AWS CloudWatch vs. Telegraf

There is no shortage of options when it comes to real-time monitoring applications. There are several that allow preventive as well as corrective actions notifying the administration team well in advance. However, as Metric Collector and Metric Storage, Telegraf and AWS CloudWatch, respectively, offer much more than this. They are convenient to set up, can be employed on-premise or on the cloud.

Understanding AWS CloudWatch

AWS CloudWatch is a tool from Amazon that allows system architects, developers, and administrators to help them perform real-time monitoring of their AWS applications hosted on the cloud. The software is automated and configured to give metrics on latency, request counts, CPU usage, etc.

Codebase

According to our research, CloudWatch code is based on telegraf agent. Because of the similar structure of the launch log and config file. More info here

The need for AWS CloudWatch

The CloudWatch software also supports custom metrics, and users can push their logs directly to CloudWatch for monitoring purposes. The reports and data that the software generates allow administrators to track resource usage, application performance, any constraints, and operational issues. In other words, the tool is critical for foreseeing and resolving technical issues well in time to streamline organization-wide operations.

However, the most significant benefit of CloudWatch is that it is done to integrate automatically with Amazon Web Services (AWS) while being scalable and flexible.

Features of AWS CloudWatch

The Amazon CloudWatch is equipped with salient features, which are:

Data Collection

The AWS CloudWatch allows users to collate and store real-time data logs from different apps, resources, and services. Typically, these include vendor logs, logs published under the AWS services banner, and custom-designed logs. The logs can be quickly published by installing the AWS CloudWatch agent.

The software comes with many built-in metrics, but users can also customize as per their requirements. You can aggregate the collected container logs and metrics within the ecosystem as well.

Monitoring

The AWS CloudWatch dashboards allow system administrators to visualize their resource performance on the cloud by creating reusable visual graphs. The central dashboard offers logs data and graph metrics in a unified view so that you can act on the issue in a faster manner. Gaining knowledge of the context is key to understanding and resolving the root cause of the problem.

AWS CloudWatch also simplifies the analysis of between metrics and logs so that you can move on from diagnosis to resolution.

Automation

The AWS CloudWatch comes equipped with Auto Scaling to automate the application’s resource planning and capacity monitoring. You can set alarms and even trigger automated action.

With CloudWatch Events' help, users can view a real-time stream of events describing any changes to the AWS resources. As a result, your response time reduces, and you can correct the issues faster.

Analysis

With AWS CloudWatch, users can view trends in real-time and retain nearly 15 months of data for analysis purposes. This historical data can prove to be the key to fine-tuning the utilization of resources. The software also provides granular data in real-time, thereby creating better visualization and analysis to optimize application performance.

Security

The AWS CloudWatch software is predesigned to integrate with IAM — AWS Identity and Access Management. As a result, the system administrators can define which resources or users can access the controls and data. Further, the data is encrypted while it is being transferred, also ensuring security and compliance.

Advantages of AWS CloudWatch Agent

The advantages of using AWS CloudWatch agent include:

● The convenience of switching between essential monitoring and detailed monitoring depending on your automated monitoring requirements.

● The same software is capable of monitoring other resources as well.

● You have the ease of creating custom metrics and monitoring using these for your particular applications. These metrics can be made using basic API requests.

● You can automatically troubleshoot, maintain, and store affected log files in case of an error. The views can be represented in graphs for better understanding.

● As one of the best software for checking and monitoring cloud resources, the AWS CloudWatch agent enables quick response and effective monitoring in one single package.

Understanding Telegraf

Telegraf is an agent for collecting, aggregating, processing, as well as writing metrics. It is an open-source server agent that helps collect data from stacks, systems, and IoT sensors.

The need for Telegraf

Telegraf’s primary purpose is data collection and transmission. The software performs this employing different components, including databases, systems, and IoT sensors. The software can connect to various data sources like MySQL, MongoDB, Redis, etc., to collate and transmit metrics. Metrics can then be collected from a varied stack of cloud platforms, orchestrators, and containers. It also enables collecting critical stateful data like temperature levels, pressure levels, etc., by connecting with various IoT devices and sensors.

