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npx create-strapi-app
my-project
If you own a business, downtime on your website or application can lead to income and client losses. A security breach that goes unnoticed in the system can expose personal information about clients or the organization. Things can go wrong to compromise the security of an organization's system.
Effective monitoring and logging services protect business operations from potential threats. They are an essential part of every organization's technical infrastructure. These services ensure the systems run smoothly and provide insights into potential issues that systems may encounter, preventing them from worsening and affecting users.
Suppose you're a developer, DevOps engineer, or IT personnel who works with an organization's computer networks and servers and wants to improve the performance and security of your infrastructure. In that case, you'll find this article quite helpful. It will help you to make informed decisions about your monitoring and logging needs.
Let's start with understanding these terms in relation to IT infrastructure: monitoring, monitoring services, logging, and logging services.
Monitoring services, therefore, are services or tools that help you inspect your computer systems, applications, and networks to ensure everything is working smoothly. If something goes wrong, they notify you so you can fix it before it affects your users.
Logging services are services or tools that record what happens within your systems and applications. Every system event is recorded in a log. These records help you understand what happened and why, making troubleshooting and improving your systems easier.
There are lots of monitoring and logging services available in the market.
In this tutorial, we'll go over some of the most popular ones, such as Amazon CloudWatch, Datadog, Splunk, Prometheus & Grafana, and the ELK (ElasticSearch, Logstach, Kibana) Stack, covering their features, capabilities, integrations, benefits, use cases, and pros and cons.
Amazon CloudWatch is a monitoring and management platform that offers detailed insights into your applications, infrastructure, and services, allowing you to resolve issues quickly and enhance your application's performance. It is a service provided by Amazon Web Services (AWS) for developers, system administrators, and IT managers.
Real-time Monitoring: With CloudWatch, you can monitor your AWS services in real time. You can also monitor EC2 instances, RDS databases, and Lambda functions. CloudWatch enables you to collect and track metrics, create alarms that send an Amazon SNS message or perform an action, and respond to changes in your AWS environment.
Custom Metrics You can create, publish, and monitor your custom metrics if you want to monitor application-specific metrics not included by default in CloudWatch.
Alarms and Notifications One of CloudWatch's many features allows you to set up alarms to monitor metrics and send out notifications for quick response to changes in your application. You can also set alarms to automate actions when thresholds are exceeded. An example would be using Amazon SNS to alert an operator of an Auto Scaling action. You can create metric and composite alarms in Amazon CloudWatch.
Logs Management With the CloudWatch Logs service, you can collect, monitor, store, and access log files from different sources, such as AWS Lambda, AWS CloudTrail, Amazon API Gateway, etc. This helps you identify and understand the root cause of your application's behavior.
CloudWatch Dashboards Your CloudWatch dashboard allows you to easily customize and view your AWS resources and analytics in real-time. CloudWatch's customizable dashboard feature enables you to create dashboards that you can use to monitor operational data, visualize metrics, and log data all in one place.
Events CloudWatch Events provide a near-real-time stream of system events that indicate changes in the AWS resources. You can set up rules that automatically respond to and perform some actions when these event changes are detected.
Pros
Cons
Datadog is a cloud-based platform for monitoring servers, databases, and services through a SaaS-based data analytics platform. It helps organizations improve application performance and ensure the reliability of their systems.
Infrastructure Monitoring One of Datadodog's key features is its infrastructure monitoring, which provides real-time metrics, analytics, visualizations, and detailed insight into the performance of infrastructure servers, databases, and other components.
Application Performance Monitoring (APM) Datadog's APM feature helps one monitor, troubleshoot, and improve application performance. It provides detailed insights into application code, latency, and error rates.
Log Management Datadog supports centralized logging. With the Datadog log management feature, you can collect, manage, and analyze log data from all your systems and services at any scale.
Dashboards and Visualizations Datadog enables users to create customizable dashboards to get real-time data and help you keep track of critical metrics.
Alerts and Notifications Datadog's automated alerts feature notifies you of any application performance issues, anomalies, or breaches.
Datadog comes with more than 750 built-in integrations.
