Datadog stands out as a cloud monitoring solution. It offers a comprehensive observability suite. This suite is designed to optimize the performance and reliability of the entire application stack and infrastructure with real-time monitoring capabilities.
However, despite its widespread use in IT infrastructure, Datadog faces challenges such as high cost, limited file support, and complex logs. These shortcomings prompt a search for alternatives to address these specific needs more effectively.
In this blog, we present a curated list of 15 Datadog alternatives, each tailored to provide robust solutions that seamlessly overcome the shortcomings experienced with Datadog. Explore these alternatives to ensure you derive maximum value from your cloud infrastructure.
Datadog is a versatile cloud management solution providing cloud monitoring as a service. Tailored for IT and DevOps teams, it is a robust monitoring and analytics tool, offering performance metrics and event monitoring for infrastructure and cloud services.
Datadog integrates with all major cloud service providers, including AWS, Azure, GCP, and RedHat OpShift. It offers deployment options both on-premise and as Software as a Service (SaaS), ensuring flexibility and scalability to meet diverse organizational needs.
Customizable dashboard: Datadog's cloud cost management lets users create personalized dashboards, allowing an inclusive viewpoint of their complete infrastructure. Its adaptable dashboards enable users to visualize and comprehend their infrastructure in a simplified manner promptly. Users can quickly respond to unexpected changes with customizable cost and performance monitors.
Logs: Datadog's log management capabilities empower users to effortlessly gather, delve into, explore, sustain, and oversee logs promptly, all without initial indexing. This empowers users to reduce unnecessary compute, storage, or data transfer costs by combining cost data with performance metrics.
Alerts: The platform allows users to configure alerts using parameters such as metrics thresholds and log levels. In the event of an incident, these alerts are seamlessly delivered across multiple channels, including Slack, emails, and other mediums via webhooks.
Tags: Users gain the ability to apply tags on the analytics page to arrange data selectively. Moreover, this functionality enables data customization to focus on desired dimensions, including team, service, or AWS account.
Application performance monitoring: It provides complete visibility into modern applications. Moreover, it monitors, troubleshoots, and optimizes application performance. It does so by tracing requests from end to end across distributed systems and by tracking app performance with auto-generated service overviews.
Integration: It simplifies the aggregation of metrics and events across the full-stack DevOps tools with turnkey integration.
Synthetics: It offers end-to-end experience visibility on a single platform and uses a web recorder to monitor and capture critical user journeys. Moreover, it uses AI-powered self-maintaining tests to save on engineering resources.
RUM: It helps users establish a connection between frontend performance and business impact by visualizing lod time, frontend errors, and every resource usage for each session. Moreover, it slices and dices data based on custom attributes.
Collaborations: It offers profound visibility into various issues in context with the production data. Additionally, it helps keep track of Snapshot potential issues and notifies the team of the same. Moreover, it also tells about who has responded to the alert and who fixed it.
API: Datadog enhances observability with its full API access features. It helps users capture metrics from their applications and infrastructure. Moreover, it allows users to generate and upload JSON-formatted dashboards.
Drawbacks of Datadog
While Datadog boasts a powerful feature set and widespread adoption in cloud services, it does come with its limitations, leading users to explore alternative solutions. Here are some of these drawbacks:
Complex Log Ingestion: The log analytics process in Datadog is complex. While you can send logs to Datadog, analyzing them is impossible without indexing and retaining them. Indexing and retention come with a separate pricing structure. This complexity and cost structure prompt some organizations to limit the logs they retain, even if they require or desire more.
Expensive: It has a high licensing cost. Moreover, while Datadog excels in monitoring and detection, its effectiveness in root cause analysis and troubleshooting is hindered by the potential for significant cost escalation in Datadog logs pricing.
Lack of file support: Datadog is compatible with various data formats and sources, although it is not designed explicitly for managing an extensive range of information sources. It does not support data types like .xml, .csv, and .json.
Steep Learning Curve: The Datadog platform is known for its complexity, which can challenge less experienced teams in learning and utilizing its features.
Top 15 Datadog Alternatives
Now that we have examined Datadog’s attributes and limitations, let’s explore some alternative options that provide superior services compared to Datadog.
