central log store. The log aggregator can further filter and consolidate log data prior to storage. The Pre-Defined Data View pattern can also be applied to support more efficient log data reporting. A special aggregator component is utilized to connect to each microservice and read and collect its logs in order to store them in a central repository.
Log Aggregator retrieves the individual log data and stores it in Log Database, from which the administrator can access them.This pattern can be applied in applied in conjunction with the Pre-Defined Data View pattern
** Usage of this Design Pattern **
1. Search, filter, and group logs - Log aggregation enables teams to use standardized facets in order to zero in on specific subsets of activity, which streamlines the log analysis process.
2. Troubleshoot in response to production incidents - Logs capture important information about system health that is crucial during outages or issues. An effective log aggregation strategy reduces manual work in these time-sensitive situations so developers can identify root causes faster.
3. Collaborate with others across the organization - Log aggregation breaks down organizational silos and improves visibility by enabling multiple teams to access the same data in a centralized platform.
4. Perform real-time monitoring - Once logs have been aggregated, teams can generate metrics from log attributes in order to visualize long-term trends and alert on log data.
** Advantages of this Design Pattern **
1. Real-Time Analysis and Monitoring.
2. Capacity Planning & AIOPs
3. Audit and Compliance
4. Mitigating Security threats
5. Data Visualization
** Chapter Timestamps **
0:00 Welcome to Log Aggregator design pattern
1:06 Agenda of tutorial
2:20 Introduction of Log Aggregator design pattern
3:47 Real world examples of Log Aggregator design pattern
6:55 Usage of Log Aggregator design pattern
8:06 Advantages of Log Aggregator design pattern
10:21 Summary of Log Aggregator design pattern
10:58 Next video on Performance Metrics design pattern for microservices
#logaggregator #observability #microservice
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Log aggregation is the mechanism for capturing, normalizing, and consolidating logs from different sources to a centralized platform for correlating and analyzing the data. This aggregated data then acts as a single source of truth for different use cases, including troubleshooting application performance issues or errors, identifying infrastructure bottlenecks, or finding the root cause of a cyberattack.
In Microservice architecture the application consists of multiple services and service instances that are running on multiple machines. Each service instance generates information about what it is doing to a log file in a standardized format.
Log aggregation is the process of collecting, standardizing, and consolidating log data from across an IT environment in order to facilitate streamlined log analysis. Without log aggregation, developers would have to manually organize, prepare, and search through log data from numerous sources in order to extract useful information from it.
Problem Statement - Microservices generate and store logs individually within their isolated environments. This can make it difficult to audit or report on solution-wide log data that spans multiple microservices.
Solution - A log aggregator mechanism can be utilized to actively retrieve log data from individual microservice log stores (as well as log information from other solution components), and write the collected log data into a central log store. The log aggregator can further filter and consolidate log data prior to storage. The Pre-Defined Data View pattern can also be applied to support more efficient log data reporting. A special aggregator component is utilized to connect to each microservice and read and collect its logs in order to store them in a central repository.
Log Aggregator retrieves the individual log data and stores it in Log Database, from which the administrator can access them.This pattern can be applied in applied in conjunction with the Pre-Defined Data View pattern
** Usage of this Design Pattern **
1. Search, filter, and group logs - Log aggregation enables teams to use standardized facets in order to zero in on specific subsets of activity, which streamlines the log analysis process.
2. Troubleshoot in response to production incidents - Logs capture important information about system health that is crucial during outages or issues. An effective log aggregation strategy reduces manual work in these time-sensitive situations so developers can identify root causes faster.
3. Collaborate with others across the organization - Log aggregation breaks down organizational silos and improves visibility by enabling multiple teams to access the same data in a centralized platform.
4. Perform real-time monitoring - Once logs have been aggregated, teams can generate metrics from log attributes in order to visualize long-term trends and alert on log data.
** Advantages of this Design Pattern **
1. Real-Time Analysis and Monitoring.
2. Capacity Planning & AIOPs
3. Audit and Compliance
4. Mitigating Security threats
5. Data Visualization
** Chapter Timestamps **
0:00 Welcome to Log Aggregator design pattern
1:06 Agenda of tutorial
2:20 Introduction of Log Aggregator design pattern
3:47 Real world examples of Log Aggregator design pattern
6:55 Usage of Log Aggregator design pattern
8:06 Advantages of Log Aggregator design pattern
10:21 Summary of Log Aggregator design pattern
10:58 Next video on Performance Metrics design pattern for microservices
#logaggregator #observability #microservice
** CHECK OUT OUR OTHER VIDEOS **
Shared Database per Service Design Pattern Shared Database Per Service Design Pa...
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Check out our channel here:
@codeonedigest
Don’t forget to subscribe!
** OUR WEBSITE **
https://codeonedigest.wordpress.com/
** GET IN TOUCH **
Email us on [email protected]
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در تاریخ 1402/02/07 منتشر شده
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