AWS CloudTrail vs Graylog vs Logstash

Overview

AWS CloudTrail

Stacks304

Followers280

Votes14

Logstash

Stacks12.3K

Followers8.8K

Votes103

GitHub Stars14.7K

Forks3.5K

Graylog

Stacks595

Followers711

Votes70

GitHub Stars7.9K

Forks1.1K

AWS CloudTrail vs Graylog vs Logstash: What are the differences?

### Key Differences Between AWS CloudTrail and Graylog and Logstash

1. **Purpose**: AWS CloudTrail is primarily used for monitoring and logging AWS account activity, including actions taken by users, services, or in response to AWS services. Graylog, on the other hand, is an open-source log management platform that enables users to collect, index, and analyze log data from various sources. Logstash is a data processing pipeline that allows for the collection, enrichment, and transport of log data to various destinations.
   
2. **Integration with AWS Services**: AWS CloudTrail integrates seamlessly with various AWS services, providing detailed insights into AWS account activity. Graylog and Logstash, while being flexible and customizable tools, require additional configuration and setup to integrate with AWS services and extract log data effectively.
   
3. **Vendor Lock-in**: Using AWS CloudTrail ties the user to the AWS ecosystem, limiting flexibility in terms of switching to other cloud providers or on-premises solutions. Graylog and Logstash, being open-source and configurable tools, offer more flexibility in terms of vendor lock-in, allowing users to adapt and customize according to their needs and infrastructure.
   
4. **Scalability and Performance**: AWS CloudTrail is a managed service, ensuring scalability and performance based on AWS infrastructure. Graylog and Logstash, being self-hosted solutions, require manual scaling and optimization for performance depending on the size of log data being processed.
   
5. **User Interface and Experience**: AWS CloudTrail provides a user-friendly web interface for viewing and managing logs, making it easy for users to navigate and analyze log data. Graylog offers a customizable web interface for log data analysis, providing more control and customization options. Logstash relies on configuration files for setup and lacks a built-in user interface, requiring more technical expertise for configuration and monitoring.
   
6. **Cost**: AWS CloudTrail involves costs based on data storage and API activity, making it a potential cost consideration for organizations with large amounts of log data. Graylog and Logstash, being open-source tools, offer cost-effective options for log management and analysis, especially for organizations looking to minimize expenses.

In Summary, the key differences between AWS CloudTrail, Graylog, and Logstash lie in their purpose, integration with AWS services, vendor lock-in, scalability, user interface, and cost considerations.

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Detailed Comparison

AWS CloudTrail	Logstash	Graylog
With CloudTrail, you can get a history of AWS API calls for your account, including API calls made via the AWS Management Console, AWS SDKs, command line tools, and higher-level AWS services (such as AWS CloudFormation). The AWS API call history produced by CloudTrail enables security analysis, resource change tracking, and compliance auditing. The recorded information includes the identity of the API caller, the time of the API call, the source IP address of the API caller, the request parameters, and the response elements returned by the AWS service.	Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.	Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.
Increased Visibility- CloudTrail provides increased visibility into your user activity by recording AWS API calls. You can answer questions such as, what actions did a given user take over a given time period? For a given resource, which user has taken actions on it over a given time period? What is the source IP address of a given activity? Which activities failed due to inadequate permissions?;Durable and Inexpensive Log File Storage- CloudTrail uses Amazon S3 for log file storage and delivery, so log files are stored durably and inexpensively. You can use Amazon S3 lifecycle configuration rules to further reduce storage costs. For example, you can define rules to automatically delete old log files or archive them to Amazon Glacier for additional savings.;Easy Administration- CloudTrail is a fully managed service; you simply turn on CloudTrail for your account using the AWS Management Console, the Command Line Interface, or the CloudTrail SDK and start receiving CloudTrail log files in the Amazon Simple Storage Service (Amazon S3) bucket that you specify.;Reliable- CloudTrail continuously transports events from AWS services using a highly available and fault tolerant processing pipeline.;Timely Delivery- CloudTrail typically delivers events within 15 minutes of the API call.;Log File Aggregation- CloudTrail can be configured to aggregate log files across multiple accounts and regions so that log files are delivered to a single bucket. Please refer to the of the AWS CloudTrail User Guide for detailed instructions.;Notifications for Log File Delivery- CloudTrail can be configured to publish a notification for each log file delivered, thus enabling you to automatically take action upon log file delivery. CloudTrail uses the Amazon Simple Notification Service (SNS) for notifications.;Choice of Partner Solutions- Multiple partners including AlertLogic, Boundary, Loggly, Splunk and Sumologic offer integrated solutions to analyze CloudTrail log files. These solutions include features like change tracking, troubleshooting, and security analysis.	Centralize data processing of all types;Normalize varying schema and formats;Quickly extend to custom log formats;Easily add plugins for custom data source	-
Statistics
GitHub Stars -	GitHub Stars 14.7K	GitHub Stars 7.9K
GitHub Forks -	GitHub Forks 3.5K	GitHub Forks 1.1K
Stacks 304	Stacks 12.3K	Stacks 595
Followers 280	Followers 8.8K	Followers 711
Votes 14	Votes 103	Votes 70
Pros & Cons
Pros 7 Very easy setup 3 Good integrations with 3rd party tools 2 Backup to S3 2 Very powerful	Pros 69 Free 18 Easy but powerful filtering 12 Scalable 2 Kibana provides machine learning based analytics to log 1 Great to meet GDPR goals Cons 4 Memory-intensive 1 Documentation difficult to use	Pros 19 Open source 13 Powerfull 8 Well documented 6 Alerts 5 User authentification Cons 1 Does not handle frozen indices at all
Integrations
Boundary Loggly Splunk Cloud	Kibana Elasticsearch Beats	GitHub