1. Lucidity
For many monitoring tools, prioritizing storage metrics over compute resources has not traditionally been a focus. This is because compute resources, such as virtual machines and instances, offer higher visibility and directly impact performance measurements, making them a primary area of optimization focus. Conversely, storage resources may not always be visible, leading to a limited understanding of their optimization capabilities.
However, overlooking storage can quickly become a costly affair. Storage costs increase and contribute significantly to the overall cloud cost. Virtana conducted a study titled, "State of the Hybrid Cloud Storage in 2023" on 350 IT personnel. It was discovered that
94% of these cloud decision-makers responded that their storage cost was increasing.
54% said it was increasing comparatively faster than the overall cloud bill.
This is why, when considering monitoring, it is important to observe the storage metrics as well. However, going the manual route or using monitoring tools has its disadvantages, such as
Limited Visibility: Monitoring tools may not offer a comprehensive view of all resources, potentially overlooking idle resources outside the monitoring scope.
Cost-intensive: Deploying and maintaining monitoring tools can become costly over time, especially with the increasing complexity of cloud environments, potentially leading to spiraling cloud costs. Moreover, deploying monitoring tools to perform observability over the entire storage infrastructure can be expensive.
This is why there is an urgent need for an automated storage metrics monitoring solution such as Lucidity Storage Audit.
An easy-to-deploy, executable tool, Lucidity Storage Audit automates identifying idle/unused storage resources and provides insight into the following:
Overall disk spend:
Evaluate your current disk expenditures.
Explore actionable steps to reduce costs by an impressive 70%.
Disk wastage:
Uncover the root causes of resource wastage, including idle volumes and over-provisioning.
Discover practical strategies to eliminate these inefficiencies and optimize resource utilization.
Disk downtime risk: Find out under-provisioned volumes that may run out of disk space, leading to financial damage.
What sets Lucidity Storage Audit apart from monitoring tools like Datadog?
Lucidity offers a visibility solution that stands out for its ability to provide comprehensive insights into the storage metrics. Lucidity Storage Audit proves instrumental in understanding the storage wastage and then implementing Block Storage Auto-Scaler to automate shrinkage as well as expansion of storage resources for optimal provisioning.
With our prime focus on storage resource optimization and to further understand how storage was impacting the overall cloud bill, we conducted an independent study on over 100 enterprises using leading cloud service providers like AWS, Azure, and GCP; we discovered that:
Block Storage accounted for a significant portion of the overall cloud bill.
Due to overestimation of growth leading to overprovisioning, the average disk utilization was low.
Organizations struggle with at least one quarterly downtime despite overprovisioning their storage resources.
To understand further why organizations overlook storage resource optimization, we did a comprehensive analysis and discovered that:
Implementation of Four Manual Touchpoints: Currently, the system relies on three manual touchpoints- deployment, alerting, and monitoring, each necessitating the DevOps team's involvement. This process involves navigating through three different tools to manage block storage, thereby increasing complexity and potential bottlenecks in system management.
Downtime Considerations: With certain cloud service providers, critical operations, such as shrinking 1 TB of disk space or upgrading disks, require a minimum downtime of 4 hours for the former and 3 hours for the latter. Meeting these downtime requirements poses challenges in maintaining seamless operations, mainly when uninterrupted service is paramount.
Expansion Process Wait Time: There is a minimum waiting period of 6 hours before the commencement of the subsequent expansion. This delay during the expansion process may hinder the system's ability to swiftly adjust to evolving demands, potentially affecting overall performance and responsiveness.
Due to the challenges above, organizations tend to overprovision the storage resources. But to blame the organizations solely in this regard won't be justifiable due to the following factors that come into play in optimizing storage resources.
Relying solely on tools offered by cloud service providers might be inefficient.
Creating a personalized tool seems feasible but necessitates considerable DevOps involvement and a significant amount of time.
Shrinkage of EBS Volume/ Persistent Disks/ Managed Disks is paramount, yet prominent CSPs lack an efficient live shrinkage procedure. The current workaround entails manual interference, thereby introducing the potential for errors and interruptions in operations due to instance termination, snapshot creation, and the mounting of new volumes.