Pros
Cons
Splunk is a data platform for searching, collecting, monitoring, and analyzing machine-generated data using a web interface. It gives organizations full visibility into their digital operations, allowing them to identify risks and issues before they become problems. With automation support, teams can respond quickly, preventing problems from escalating. Splunk can also help you uncover data patterns and use insights to improve company operations and metrics.
Log Management The Splunk log management feature enables collecting, parsing, and analyzing log data. Types of log data include application logs, security logs, network logs, etc.
Reporting and Metrics You can create real-time reports and schedule them to run at intervals. You get the visual analysis of metrics, logs, and event data for your report.
Machine Learning Splunk incorporates AI and machine learning algorithms into its data strategy to gain insights, such as detecting anomalies, predicting trends, forecasting time series, and making smarter decisions.
Dashboards and Visualizations Create interactive, real-time dashboards that visualize data insights, like critical metrics and trends. There are also lots of visualization types to choose from, including area and line charts, bubble charts, maps, graphs, etc.
Alerting Splunk's alerting feature allows you to monitor specific conditions, get real-time updates on critical events, and respond to events. Splunk can notify you via email, Slack using Slack webhook, or configuring a custom webhook.
Pros
Cons
Prometheus and Grafana are two popular open-source tools that are often used together for monitoring and visualization.
Prometheus is an open-source monitoring solution that collects and stores metrics and insights, while Grafana is a data visualization and monitoring solution that collects, correlates, and visualizes data with dashboards. Want to add prometheus metrics to your Strapi project? You can try the Strapi plugin strapi-prometheus
from the Strapi Market place.
Prometheus
Grafana
Prometheus:
Time-Series Database Prometheus stores and collects metrics as time series data using a pull model over HTTP. Prometheus identifies these metrics by their names and key/value pairs.
Multidimensional Data Model Prometheus uses a multidimensional data model that includes labels for identifying time-series data.
Powerful Query Language (PromQL) Prometheus has a feature - PromQL, that can be used to slice and dice collected time series data into tables, graphs, and alerts.
Service Discovery Prometheus uses service discovery and static configuration to automatically discover and scrape metrics from targets.
Alerting Prometheus's alerting system uses PromQL to define the alert conditions and supports many notification channels.
Grafana:
Visualization Grafana is excellent for visualizing data from various sources in different formats, like tables, charts, and graphs.
Data Source Integrations Grafana supports multiple data sources, including Prometheus, Cloudflare, Azure Monitor, Elasticsearch, Splunk, and so on.
Custom Plugins and Extensibility Grafana's plugin system enables you to extend its functionality with various plugins, like Zabbix.
Alerting Grafan also provides an alerting feature based on the dashboard data. These alerts can be sent using different notifiers, including Email, Slack, and PagerDuty.
Prometheus Prometheus enables integrations with various exporters to collect metrics from different systems, including MongoDB, Kubernetes, Jira, Jenkins, and more.
Grafana Prometheus enables integrations with multiple data sources and supports different data plugins for additional functionalities.
Pros
Cons
The Elastic, Logstash, and Kibana (ELK) Stack comprises three open-source tools: Elasticsearch, Logstash, and Kibana. These tools enable users to take data from any source, search, analyze, and visualize it in real time. Integrating Elasticsearch to your Strapi project can be done using the Strapi plugin strapi-plugin-elasticsearch
from the Strapi Market place.
Elasticsearch
Search and Analytics Engine Elasticsearch is a distributed search and analytics engine that stores your data so you can index, search, and analyze them.
Scalability Elasticsearch can scale horizontally to meet your needs, handle large volumes of data, and balance multi-node clusters.
Full-Text Search Elasticsearch's full-text search functionality enables searches within full-text fields to find the most relevant documents. The full-text queries allow you to search the analyzed text fields.
Logstash
Data Ingestion Logstash is a server-side data processing pipeline that ingests data from multiple sources, transforms it, and sends it to your desired storage location (e.g., Elasticsearch).
Main Components The Logstash pipeline has three main components or stages - inputs, filters, and outputs. The inputs are used to get data into Logstash. The filters are where the data is processed and transformed. The output is the final phase of the Logstash pipeline, and it's where the processed data is sent (Elasticsearch, file, graphite, or statsd)
Plugin Ecosystem Logstash has over 200 plugins for inputs, filters, and outputs that can be used to customize your data pipeline.
