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  1. Stackups
  2. DevOps
  3. Log Management
  4. Log Management
  5. Amazon CloudWatch vs Loggly

Amazon CloudWatch vs Loggly

OverviewComparisonAlternatives

Overview

Loggly
Loggly
Stacks269
Followers304
Votes168
Amazon CloudWatch
Amazon CloudWatch
Stacks12.0K
Followers8.2K
Votes214

Amazon CloudWatch vs Loggly: What are the differences?

### Introduction
In this comparison, we will explore the key differences between Amazon CloudWatch and Loggly, two popular tools for monitoring and managing logs in a cloud environment.

### 1. Scalability:
Amazon CloudWatch offers auto-scaling capabilities, allowing users to adjust resources automatically based on the demand. On the other hand, Loggly provides scalability through its cloud-based architecture, which can handle large volumes of log data efficiently.

### 2. Data Sources:
Amazon CloudWatch primarily focuses on monitoring and managing metrics and log data from AWS services, while Loggly supports log data from a wide range of sources, including both cloud-based and on-premises infrastructure.

### 3. Search and Analysis:
Loggly offers advanced search and analysis functionalities, including the ability to set up alerts and dashboards, making it easier for users to pinpoint and troubleshoot issues in their log data. Amazon CloudWatch provides basic search and filter options but may not offer the same level of depth in analysis as Loggly.

### 4. Customization:
Loggly allows users to create custom parsing rules and tags for log data, providing more flexibility in organizing and structuring the data for analysis. Amazon CloudWatch, while customizable to some extent, may not offer the same level of customization options as Loggly.

### 5. Pricing Model:
Amazon CloudWatch follows a pay-as-you-go pricing model, where users are charged based on the resources and metrics they use. In contrast, Loggly offers tiered pricing plans based on the volume of log data processed, making it easier for users to estimate costs.

### 6. Integration:
Amazon CloudWatch seamlessly integrates with other AWS services, making it a preferred choice for users already utilizing the AWS ecosystem. Loggly, on the other hand, offers integrations with various third-party tools and services, making it a more versatile option for users with diverse technology stacks.

In Summary, the key differences between Amazon CloudWatch and Loggly lie in scalability, data sources, search and analysis capabilities, customization options, pricing models, and integration capabilities.

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Detailed Comparison

Loggly
Loggly
Amazon CloudWatch
Amazon CloudWatch

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

It helps you gain system-wide visibility into resource utilization, application performance, and operational health. It retrieve your monitoring data, view graphs to help take automated action based on the state of your cloud environment.

See what your application is doing during development;Catch exceptions and track execution flow;Graph and report on the number of errors generated;Search across multiple deployments;Narrow down on specific issues;Investigate root cause analysis;Monitor for specific events and errors;Trigger alerts based on occurrences and investigate for resolutions;Track site traffic and capacity;Measure application performance;A rich set of RESTful APIs which make data from applications easy to query;Supports oAuth authentication for third-party applications development (View our Chrome Extension with NewRelic);Developer ecosystem provides libraries for Ruby, JavaScript, Python, PHP, .NET and more
Basic Monitoring for Amazon EC2 instances: ten pre-selected metrics at five-minute frequency, free of charge.;Detailed Monitoring for Amazon EC2 instances: seven pre-selected metrics at one-minute frequency, for an additional charge.;Amazon EBS volumes: eight pre-selected metrics at five-minute frequency, free of charge.;Elastic Load Balancers: thirteen pre-selected metrics at one-minute frequency, free of charge.;Amazon RDS DB instances: thirteen pre-selected metrics at one-minute frequency, free of charge.;Amazon SQS queues: eight pre-selected metrics at five-minute frequency, free of charge.;Amazon SNS topics: four pre-selected metrics at five-minute frequency, free of charge.;Amazon ElastiCache nodes: twenty-nine pre-selected metrics at one-minute frequency, free of charge.;Amazon DynamoDB tables: seven pre-selected metrics at five-minute frequency, free of charge.;AWS Storage Gateways: eleven pre-selected gateway metrics and five pre-selected storage volume metrics at five-minute frequency, free of charge.;Amazon Elastic MapReduce job flows: twenty-three pre-selected metrics at five-minute frequency, free of charge.;Auto Scaling groups: seven pre-selected metrics at one-minute frequency, optional and charged at standard pricing.;Estimated charges on your AWS bill: you can also choose to enable metrics to monitor your AWS charges. The number of metrics depends on the AWS products and services that you use, and these metrics are free of charge. Learn more about this option.
Statistics
Stacks
269
Stacks
12.0K
Followers
304
Followers
8.2K
Votes
168
Votes
214
Pros & Cons
Pros
  • 37
    Centralized log management
  • 25
    Easy to setup
  • 21
    Great filtering
  • 16
    Live logging
  • 15
    Json log support
Cons
  • 3
    Pricey after free plan
Pros
  • 76
    Monitor aws resources
  • 46
    Zero setup
  • 30
    Detailed Monitoring
  • 23
    Backed by Amazon
  • 19
    Auto Scaling groups
Cons
  • 2
    Poor Search Capabilities
Integrations
Heroku
Heroku
Amazon S3
Amazon S3
New Relic
New Relic
AWS CloudTrail
AWS CloudTrail
Engine Yard Cloud
Engine Yard Cloud
Cloudability
Cloudability
No integrations available

What are some alternatives to Loggly, Amazon CloudWatch?

Papertrail

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

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.

Logentries

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.

Logstash

Logstash

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.

Graylog

Graylog

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.

Stackdriver

Stackdriver

Google Stackdriver provides powerful monitoring, logging, and diagnostics. It equips you with insight into the health, performance, and availability of cloud-powered applications, enabling you to find and fix issues faster.

Sematext

Sematext

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

Fluentd

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.

Lumigo

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

ELK

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.

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