Logging your system’s activity is crucial for maintaining its proper function. Logs provide valuable insights into problems as they arise and help you gauge your software’s performance over time, highlighting areas of success and identifying potential failures.

When each component of your infrastructure generates its own logs, managing them can become overwhelming, often resulting in dozens of disparate logs. This is where log monitoring tools come into play, offering a streamlined approach to handling logs.

Centralised Logging

While having multiple log sources is unavoidable, managing and analysing them independently is impractical. Centralised logging simplifies this process by consolidating log management through the following key components:

• Log Collection and Transport: To gain real-time insights, logs must be collected and transported either via an API or by configuring systems to send logs directly to a centralised log manager. Consideration must be given to packet loss and methods to mitigate it during this process.

• Log Storage: Choosing the right monitoring solution involves evaluating factors like data volume and retention periods to ensure that logs are stored efficiently and for the required duration.

• Log Analysis: Effective log analysis relies on categorising logs, visualising data, and identifying recurring patterns or emerging trends. This analysis can help establish baselines and set thresholds for monitoring. Many modern solutions leverage AI to automate and enhance this analysis.

• Alerting: Once thresholds are established and software behaviour is understood, integrating your monitoring solution with alerting tools ensures you receive immediate notifications if issues arise.

Log monitoring extends beyond simple log management and is integral to various other monitoring practices, including: Server, Network, Application, Database, Cloud Monitoring

Centralised logging not only simplifies the management of multiple log sources but also enhances the overall efficiency of your monitoring processes, ensuring that you remain informed and responsive to potential issues.

1. LogicMonitor

LogicMonitor provides advanced log intelligence for hybrid and multi-cloud environments, centralising, correlating, and contextualising your data with a focus on data hygiene and compliance. It enables you to consolidate monitoring by correlating logs with metrics on a single platform.

With support for over 2,000 integrations, modules, and pre-built templates, LogicMonitor caters to both on-premises and cloud infrastructures. It is designed to be user-friendly, offering query options suitable for all experience levels and allowing access to raw data up to 12 months old. Metrics, logs, and anomalies are all linked to their respective devices, cloud instances, and containers.

Leveraging machine learning, LogicMonitor reduces troubleshooting times and improves workflow efficiency by automating the detection and contextualisation of anomalies. This facilitates easier root cause analysis and enhances IT operations lifecycle support through integrations with tools like ServiceNow, CMDB, and Ansible.

However, one notable drawback is that subscribing to LogicMonitor requires communication with a sales team to obtain a custom quote.

2. Logstash

Logstash is a free and open-source server-side data processing pipeline that ingests data from multiple sources. It is a key component of the ELK stack—Elasticsearch, Logstash, and Kibana. Logstash is capable of ingesting, transforming, and transferring data of any format or complexity. It can derive structure from unstructured data using grok or collect geo-coordinates from IP addresses.

Logstash offers flexible data routing through various output options and is highly customisable with over 200 plugins. If the available plugins don’t meet your needs, you can use the Logstash API to develop custom plugins.

Elastic provides both Elastic Cloud, a managed service available on major cloud platforms, and the fully configurable Elastic Stack, which can be downloaded for on-premises deployment. The Elastic Cloud starter premium package begins at $16 per month.

3. Papertrail

Papertrail aggregates and analyses logs from a wide range of sources, including syslogs, .txt files, Apache, MySQL, Ruby on Rails, Windows Events, Tomcat, Heroku, and various applications, routers, or firewalls.

It scans logs for anomalies and deviations, providing real-time alerts and summaries as needed. Papertrail supports multiple languages and platforms, such as Angular, Linux Logging Software, Ruby, NGINX, MySQL, JavaScript, HAProxy, and Golang. The platform also allows for per-user access control, ensuring data consistency, security, and integrity even when multiple team members have access.

Papertrail offers a free tier with a 48-hour search window, seven-day archive, and a 16 GB bonus for the first month, followed by a 50 MB/month quota. Paid plans start at $7 per month.