This is why organizations need an automated solution to help reducehidden cloud costs like those associated with storage usage. Lucidity Block Storage Auto-Scaler is one such tool that aims to eliminate the habit of overprovisioning.
An autonomous storage orchestration solution, Lucidity has designed the industry's first block storage auto-scaler to make EBS, Managed Disk, and Persistent Disk economical and reliable, no matter the fluctuations in requirements.
Once we have identified the idle/unused resources, we deploy Lucidity Block Storage Auto-Scaler, which offers the following benefits:
Seamless shrinkage and expansion: Lucidity automates the shrinkage and expansion of storage resources, ensuring that there is always storage availability, no matter how much the requirements fluctuate.
Storage Cost Savings (up to 70%): With automated shrinkage and expansion of storage resources, you no longer have to overprovision the resources. Lucidity Block ensures that you only pay for what you use, resulting in up to 70% savings on storage costs. You can use our ROI Calculator to check how much you can save through Lucidity Block Storage Auto-Scaler. You only need to input basic details like disk spend, growth rate, and voila! You can visualize your storage cost savings.
No downtime: Manual provisioning necessitates a process that could lead to downtime. This is not the case with Lucidity. The Block Storage Auto-Scaler automatically shrinks and expands the resources depending on the changing requirements, leaving no room for downtime. Committed to zero downtime, our platform introduced a robust "Create Policy" feature. Here, users can tailor policies with specific details like desired utilization, maximum disk size, and buffer size. Lucidity Block Storage Auto-Scaler seamlessly executes shrinkage and expansion based on these policies, ensuring a downtime-free experience.
2. New Relic
New Relic offers comprehensive observability solutions with advanced logging and monitoring capabilities. It provides readily configured dashboards that enable instant data monitoring and analysis. With seamless integration across various platforms like Google Cloud Platform, Microsoft Azure, and others, New Relic facilitates correlating data from your entire environment, expediting troubleshooting processes efficiently.
Features
New Relic enables seamless data aggregation from multiple sources, providing convenient access through a unified user interface.
It prioritizes the safety and integrity of data by employing the TLS protocol for data encryption, ensuring robust security measures.
It leverages a cutting-edge machine learning engine to identify errors and anomalies, empowering quicker incident responses swiftly.
Customer Rating
G2: 4.3
3. Better Stack
Better Stack presents an observability platform comprising two core products: Logtail for log management and Better Uptime for monitoring and incident management. In this overview, we'll delve into Better Uptime's monitoring capabilities.
Better Uptime specializes in monitoring the status of applications, services, and scheduled tasks, promptly alerting users via email, SMS, Slack, or phone calls upon any incident occurrence.
Features
The customization escalation policy features allow users to set a response when any incident takes place.
Users can create different on-call calendars to assign other team members to receive alerts at different times.
It records API error messages and takes real-time screenshots to inform the organization of what happened.
The on-call schedule alerts the right colleague at the right time.
Customer Rating
G2: 4.8
4. Coralogix
Coralogix is an observability platform that analyzes logs, metrics, tracing, and security data without needing indexing or costly storage solutions. It distinguishes itself by offering built-in cost optimization features, ensuring organizations can benefit from modern observability at a fraction of the cost compared to alternatives such as Datadog.
Features
Enables intuitive and accessible data analysis through AI-driven natural language queries.
Utilizes machine learning for automated clustering of log data.
Identifies patterns and anomalies in the data.
Provides valuable insights into system behavior.
Customer Rating
G2: 4.6
5. Splunk
Splunk is a data management platform renowned for its expertise in searching, monitoring, and analyzing machine-generated data. Its capabilities extend beyond basic data processing, encompassing advanced visualization features that empower users to gain comprehensive insights from their data through graphs, reports, maps, and dashboards.
While Datadog shares similarities with Splunk in areas like infrastructure monitoring, application performance monitoring, and alerting, there are critical differences between the two platforms. Splunk offers a holistic solution, excelling particularly in Security Information & Event Management (SIEM) and IT Operations Management (ITOM), whereas Datadog focuses primarily onobservability and monitoring.
Features
Include an extensive range of data visualization options, such as dashboards and reports, to facilitate the conversion of valuable data insights into actionable intelligence.