Kibana
Visualization Kibana offers visualization capabilities in addition to Elasticsearch data. You can create bar charts, line graphs, pie charts, and maps. Kibana also lets you generate visualization for metrics like count, average, sum, min, max, standard deviation, etc.
Dashboard Creation Kibana lets you create and share dashboards that combine a collection of visualizations (charts, maps, filters) to display the full picture of your data and aid decision-making. The image panel allows you to add your own logos and graphics to personalize your dashboards.
Pros: Elasticsearch offers advanced search and analytics capabilities and can also handle a large volume of data as it is designed for horizontal scalability.
Cons:
Feature/Service | Amazon CloudWatch | Datadog | Splunk | Prometheus & Grafana | ELK Stack (Elasticsearch, Logstash, Kibana) |
---|---|---|---|---|---|
Overview | AWS-native monitoring and management service | Cloud-based monitoring and analytics platform | Comprehensive data analysis and monitoring tool | Open-source monitoring and visualization | Open-source log management and analysis platform |
Key Features | Metrics collection, log monitoring, alarms, dashboards | Metrics, traces, logs, APM, dashboards | Log management, search, visualization, machine learning | Time-series data collection, alerting, dashboards | Full-text search, log aggregation, visualization |
Capabilities | Cloud resource monitoring, custom metrics, automation | End-to-end visibility, real-time monitoring, analytics | Advanced search and query, machine learning, alerting | Metrics collection, visualization, alerting | Log indexing, search, data visualization |
Integrations | AWS services, third-party integrations | Cloud services, third-party tools | Wide range of integrations and apps | Various exporters and integrations | Numerous log sources, data pipelines |
Use Cases | AWS resource monitoring, application performance | Full-stack monitoring, infrastructure management | Security information, operational intelligence | Infrastructure and application monitoring | Log analysis, application monitoring, data visualization |
Pros | AWS integration, easy setup for AWS users | Comprehensive features, user-friendly, scalable | Powerful search capabilities, extensive features | Open-source, flexible, highly customizable | Scalable, strong community support, flexible |
Cons | AWS-centric, can be expensive | Can be costly at scale, complex setup | Expensive, high learning curve | Requires setup and management, not a complete solution | Can be complex to configure, resource-intensive |
When selecting monitoring and logging services, remember these points to ensure you choose a solution that meets your organization's requirements.
What features does the tool have?
Ensure the tool you're considering provides services you'll need for your monitoring/logging needs, such as application performance, network monitoring, and log management.
Make sure the tool has real-time alerting functionality and customizable dashboards, as these are all important features. This might not be a priority, but you can check how long the service retains historical data.
How well does the service integrate with your existing tools and systems?
Ensure the monitoring and logging service integrates seamlessly with your systems' existing tools and platforms. The tool might not include some functionalities by default, so check to see if there are available plugins or extensions to extend its capabilities.
Can it scale to meet your business's needs?
One crucial factor, especially for large organizations, is to know if their service can scale to handle large volumes of data and more complex requirements as the infrastructure grows. It should be scalable and maintain constant and efficient system performance as it expands.
Does the service provide proper security measures?
Security is crucial to any organization, so look for services that prioritize data security, like utilizing SIEM.
What is the cost of using and maintaining the service?
If the service offers free trials or tiers, try them out before upgrading your plan or making payments. Check out the metrics on which the pricing is based, such as data volume, number of hosts, etc. Consider the subscription fee and the cost of maintaining the service.
How easy is it to use this tool?
Tools that are not user-friendly or difficult to use usually discourage potential consumers. To avoid complications, ensure the service is user-friendly and easy to configure and monitor. Ensure that the service includes thorough documentation and tutorials for users so that they can quickly resolve any issues that may come up.
The right monitoring and logging service depends on your system requirements, environment, and budget. Understanding the features, capabilities, pros, and cons of each tool allows you to make an informed decision that improves the reliability, performance, and security of your IT infrastructure.
Since monitoring and logging are essential aspects of IT infrastructure management, investing in the proper monitoring and logging services is necessary to ensure effective business operations.
Juliet is a developer and technical writer whose work aims to break down complex technical concepts and empower developers of all levels.