Datadog is a monitoring platform for cloud apps that are based on SaaS. This guide on “Datadog tutorial” will explain how IT professionals and DevOps teams can get started with Datadog and use this observability platform to its fullest. So you will learn to implement the operations and execute the features of Datadog.
Datadog is an analytics and tracking solution that can be employed for event tracking for architecture and cloud services as well as performance measure calculation. The software can keep an eye on tools, servers, and databases.
Datadog can integrate with a wide range of services, tools, and computer languages thanks to a Rest application programme interface (API). Chef, Kubernetes, Ansible, Puppet, Bitbucket integrations and Ubuntu, for example. The user interface features customisable dashboards that can display real-time graphs made up of data from many sources. To know more about this Datadog Tutorial, read below!
Datadog - Table of Contents |
Simply put, Datadog is a SaaS monitoring and analytics platform for large-scale software and infrastructure.
Datadog integrates end-to-end tracing with real-time data from hosts, capsules, databases, and applications to facilitate full-stack observability. This leads to useful alerts and effective representations.
Datadog provides more than 200 supported connectors with leading vendors and APM libraries for numerous languages.
Datadog's typical use cases include
If you want to enrich your career and become a professional in Datadog, then enroll in "Datadog Training". This course will help you to achieve excellence in this domain. |
Datadog is a widely used programme and the company that makes it is expanding rapidly. Although Datadog is doing well, competition is heating up in the application performance management market, which is also expanding rapidly.
Datadog is a top-notch network and service monitoring service ideal for small and medium-sized IT companies. Once you get past the installation process and the agent-based architecture, it has a lot to offer, such as numerous integrations, dashboards, and customizable alerts.
Datadog is a cloud-scale monitoring service that provides monitoring of databases, servers, tools, and services via a SaaS-based data analytics platform. The Datadog Agent is a piece of software that is installed on your hosts. It gathers events and metrics from hosts and sends them to Datadog, where monitoring and performance data may be analyzed.
The Datadog Agent is open-source, and its source code is available on GitHub at DataDog/datadog-agent. HTTP Strict Transport Security and Transport Layer Security (TLS) are used to secure all data exchanges between Datadog and its clients (HSTS). If encrypted communication is disrupted, the Datadog application is inaccessible.
Datadog lets you track metrics and get in-depth information about your IT infrastructure in real-time. Here are the main ways the Datadog can be used:
Customers can ingest all metrics, traces, and logs from applications, infrastructure, and third-party services using Data Dog's simple-to-use, fully-featured application. The business uses a single platform to monitor systems as well. Other advantages of Datadog however are:
Datadog has a reputation as a tool for cloud-native firms looking to monitor their infrastructure and applications. Many of these firms continued with the service as they grew, but they encountered restrictions on data ingestion and retention. As was already mentioned, Datadog is quite good at spotting problems, but determining their core causes is trickier.
Many Datadog users adore the platform's pre-built dashboards and simple user interface. The entire system may be seen through one single pane of glass. Without writing any code, you may design custom views using drag-and-drop widgets. You may simply create reports and see data in a wide range of forms thanks to a selection of visualization tools.
The Datadog agent can quickly install, configure, and connect to various services using API integrations. The intake and retention "rehydration" process may become much more expensive and difficult to manage as you delve even more into the logging analytics use case, though.
There are plenty of features of Datadog, however, the most prominent ones are:
Related Article: Datadog Interview Questions |
Depending on your browser's width, the Datadog website's navigation changes. Up to three different ways of navigation are possible. Just modify the width of your browser to adjust the navigation type.
Some prominent capabilities of the Datadog are
You may deliver and process each log that the services and equipment produce using Datadog Log Management. The Live Tail allows you to view the logs in genuine without indexing them. Each of the logs from the apps and infrastructure may be ingested, and you can use filters to dynamically select which ones to index before archiving them.
Alongside your logs and infrastructure monitoring, Datadog Software Performance Monitoring, also called as APM or tracing gives you a comprehensive insight into the performance of your application. This includes detailed traces of individual requests in addition to automatically generated dashboards for key metrics like request volume and latency. Datadog can track a request's progress throughout a distributed system when it is submitted to a program and provide you with systematic information about the request's status.
You may access the host map from the Infrastructure menu. It provides the potential to:
The much more recent events produced by the services and infrastructure are shown in the Event Explorer. Things like the following can happen:
The events gathered by the Agent and any installed integrations are automatically collected in the Event Explorer. Utilizing the personalized Agent checks, Datadog API, Events email API or the DogStatsD, you may also send your own unique events. You can use facets or search terms to filter your events in the Event Explorer. With the use of event analytics, you may combine or select events by an attribute and visualize them.
Dashboards have graphs with current performance indicators.
On the basis of metric thresholds, integration readiness, network endpoints, and other factors, monitors offer alerts and notifications.