Offers real-time visibility into system performance, security threats, and operational health.
Ability to search, monitor, visualize, and analyze real-time data.
Transforms real-time data into easily readable insights for later analysis.
Proficient in analyzing unstructured raw data.
Customer Rating
G2: 4.3
6. Dynatrace
Dynatrace is a sophisticated software monitoring solution that extends its capabilities to oversee entire cloud ecosystems. It adopts a comprehensive approach, monitoring not only infrastructure but also application security, real-time user behavior, and even business metrics. This inclusive perspective provides users with a holistic view of their system's health and performance.
Features
Discovers and collects data from different sources in the IT infrastructure.
An interactive topology map, Smartscape visualizes the relationships between all stack components.
Leverages AI technology to handle data processing and analysis. Its AI engine detects stack issues, forecasts their potential impact, and provides suggested solutions for prompt resolution.
Customer Rating
G2: 4.5
7. Prometheus
Prometheus is an open-source solution tailored for efficiently monitoring time-series data. It holds particular significance within the Kubernetes ecosystem, fulfilling a vital role in monitoring applications within containers. Prometheus empowers users to effortlessly collect time-series data, including metrics and logs, enabling them to gain valuable insights and a comprehensive understanding of their system’s performance and well-being.
Features
Users are empowered with real-time monitoring and alerting functionalities, which facilitate prompt identification and resolution of any issues in their operating environment.
Flexible service discovery mechanism for containerized environments.
Enables efficient time series storage on both local disk and in memory using a tailored format.
Customer Rating
G2: 4.5
8. AppDynamics
AppDynamics serves as a leading application performance management system, delivering real-time monitoring capabilities, and guaranteeing business applications' continuous health and excellent performance. It goes beyond primary application supervision and provides a comprehensive view of the entire infrastructure. This encompasses extensive visibility into servers, networks, and databases, empowering users with efficient troubleshooting tools. AppDynamics manages the complexities of intricate distributed applications, helping organizations streamline their operations and deliver a smooth and prompt user experience.
Features
End-user monitoring (EUM) capabilities provide organizations with valuable insights into various aspects of user experience, including error occurrences, issues, crashes, and page-loading details.
Organizations can access valuable insights to efficiently and effortlessly address customer concerns promptly.
Offers a business performance monitoring capability that connects application performance and business results. It provides valuable insights into the correlation between application performance and its impact on various business metrics.
Customer Rating
G2: 4.3
9. SolarWinds
SolarWinds is a full-stack hybrid and multi-cloud observability platform that offers users complete visibility into their cloud infrastructure and application monitoring. This visibility covers servers, virtual machines, applications, and networks.
Features
The network performance monitor enables users to troubleshoot and effectively enhance their network operations at any scale.
With the database performance analyzer, monitoring and optimizing multiple database management systems has never been easier.
The storage resource monitor provides comprehensive management reporting from different vendors for the health, performance, and capacity of various storage solutions.
The network configuration manager significantly reduces costs, saves valuable working hours, and ensures compliance through automated network configuration management and backup.
Customer Rating
G2: 4.3
10. Instana
Instana, powered by IBM, is an application performance monitoring tool that offers full-stack context to effectively comprehend the correlation between traces, calls, services, and applications. With Instana APM, software teams can effortlessly monitor the performance and availability of their applications.
Features
The system utilizes one lightweight agent on each host to continuously monitor various aspects, including real-time application performance, microservices, Kubernetes, databases, APIs, serverless architecture, and containers. It does this without any sampling, employing sensors for seamless monitoring.
Instana autonomously identifies and charts all services' consumption of observability metrics, traces each request, profiles every process, and maps all application dependencies.
Mobile app and website monitoring provide a consolidated data repository to comprehend user behavior thoroughly and promptly address any frontend concerns.
Customer Rating
G2: 4.4
11. Sematext
Sematext is one of the most affordable Datadog alternatives, offering comprehensive visibility into applications and infrastructure. It allows users to correlate logs and metrics across various areas, such as infrastructure, Real User Monitoring (RUM), and synthetic testing. This expedites the troubleshooting process and helps achieve swift issue resolution. The platform includes an auto-discovery feature for services, eliminating the requirement for extra configuration and allowing seamless streaming of logs and metrics as soon as new applications and services are detected.
