Table of Contents
DataDog logo with white background

What is Datadog Log Management?

Datadog Log Management is a powerful log aggregation, analysis and monitoring solution offered by Datadog, a leading cloud monitoring and security platform. It enables organizations to centralize their logs from all their systems and applications in one place, analyze them in real-time, detect issues and anomalies, and troubleshoot problems faster.

With Datadog Log Management, you can ingest logs from any source including hosts, containers, serverless functions, cloud services, and even custom applications. It gives you complete visibility into your logs so you can understand the behavior and performance of your entire stack.

Key Features

Some of the key features of Datadog Log Management include:

  • Log Collection: Easily collect logs from any source using Datadog's log collection agent, APIs and integrations.

  • Live Tail: View your logs in real-time as they stream in using the Live Tail feature to monitor and investigate issues as they occur.

  • Parsing and Enhancements: Automatically parse your logs to extract key attributes, and enrich them with metadata from other Datadog solutions.

  • Indexes: Dynamically create indexes to search and analyze subsets of your logs for specific use cases.

  • Analytics: Use the Log Analytics to aggregate, measure, and monitor key metrics and KPIs derived from your logs.

  • Monitors and Alerts: Set up log monitors to alert you when specific log patterns and thresholds are detected indicating potential issues.

  • Dashboards: Build interactive log dashboards and visualizations to track key log metrics over time.

What it Does?

Datadog Log Management allows you to:

  • Unify logs from all your services in one centralized platform

  • Search, filter and analyze massively large volumes of logs in seconds

  • Monitor your logs in real-time to detect issues, errors and potential security threats

  • Troubleshoot application and infrastructure issues faster by correlating logs with metrics and traces

  • Derive actionable insights and KPIs from your logs to optimize performance and user experience

  • Achieve compliance by retaining complete log archives and controlling user access

Components of Datadog Log Management

The main components of Datadog Log Management are:

  1. Datadog Agent: Collects logs from hosts and sends them to Datadog. Install the agent on each host you want to collect logs from.

  2. Integration Libraries: Datadog provides integration libraries for common languages, frameworks and cloud services to send logs directly to Datadog.

  3. HTTP API: Send logs to Datadog programmatically via the HTTP Log API.

  4. Processing Pipelines: Define log processing pipelines to parse, filter, enrich and route incoming logs to specific indexes.

  5. Indexes: Indexes contain a subset of logs and are used for specific analytical purposes. Datadog automatically creates some indexes, and you can define custom ones too.

  6. Archives: Datadog archives all ingested logs to long-term storage. You can define custom retention periods and rehydrate archived logs on-demand.

  7. Security Tools: RBAC, APIs keys, and Audit Logs help you manage access to log data and meet compliance requirements.

Architecture of Datadog Log Management

Here's a high-level architecture diagram showing how logs flow through Datadog Log Management:

Who Should Use Datadog Log Management?

Datadog Log Management is best suited for organizations that:

  • Manage complex, distributed applications and infrastructure

  • Generate large volumes of logs from multiple sources

  • Need to centralize log management and analysis

  • Want to derive insights and intelligence from their logs

  • Require log data for troubleshooting, security and compliance

It is used by Development, Operations, DevOps, SRE and Security teams for various use cases such as application monitoring, incident response, threat hunting, auditing, and more.

How Does Datadog Log Management Work?

Here's how Datadog Log Management works end-to-end:

  1. Logs are collected from various sources using the Datadog agent, integration libraries or APIs and sent securely to Datadog.

  2. Incoming logs are processed by the processing pipelines where they are parsed, filtered, sampled and enriched.

  3. Processed logs are routed to one or more indexes for storage and analysis. Hot indexes (recent logs) are searchable in near real-time.

  4. All logs are archived to durable long-term storage and can be rehydrated into an index later for compliance and further analysis.

  5. Users can explore, search, filter and analyze log data in the indexes using the Logs Explorer. They can monitor key log metrics using Logs Analytics.

  6. Proactive log monitors alert the right people through email, Slack, PagerDuty when specific log patterns indicating issues are detected.