Coverage

Telegraf simplifies metric collection from your endpoints as it comes with more than 200 plugins defined by SMEs (subject matter experts) from the community. Designing and building plugins are straightforward, meaning that you can develop customized plugins that cater to your particular monitoring requirements. Above all, the Telegraf monitoring software can be used to parse any input data formats directly into metrics, including JSON, InfluxDB Line Protocol, Value, Graphite, Collectd, and Nagios.

Agent

Plugins drive Telegraf for data collection as well as data output making it easily extendable. The software application can collect metrics covering a wide range of input avenues and code them into an equally wide range of outputs. Written in Go, the code is a standalone, compiled binary that can be implemented without external dependencies. In other words, it does not require npm, gem, pip, or such package management tools.

Convenience

The Telegraf plugin architecture comes with the flexibility to support your internal organizational processes. You need not modify your workflows to suit the application’s technology. It can be a centralized platform, or you can place it on the system's edge to fit your process requirements. In other words, it is incredibly convenient to implement.

Advantages of Telegraf

Like AWS CloudWatch, Telegraf comes with several advantages and negligible disadvantages.

● Like AWS CloudWatch, the Telegraf open-source monitoring solution is also a cohesive stack catering to all your monitoring requirements in one package.

● A single Telegraf agent is capable of functioning as multiple exporters with bare minimum handling requirements.

● The open-source platform is readily available to one and all and is continuously updated by the community with the latest developments.

● Telegraf agent comes with a wide array of metrics, and users can customize these to suit their organizational monitoring requirements.

● The software also comes with its set of multiple plugins that are more than enough for most organization-wide requirements. However, in case more is required, then additional plugins can be customized using different languages.

Popular CPU Metrics for AWS CloudWatch and Telegraf Agent

Both AWS CloudWatch and Telegraf come with an extension of metrics that support their monitoring capabilities.

Some popular CPU metrics are:

● cpu_time_active

This metric refers to the amount of time for which the CPU remains active irrespective of the capacity. These monitoring software tools are capable of measuring this metric in hundredths of one second.

● cpu_time_guest

This metric refers to the amount of time for which the CPU operates a virtual CPU for guest OS (operating system). Like most other monitoring metrics, this metric is also measured one-hundredths of a second.

● cpu_time_guest_nice

This metric refers to the total amount of time for which the CPU operates a virtual CPU for a guest OS. Typically, this operating system is low in priority. As a result, it can be interrupted by other more critical processes. Its measurement is done in hundredths of a second.

● cpu_time_nice

This metric refers to the total amount of time for which the CPU is in actual user mode while operating low priority processes. These are processes that can be interrupted by other higher-priority methods quickly. The tools are capable of measuring this metric in hundredths of a second for efficient monitoring.

● cpu_usage_active

As the name suggests, this metric refers to the total percentage of time for which the CPU remains active in any capacity. The percentage is the unit of measurement for this metric.

Other popular CPU metrics include:

● time_user (float)

● time_system (float)

● time_idle (float)

● time_active (float)

● time_nice (float)

● time_iowait (float)

● time_irq (float)

● time_softirq (float)

● time_steal (float)

● time_guest (float)

● time_guest_nice (float)

● usage_user (float, percent)

● usage_system (float, percent)

● usage_idle (float, percent)

Conclusion

In all instances where applications are deployed on Amazon Web Services (AWS), users have pre-configured AWS CloudWatch for automated monitoring and insights.

There are a few things to keep in mind:

  • AWS CloudWatch agent will collect metrics like a disk, network, and CPU utilization, and it cannot measure EC2 memory consumption or default disk utilization.

This gap is effectively filled in by Telegraf, which is highly suitable for EC2 memory usage monitoring. Hence, both AWS CloudWatch and Telegraf can be complementary to each other when implemented efficiently.

So, RocketCompute.com recommends that better attention be paid to Telegraf. In our team, we have many highly specialized and technical professionals. We can help with implementation, custom plugins building, and metrics selection for monitoring.

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Vladimir Kobzev, RocketCompute