Features
Enables organizations to monitor metrics from servers, applications, containers, and cloud services.
Facilitates log collection, aggregation, and analysis across an organization's technology stack.
Provides application performance monitoring and tracing for tracking requests and transactions.
Includes infrastructure monitoring for server health, resource utilization, and network performance.
Custom Rating
G2:4.7
12. Amazon CloudWatch
CloudWatch is a monitoring and management service that provides users with in-depth analyses of their AWS infrastructure, applications, and services. This platform streamlines the collection and tracking of metrics, enabling organizations to make data-driven decisions. Additionally, CloudWatch offers advanced functionality for thorough log file collection and monitoring, allowing users to gain comprehensive insights into system behavior. The inclusion of alarm settings allows for proactive management, empowering users to address emerging issues and easily and promptly optimize their AWS environment.
Features
Offers pre-configured dashboards that can be personalized according to user's needs and create tailored dashboards and reports for enhanced visibility and analysis.
The system enables real-time monitoring and alerting, empowering users to detect and promptly address issues within their AWS environment.
Automated actions and remedies are available to tackle common problems effortlessly, such as scaling resources up or down based on demand.
Customer Rating
G2: 4.3
13. Atatus
Atatus is a Software-as-a-Service (SaaS) tool for monitoring application performance, offering extensive visibility across all aspects of the stack. It enables users to collect various performance data points dynamically across multiple applications. This allows swift issue resolution and contributes to improving digital customer experiences. By providing a holistic view of application performance, Atatus is an indispensable asset for organizations searching for efficient and user-centric solutions.
Features
It gathers extensive performance data from various applications, enabling fast issue resolution and enhancing the overall digital customer experience.
It offers comprehensive insights into the application performance metrics required for delivering top-notch and dependable software.
It provides a meticulous breakdown of the factors responsible for performance degradation, including precise information on individuals involved, timing, and the specific causes.
The entire application's frontend and backend performance is evaluated by analyzing user satisfaction levels using Application Index (Apdex) scores.
Customer Rating
G2: 4.7
14. LogicMonitor
While Datadog offers robust observability solutions, LogicMonitor distinguishes itself as an agentless monitoring platform. However, similar to Datadog, LogicMonitor delivers comprehensive observability solutions that enhance visibility across applications, infrastructure, networks, website users, and containerized workloads.
Features
The dashboards are pre-configured but can also be customized to display essential parameters, enabling users to gain insights into the system's health and performance.
The alerting capabilities promptly notify users of any issues or anomalies in the system.
Utilizing dynamic topology mapping, the solution illustrates the interconnectedness between various components in your environment, providing a comprehensive understanding of their interactions.
Customer Rating
G2: 4.5
15. Sumo Logic
In its pursuit of continuous intelligence, Sumo Logic has devised a solution to address the data challenges and opportunities arising from digital transformation, cloud computing, and modern applications. The Continuous Intelligence PlatformTM offered by Sumo Logic simplifies the process of collecting, ingesting, and analyzing application, infrastructure, security, and IoT data, culminating in the extraction of valuable and actionable insights.
Features
This platform offers comprehensive visibility into the entire application configuration for accurate data analysis.
Integrating multi-dimensional patterns, comparisons, and anomaly detection with machine learning effectively detects operational issues.
Customer Rating
G2: 4.3
Look Beyond Datadog For Comprehensive Cloud Management & Efficiency!
Our blog presents diverse options, empowering users with choices and assisting organizations in refining their strategies for achieving optimal performance and cost-effectiveness. By embracing these alternatives, businesses can stay ahead in the constantly evolving digital landscape and adapt to the ever-changing demands of managing cloud infrastructure.
If grappling with challenges in efficiently identifying idle or unused storage resources or overprovisioning is straining your cloud budget, consider reaching out to Lucidity for a personalized demo. Our expertise lies in demonstrating how automation can streamline your processes and deliver substantial time and cost savings over the long term. Let us guide you through unlocking the full potential of optimizing your cloud environment, ensuring it seamlessly aligns with your needs while keeping expenses in check.