Cloud Native Logging with Fluentd (LFS242)
Fluentd log, Cloud Native Logging, Fluentd and Unified Logging, Fluentd Configuration, Fluentd with Plugins, Filtering Data, Creating Pipelines, Parsing Data, Formatting Data, Designing Effective Configurations, High Availability with Fluentd, Monitoring the Unified Logging Layer, Debugging, Tuning Fluentd, Fluent Bit
ABOUT CLOUD NATIVE LOGGING WITH FLUENTD COURSE
The Fluentd log forwarding and aggregation method are introduced in this course for use in cloud native logging. Fluentd, also known as the “unified logging layer,” provides log transformation and enrichment, as well as aggregation and routing, in a fast and efficient manner.
Because of the rising prevalence of big, distributed systems, log management has become more difficult. There are now dozens of nodes and hundreds of services outputting data that has to be attributed, standardized, and aggregated i.e. “logged” in today’s networked world. It’s called the “unified logging layer” because of the speed and efficiency with which it performs log processing, enrichment, aggregation, and forwarding.
This course is designed for people with professional experience, such as sysadmins and engineers, who need to use cloud native logging software.
After completing this course, you will be able to deploy Fluentd in a variety of production environments.
CLOUD NATIVE LOGGING LAB INFO
Access to a Linux server or Linux desktop/laptop is necessary to complete the lab exercises in this course. You’ll also need access to a public cloud service or VirtualBox installed on your desktop. The course includes detailed guidance for setting up your lab space.
You should be able to complete the lab activities using the free tier or credits offered by a cloud service such as GCP or AWS. However, you can be charged if you use more credits than the cloud provider originally allocated to you, or if the cloud provider’s terms and conditions change.
WHAT YOU WILL LEARN
This course will cover everything you need to know about Fluentd. From downloading Fluentd to running Fluentd in a container, and from using Fluentd as a basic log forwarder to using Fluentd as a sophisticated log aggregator and processor.
Learn how to:
- Create a Cloud Native Fluentd installation and configure it
- Create a Fluentd configuration for processing log data from various sources
- Filter and modify data with Fluentd
- Distribute Fluentd log data to several backends.
- Ensure that Fluentd is configured for maximum uptime and availability.
Why use Fluentd in Cloud Native?
Logging Layer unified
Data sources and backend systems are separated by Fluentd’s unified logging layer.
It is via this layer that various logs are made available to programmers and data analysts. At the same time, you’re reducing the chance that “poor data” can slow things down and confuse your company.
You and your company can make greater use of data and iterate on your software more rapidly with a uniform logging layer.
Software that is free to use and modify
Open-source software Fluentd is licensed under the Apache 2.0 License. Fluentd’s capabilities are limited only by your creativity, not licencing constraints. There is a GitHub repository for the source code.
Simple and straightforward, yet still adaptable
Using Fluentd on your laptop is quick and easy. Right now, you may download it for free and give it a go. In addition to 500+ plugins, Fluentd is able to work with a wide variety of data sources and outputs. When it comes to creating a plugin, it’s a simple process.
The Fluentd community is constantly updating the software and working together to make it more helpful to everyone.
Cloud Native – Fluentd role in Kubernetes logging
When it comes to containers, there are just too many sources of data. More detailed stack logs are created than in more typical monolithic apps at every level. As instances are built and decommissioned, their settings are altered, network proxies speak with one another, services are installed, and requests are handled, log data is produced. This information contains valuable nuggets of information that may be used to monitor and adjust the application’s performance.
Managing and adapting to the individual demands of containers at each stage of the log lifecycle is becoming more difficult due to the exponential growth in the volume of log data. Kubernetes has an open design that allows for this sort of innovation. It enables the creation of open source logging tools that can extract Kubernetes logs and analyze these logs independently.
As a result, logging technologies have risen to the occasion. The majority of these logging tools are free and open source, allowing you to tailor your logging strategy to your needs. In addition to aggregation and analysis capabilities, log visualizations are also available. Fluentd is a log aggregation tool that has climbed to the top.
The Fluentd agent may be quickly deployed using an add-on for Kubernetes. It is possible to install Fluentd using the Minikube addon if you are using Minikube. enabling the efk mode requires just the minikube addons enable efk command. Fluentd and Elasticsearch and Kibana are installed as part of this process. As compared to Fluentd, the other two use more resources and will take longer to start up, requiring greater RAM in the VM used to host them.
Operating applications in Kubernetes relies heavily on logging, which is why it is so important. As tough as it might be to log in Kubernetes, the good news is that there are solutions for every stage of the logging process. With Kubernetes, log aggregating is at the heart of the logging.
It gives you the ability to gather all logs from beginning to finish and transport them to a variety of data analysis tools. As the main log aggregator for Kubernetes, Fluentd’s ability to add relevant information to logs, as well as its minimal footprint and superior plugin library, make it suitable for Kubernetes logging requirements. In order to get Fluentd up and running, there are a number of options available.
The average salary of Cloud Native Developer in USA is $130k
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