4. Sematext Logs

Sematext is a comprehensive monitoring and logging service that centralises and aggregates logs from various sources into a single location. It enables you to collect data from servers, applications, databases, containers, and other systems, providing live viewing of logs as they arrive in the cloud from multiple sources.

Sematext leverages Elasticsearch, Logstash, and Kibana for data collection, transformation, search, filtering, analysis, management, and visualisation. It offers real-time alerting for both metrics and logs, enhancing troubleshooting and anomaly detection. Integrations with tools like email, PagerDuty, Slack, HipChat, BigPanda, OpsGenie, VictorOps, WebHooks, Nagios, and Zapier facilitate seamless operations.

Running on AWS infrastructure, Sematext adheres to strict IT security best practices, with logs encrypted via HTTPS and transmitted through TLS/SSL channels. It also supports permission restrictions to control team member access.

5. Dynatrace

Dynatrace provides Log Monitoring as part of its platform, enabling the creation of custom log metrics for more intelligent and efficient troubleshooting. Their Log Management solution offers comprehensive log data analysis and alerting capabilities. Dynatrace allows you to analyse log events across different parts of production and over extended periods, leveraging artificial intelligence to correlate log messages with issues detected by your monitors. This data is utilised for root-cause analysis.

You can set up custom rules and log metrics to receive notifications for anomalies or threshold breaches. Dynatrace offers two modes for log monitoring: Log Monitoring v1 and Log Monitoring v2. While v2 is the newer version, addressing issues like unrecognised timestamps with a generic log data ingestion engine, it still lacks some features present in v1, such as sensitive information masking, UI configuration files on hosts, and on-demand access to log files on monitored hosts.

Dynatrace’s platform can be complex and may require a learning curve. It offers both full-stack monitoring solutions and various individual plans.

6. Datadog

Datadog’s Log Management provides comprehensive visibility into cloud-scale infrastructure by aggregating metrics and events from over 500 integrated technologies. It supports tagging and storing logs, and allows for their collection, search, and analysis. You can correlate logs with specific traces, metric spikes, or security signals.

The platform is intuitive, enabling easy correlation of individual logs and pattern discovery. Data visualisation is facilitated through customisable, drag-and-drop dashboards, and log querying does not require knowledge of a query language. Datadog’s machine learning-powered alerts automatically detect anomalies and log errors.

Additionally, Datadog’s Log Management helps identify potential threats, uncover misconfigurations, and monitor logs using threshold and anomaly detection. It also ensures the security of all layers within your cloud environment, tracks the performance impact of each code deployment, and automatically maps data flows and dependencies with the service map.

7. Better Stacks

Better Stack offers structured log management with SQL-compatible querying, allowing you to search and filter petabytes of logs quickly through its custom-built data pipeline and ClickHouse. You can set up anomaly detection alerts to notify you when logs deviate from normal patterns, all while saving costs due to Better Stack’s efficiency.

The platform integrates with a wide range of stacks, including Kubernetes, Heroku, Logstash, Rails, Docker, and AWS, providing extensive monitoring options. All collected data is visualised in Grafana for comprehensive insights and efficient management. The interface is designed with a user-friendly dark mode UI.

One of Better Stack’s standout features is its built-in collaboration tools. These allow you to work with colleagues in a Google Docs-like environment, enabling you to save, share, and archive code, and collaborate effectively.

8. Sumo Logic

Sumo Logic provides a comprehensive set of log management tools for cloud, on-premises, and hybrid environments. Its centralized data visualisation helps you identify trends and address errors proactively or during damage control, speeding up root cause analysis. With features like anomaly detection, outlier detection, and predictive analytics, Sumo Logic offers deep insights into your architecture’s performance.

The platform delivers real-time visibility into AWS, Azure, and GCP cloud applications and infrastructure. It also integrates with over 150 apps and native technologies for complete out-of-the-box visibility.

Sumo Logic features two types of dashboards: the live dashboard and the interactive dashboard. The live dashboard presents real-time data as it arrives but does not allow for historical data review. For this purpose, the interactive dashboard provides a complete overview of events and trends, enabling you to focus on specific graphs and rare events. It also allows you to filter for specific errors and exceptions, helping you concentrate on critical issues in the future.