  7. Log insights are correlated with infrastructure metrics and application traces in easily sharable Dashboards and Notebooks for faster problem-solving.

To get started, install the Datadog Agent and configure it to collect logs. Here's an example of tailing logs from a file:

How to Use DataDog Log Management?

To start using DataDog Log Management, follow these steps:

  1. Sign up: Go to the DataDog website and sign up for an account. You can choose to start with a free trial or select a pricing plan that best suits your needs.

  2. Install the DataDog Agent: Download and install the DataDog Agent on your hosts. The Agent is a lightweight software that collects logs, metrics, and traces from your applications and infrastructure. You can find detailed installation instructions for various platforms in the DataDog documentation. For example, to install the DataDog Agent on Ubuntu, run the following commands:

sudo apt-key adv --recv-keys --keyserver hkp:// A2923DFF56EDA6E76E55E492D3A80E30382E94DE
sudo add-apt-repository "deb stable 7"
sudo apt-get update
sudo apt-get install datadog-agent

3. Configure Log Collection: Once the Agent is installed, configure it to collect logs from your desired sources. DataDog provides integrations for popular log sources, such as Apache, Nginx, and Docker. You can also configure custom log collection using the Agent's configuration files. For example, to collect logs from an Apache web server, add the following configuration to datadog.yaml file:

  - type: file
    path: /var/log/apache2/access.log
    service: apache
    source: apache
    sourcecategory: http_web_access

4. Explore and Analyze Logs: After log collection is set up, you can start exploring and analyzing your log data in the DataDog platform. Use the Log Explorer to search and filter logs based on various criteria. For example, to search for logs containing the word "error", enter the following query in the Log Explorer:


You can also use boolean operators and wildcards to create more complex queries:

status:error AND (service:web* OR service:api*)

Create Log Analytics to gain insights into your log data and identify patterns or anomalies.

5. Set up Dashboards and Alerts: Create custom dashboards to visualize your log data and monitor key metrics. Set up alerts to notify you of critical issues or anomalies in your log data. For example, to create an alert that triggers when the number of error logs exceeds a certain threshold, use the following configuration:

name: High Error Rate
type: log alert
query: status:error
threshold: 100
time_aggregator: sum
time_window: last_5m

6. Integrate with Other Tools: Integrate DataDog Log Management with other tools in your IT ecosystem, such as Slack, PagerDuty, or Jira, to streamline your workflow and enable collaboration.

7. Secure and Comply: Configure security and compliance settings in DataDog Log Management to protect your log data and meet regulatory requirements. This includes setting up role-based access control, configuring data scrubbing, and enabling audit logging.

By following these steps and leveraging the examples and commands provided, you can quickly set up and start using DataDog Log Management to collect, manage, and analyze your log data efficiently. DataDog's extensive documentation and support resources are available to guide you through the process and help you make the most of the platform's features and capabilities.

Bottom Line

DataDog Log Management is a powerful, cloud-based platform that enables organizations to centralize, analyze, and monitor their log data at scale. With its intuitive interface, advanced analytics capabilities, and seamless integration with other DataDog tools, it provides a comprehensive solution for log management and analysis.

By leveraging DataDog Log Management, organizations can:

  • Quickly troubleshoot issues and identify root causes

  • Optimize application and infrastructure performance

  • Detect and investigate potential security threats

  • Ensure compliance with regulatory requirements

  • Gain valuable insights into their IT environment

Whether you are a DevOps team, IT operations professional, security analyst, or developer, DataDog Log Management can help you streamline your log management process and make data-driven decisions to improve the reliability, performance, and security of your systems.

To experience the benefits of DataDog Log Management firsthand, sign up for a free trial and start collecting, analyzing, and monitoring your log data today.



View All

Learn More About Cyber Security Security & Technology

“Knowledge Arsenal: Empowering Your Security Journey through Continuous Learning”

Cybersecurity All-in-One For Dummies - 1st Edition

"Cybersecurity All-in-One For Dummies" offers a comprehensive guide to securing personal and business digital assets from cyber threats, with actionable insights from industry experts.


Recently added

View all

Learn Something New with Free Email subscription