What are some alternatives to AWS CloudTrail, Logstash, Graylog?

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

Logentries

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

Sematext

Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.

Fluentd

Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure.

ELK

It is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.

Sumo Logic

Cloud-based machine data analytics platform that enables companies to proactively identify availability and performance issues in their infrastructure, improve their security posture and enhance application rollouts. Companies using Sumo Logic reduce their mean-time-to-resolution by 50% and can save hundreds of thousands of dollars, annually. Customers include Netflix, Medallia, Orange, and GoGo Inflight.

Splunk

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

LogDNA

The easiest log management system you will ever use! LogDNA is a cloud-based log management system that allows engineering and devops to aggregate all system and application logs into one efficient platform. Save, store, tail and search app

Related Comparisons

AWS CloudTrail vs Graylog vs Logstash: What are the differences?

### Key Differences Between AWS CloudTrail and Graylog and Logstash

1. **Purpose**: AWS CloudTrail is primarily used for monitoring and logging AWS account activity, including actions taken by users, services, or in response to AWS services. Graylog, on the other hand, is an open-source log management platform that enables users to collect, index, and analyze log data from various sources. Logstash is a data processing pipeline that allows for the collection, enrichment, and transport of log data to various destinations.
   
2. **Integration with AWS Services**: AWS CloudTrail integrates seamlessly with various AWS services, providing detailed insights into AWS account activity. Graylog and Logstash, while being flexible and customizable tools, require additional configuration and setup to integrate with AWS services and extract log data effectively.
   
3. **Vendor Lock-in**: Using AWS CloudTrail ties the user to the AWS ecosystem, limiting flexibility in terms of switching to other cloud providers or on-premises solutions. Graylog and Logstash, being open-source and configurable tools, offer more flexibility in terms of vendor lock-in, allowing users to adapt and customize according to their needs and infrastructure.
   
4. **Scalability and Performance**: AWS CloudTrail is a managed service, ensuring scalability and performance based on AWS infrastructure. Graylog and Logstash, being self-hosted solutions, require manual scaling and optimization for performance depending on the size of log data being processed.
   
5. **User Interface and Experience**: AWS CloudTrail provides a user-friendly web interface for viewing and managing logs, making it easy for users to navigate and analyze log data. Graylog offers a customizable web interface for log data analysis, providing more control and customization options. Logstash relies on configuration files for setup and lacks a built-in user interface, requiring more technical expertise for configuration and monitoring.
   
6. **Cost**: AWS CloudTrail involves costs based on data storage and API activity, making it a potential cost consideration for organizations with large amounts of log data. Graylog and Logstash, being open-source tools, offer cost-effective options for log management and analysis, especially for organizations looking to minimize expenses.

AWS CloudTrail vs Graylog vs Logstash

Overview