Datadog Network Performance Measurement (NPM) allows you to see the network traffic flowing through any tagged item in the Datadog system, including hosts, services, and zones as well as containers. Group by anything, including data centers, teams, and even specific containers. Use tags to source- and destination-filter traffic. Through a customisable network page and network map, the filters are then aggregated into flows, each of which depicts the traffic between a single source and a single destination. Network parameters including speed, bandwidth, retransmit count, and source/destination details down to the IP, port, and PID levels are all included in each flow. Then, important statistics like traffic volume and TCP retransmits are reported.
Real-time user behaviors and experiences can be visualized and analyzed with Datadog Real User Monitoring (RUM). To better understand your users' behavior, you can record and view their online browsing sessions using Session Replay. You may resolve problems with program, infrastructural, and key metrics in one dashboard by correlating business and application data in the RUM Explorer in addition to seeing frontend errors, page dependencies and load times.
Event-driven programming can be written using serverless technology and uploaded to a cloud provider that controls all of the core computing resources. In order to improve performance, you can filter to functions that are producing failures, high latency, or cold starts using Serverless, which collects traces, logs and metrics from any AWS Lambda functions that are running serverless apps into one view.
Threats to your application or infrastructure are automatically discovered by Datadog Cloud SIEM also known as Security Information and Event Management. A planned attack, a system interacting with an IP that matches a threat intelligence list, or an unsafe configuration are a few examples. These risks can be connected and prioritized in the Security Explorer after being revealed in Datadog as Safety Signals.
You may develop and execute API and browser tests which proactively replicate user interactions with your applications using Datadog Synthetic Monitoring, and you can also keep an eye on all internally and externally network endpoints throughout your system's layers. To stop problems from cropping up in production, you can find faults, spot regressions, and automate rollbacks.
Datadog supports multiple technologies, including Azure, Amazon Web Services (AWS), Red Hat OpenShift, Kubernetes, Google Cloud, and Pivotal Platform.
Let's briefly examine how the following technologies interface with Datadog:
This manual covers how to report an incident using the Datadog Clipboard.
You can collect data from a variety of sources, including graphs, monitors, complete dashboards, or notebooks, using the Clipboard. This enables you to declare an incident with as much detail as feasible.
Declaring an incident is also possible through a graph, a monitor, or the events API. Users using APM can declare an incident by clicking the Alarm symbol on just about any APM graph. As part of the Slack connection, you can also declare an incident and specify its title, severity, and client effects by using the /datadog incident shortcut. By selecting the Notify button in the upper right corner after creating the occurrence, you can add more notifications.
You must be familiar with the three Datadog pricing tiers before you begin utilizing the service.
Datadog is a monitoring and analytics tool for IT and DevOps teams. It can be used to track infrastructure and cloud services for performance metrics and event monitoring.
Datadog interfaces with Google Cloud Run services to capture data in real-time and automatically scales with GCP infrastructure by monitoring newly created resources.
Yes, Datadog helps organizations build a culture of being able to see what's going on, working together, and sharing data. These are all important parts of the DevOps movement.
Datadog is a modern Software as a Service (SaaS) tool that aggregates data from applications, infrastructures, third-party services, and cloud integrations to make your entire stack observable.
The tool Datadog has a dashboard that can be easily changed to fit the needs. The Splunk tool doesn't have such a choice. The dashboard can't be changed or made to look different. Compared to the Splunk tool, setting up and installing the Datadog tool is pretty easy.
Related Article: Datadog vs Splunk |
In the market for service monitoring, Amazon CloudWatch competes with Datadog. But only service providers can use Amazon CloudWatch, while Datadog is a full-stack monitoring platform. Anomaly detection can be improved by using CloudWatch with CloudWatch Logs and EKSor personalized metrics and dashboards
Datadog Database Monitoring adds to the ability to monitor the general health and availability of the database and the underlying infrastructure by letting users find the exact queries that affect application performance and the user experience.
With the Datadog data source for Grafana, you can use Grafana to query and display Datadog metrics.
Datadog can get logs from servers, AWS EC2 instances, containers, and other cloud-based environments. Logging lets you collect, process, and keep an eye on different logs from all over the system.
Datadog's dashboards can be changed to fit your needs, and it's free for up to 5 hosts (with 1-day data retention). After that, $15 per host per month is charged to the customer. There is also a free trial for 14 days. On the website, you can see the most up-to-date prices for the Datadog infrastructure.
Datadog offers a wide variety of useful functions and is completely free to use. This Datadog tutorial will show you how to use Datadog to manage setups, monitor and record metrics. So, you should now be aware of all that Datadog is capable of, from controlling settings to monitoring and recording metrics. Our Mindmajix experts offer a Datadog Training Course to know more about the datadog concepts.So enroll now and start learning!
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Madhuri is a Senior Content Creator at MindMajix. She has written about a range of different topics on various technologies, which include, Splunk, Tensorflow, Selenium, and CEH. She spends most of her time researching on technology, and startups. Connect with her via LinkedIn and Twitter .